Another core member of the hacker subset of The Com involved in a spree of extortion attacks from at least 2021 to 2023 pleaded guilty to federal charges, according to court records released Tuesday.
Ahmed Hossam Eldin Elbadawy, a 24-year-old from Texas, pleaded guilty exactly one year ago to wire fraud conspiracy and aggravated identity theft. His guilty plea wasn’t shared publicly until prosecutors filed an order of forfeiture this week seeking proceeds from Elbadawy’s criminal activities.
Elbadawy and his co-conspirators — Noah Michael Urban, a Florida man sentenced to 10 years in prison last year, and Tyler Robert Buchanan, a Scottish man who pleaded guilty to multiple cybercrimes in April and awaits sentencing — were part of an aggressive subset of The Com coined Scattered Spider.
The financially-motivated crew obtained credentials via social engineering and stole sensitive company data to identify high net worth employees with virtual currency accounts containing millions of dollars, according to an indictment filed against Elbadawy and his co-conspirators in late 2024.
Federal authorities filed charges against five individuals with links to the Scattered Spider cybercrime outfit, including Elbadawy, Urban, Buchanan, Evans Onyeaka Osiebo and Joel Martin Evans in 2024.
Elbadawy’s victims included large businesses in the entertainment, telecom, technology, business process outsourcing, IT, cloud and virtual currency sectors, officials said. Prosecutors linked Elbadawy and his co-conspirators to at least 12 victim companies in the indictment, including three businesses located in Southern California where he awaits sentencing.
Authorities detailed 29 victims who were compromised by Elbadawy and his co-conspirators. The crew stole virtual currency from wallets controlled by many of those victims. The most high-value thefts included virtual currency worth nearly $6.35 million in September 2021, $571,000 in June 2022 and nearly $1.7 million in December 2022.
Prosecutors are seeking significant property and asset forfeiture from Elbadawy, including Bitcoin valued at more than $14.19 million, Ethereum valued at more than $3.4 million and nearly $63,000 in cash. Officials also requested the forfeiture of a lifted golf cart, three luxury vehicles, a painting of Muhammad Ali, luxury watches, gold jewelry, a vast collection of designer bags and 150 pairs of shoes.
The terms of Elbadawy’s plea agreement haven’t been released.
While early leaders of Scattered Spider have been arrested or sentenced for their crimes, others have filled those roles with even more exceptional impact.
The Com has grown to thousands of members, typically between 11 and 25 years old, splintered into three primary subsets the FBI describes as Hacker Com, In Real Life Com and Extortion Com.
Criminal acts committed by these multiple, interconnected networks include swatting, extortion and sextortion of minors, production and distribution of child sexual abuse material, violent crime and various other cybercrimes.
You can read the indictment against Elbadawy and some of his co-conspirators below.
The post Early Scattered Spider member pleads guilty to cybercrime spree appeared first on CyberScoop.
Every wave of technology excitement creates a new opportunity for cyberattackers, and AI is no exception. Microsoft Threat Intelligence has published research showing a growing set of campaigns that impersonate popular AI platforms and tools, including ChatGPT, Microsoft Copilot, DeepSeek, and Claude.1 The goal is to make phishing, search-driven malware campaigns, and malvertising—which is malicious advertising that uses online ads to lure users to harmful sites, downloads, or redirect chains—more convincing. A ChatGPT-themed phishing campaign sent up to 100,000 emails in a single day, tricking users into updating their ChatGPT Plus payment information and stealing personal and credit card data. These campaigns do not represent a compromise of the AI services being referenced. They represent something more familiar—cyberattackers doing what they have always done: borrowing trust. Right now, AI brands can carry significant trust and curiosity, making them attractive themes for cyberattackers to exploit.
Understanding why this trend matters and what it means for security teams is critical to shaping a modern protection strategy. The tactics are the same ones cyberattackers have always refined: urgency, curiosity, and impersonation of something familiar to lower a user’s guard. What has changed is the wrapper. A message about a new model release, a policy update from a familiar AI assistant, or a plugin that promises to make the workday easier is today’s version of the fake invoice or the shipping notification. AI-themed lures deserve attention not because they are a passing trend tied to one product cycle, but because AI remains a genuine source of excitement and urgency for employees and consumers alike, and cyberattackers are exploiting the human instinct to explore what is new, useful, or urgent.
Microsoft’s research team recently observed several AI brand campaigns including:
In one case, an initial access broker tracked as Storm-3075 used AI-themed malvertising to distribute payloads for multiple downstream actors, a sign of how quickly this tactic is being commoditized across the criminal ecosystem.
What ties these campaigns together is not sophistication in the traditional sense. It is patience and precision in exploiting a moment. Threat actors are capitalizing on anticipated launches and emerging trends, layering multi-stage redirection chains and disposable infrastructure to slip past both users and defenses. That has real implications for security leaders: it means these incidents cannot be evaluated one surface at a time. A single AI-themed lure can begin as an email, become a malicious link, trigger a suspicious download, and end as an identity or endpoint compromise. Organizations that assess each of those as an isolated event are always a step behind. Organizations that connect them see the full shape of the cyberattack, often early enough to stop it.
In practice, protection starts before the user ever engages with the lure. Microsoft Defender’s anti-phishing policies can help detect spoofing and impersonation attempts, including user and domain impersonation, first-contact messages, mailbox intelligence signals, and other suspicious sender characteristics. For an AI-themed lure, that might look like a fake “Copilot policy update,” a spoofed support notice, or a lookalike domain designed to make a credential collection page feel legitimate.
If the campaign relies on links, Defender’s Safe Links provides URL scanning and detonation during mail flow, plus time-of-click verification when a user selects a link in email, Microsoft Teams, or supported Microsoft 365 apps. That is important when cyberattackers use redirect chains, delayed activation, or links that appear benign at delivery but later resolve to phishing infrastructure, fake sign-in pages, or malicious downloads.
For campaigns that use fake installers, malicious downloads, or weaponized attachments, Safe Attachments adds another layer by detonating attachments in a virtual environment before delivery when policies are configured. For example, if a message promotes a “new AI plugin” but includes a harmful attachment, Safe Attachments can analyze the file for malware, ransomware, or phishing behavior before it reaches the user. If a cyberthreat is identified after delivery, Defender’s post-delivery filtering capabilities help remove malicious content from mailboxes and reduce the window of exposure.
But AI-powered attacks don’t stop at email. Their objective is to gain the highest level of access possible, using compromised accounts as a foothold to move across identities, devices, and data. When a cyberattack moves beyond the inbox, Defender helps connect the evidence. Signals from email and collaboration tools, endpoints, identities, and software as a service (SaaS) apps are correlated into an attack story so analysts can see whether the same lure led to a clicked link, a downloaded payload, risky sign-in behavior, or endpoint activity.
As cyberattackers expand beyond email to gain broader access across the environment, Defender moves from detection to disruption. For multi-stage, multi-domain attacks like business email compromise or AiTM, Defender’s powerful, built-in response capability, attack disruption, will contain the compromised asset during the attack to prevent further lateral movement while security teams investigate and remediate. Attack disruption contains more than 81,000 compromised user accounts monthly and is now disrupting more than 45,000 AiTM attacks each month.
In a recent case study, Defender disrupted a business email compromise attack within four minutes of the initial activity (Figure 4). While response times may vary by scenario, this case shows the impact of attack disruption on a real cyberthreat. The cyberattacker used a convincing document-sharing lure to trick a user to start a legitimate Microsoft device code sign-in flow, which avoided traditional credential theft techniques. Defender recognized the resulting device code authentication and follow-on activity as suspicious, correlated signals across identity and email telemetry, and disrupted the attack within four minutes before the attacker could establish persistence, create inbox rules, or execute payroll fraud.
AI brands are the new bait, but the underlying lesson is bigger than any single campaign. As cyberattackers continue to exploit the momentum around AI, organizations should expect social engineering to become more targeted, more believable, and more difficult to evaluate in isolation.
The answer is not to treat every new lure as a brand-new category of risk. It is to build a protection model that makes trust harder to exploit across the full attack chain. Microsoft Defender helps organizations do that by connecting prevention, detection, investigation, and response across the attack path, so AI-themed lures are harder to deliver, harder to trust, and harder to turn into broader compromise.
To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.
1AI brands as bait: How threat actors are using the AI hype in social engineering, Microsoft Threat Intelligence. June 8, 2026.
The post Detect and disrupt AI-themed attacks with Microsoft Defender appeared first on Microsoft Security Blog.
Deceptive apps in Early Access are being used by dishonest developers for their own benefit.
The post Deceptive Android Apps Exploit Google Play Early Access to Evade Reviews appeared first on SecurityWeek.
Every wave of technology excitement creates a new opportunity for cyberattackers, and AI is no exception. Microsoft Threat Intelligence has published research showing a growing set of campaigns that impersonate popular AI platforms and tools, including ChatGPT, Microsoft Copilot, DeepSeek, and Claude.1 The goal is to make phishing, search-driven malware campaigns, and malvertising—which is malicious advertising that uses online ads to lure users to harmful sites, downloads, or redirect chains—more convincing. A ChatGPT-themed phishing campaign sent up to 100,000 emails in a single day, tricking users into updating their ChatGPT Plus payment information and stealing personal and credit card data. These campaigns do not represent a compromise of the AI services being referenced. They represent something more familiar—cyberattackers doing what they have always done: borrowing trust. Right now, AI brands can carry significant trust and curiosity, making them attractive themes for cyberattackers to exploit.
Understanding why this trend matters and what it means for security teams is critical to shaping a modern protection strategy. The tactics are the same ones cyberattackers have always refined: urgency, curiosity, and impersonation of something familiar to lower a user’s guard. What has changed is the wrapper. A message about a new model release, a policy update from a familiar AI assistant, or a plugin that promises to make the workday easier is today’s version of the fake invoice or the shipping notification. AI-themed lures deserve attention not because they are a passing trend tied to one product cycle, but because AI remains a genuine source of excitement and urgency for employees and consumers alike, and cyberattackers are exploiting the human instinct to explore what is new, useful, or urgent.
Microsoft’s research team recently observed several AI brand campaigns including:
In one case, an initial access broker tracked as Storm-3075 used AI-themed malvertising to distribute payloads for multiple downstream actors, a sign of how quickly this tactic is being commoditized across the criminal ecosystem.
What ties these campaigns together is not sophistication in the traditional sense. It is patience and precision in exploiting a moment. Threat actors are capitalizing on anticipated launches and emerging trends, layering multi-stage redirection chains and disposable infrastructure to slip past both users and defenses. That has real implications for security leaders: it means these incidents cannot be evaluated one surface at a time. A single AI-themed lure can begin as an email, become a malicious link, trigger a suspicious download, and end as an identity or endpoint compromise. Organizations that assess each of those as an isolated event are always a step behind. Organizations that connect them see the full shape of the cyberattack, often early enough to stop it.
In practice, protection starts before the user ever engages with the lure. Microsoft Defender’s anti-phishing policies can help detect spoofing and impersonation attempts, including user and domain impersonation, first-contact messages, mailbox intelligence signals, and other suspicious sender characteristics. For an AI-themed lure, that might look like a fake “Copilot policy update,” a spoofed support notice, or a lookalike domain designed to make a credential collection page feel legitimate.
If the campaign relies on links, Defender’s Safe Links provides URL scanning and detonation during mail flow, plus time-of-click verification when a user selects a link in email, Microsoft Teams, or supported Microsoft 365 apps. That is important when cyberattackers use redirect chains, delayed activation, or links that appear benign at delivery but later resolve to phishing infrastructure, fake sign-in pages, or malicious downloads.
For campaigns that use fake installers, malicious downloads, or weaponized attachments, Safe Attachments adds another layer by detonating attachments in a virtual environment before delivery when policies are configured. For example, if a message promotes a “new AI plugin” but includes a harmful attachment, Safe Attachments can analyze the file for malware, ransomware, or phishing behavior before it reaches the user. If a cyberthreat is identified after delivery, Defender’s post-delivery filtering capabilities help remove malicious content from mailboxes and reduce the window of exposure.
But AI-powered attacks don’t stop at email. Their objective is to gain the highest level of access possible, using compromised accounts as a foothold to move across identities, devices, and data. When a cyberattack moves beyond the inbox, Defender helps connect the evidence. Signals from email and collaboration tools, endpoints, identities, and software as a service (SaaS) apps are correlated into an attack story so analysts can see whether the same lure led to a clicked link, a downloaded payload, risky sign-in behavior, or endpoint activity.
As cyberattackers expand beyond email to gain broader access across the environment, Defender moves from detection to disruption. For multi-stage, multi-domain attacks like business email compromise or AiTM, Defender’s powerful, built-in response capability, attack disruption, will contain the compromised asset during the attack to prevent further lateral movement while security teams investigate and remediate. Attack disruption contains more than 81,000 compromised user accounts monthly and is now disrupting more than 45,000 AiTM attacks each month.
In a recent case study, Defender disrupted a business email compromise attack within four minutes of the initial activity (Figure 4). While response times may vary by scenario, this case shows the impact of attack disruption on a real cyberthreat. The cyberattacker used a convincing document-sharing lure to trick a user to start a legitimate Microsoft device code sign-in flow, which avoided traditional credential theft techniques. Defender recognized the resulting device code authentication and follow-on activity as suspicious, correlated signals across identity and email telemetry, and disrupted the attack within four minutes before the attacker could establish persistence, create inbox rules, or execute payroll fraud.
AI brands are the new bait, but the underlying lesson is bigger than any single campaign. As cyberattackers continue to exploit the momentum around AI, organizations should expect social engineering to become more targeted, more believable, and more difficult to evaluate in isolation.
The answer is not to treat every new lure as a brand-new category of risk. It is to build a protection model that makes trust harder to exploit across the full attack chain. Microsoft Defender helps organizations do that by connecting prevention, detection, investigation, and response across the attack path, so AI-themed lures are harder to deliver, harder to trust, and harder to turn into broader compromise.
To learn more about Microsoft Security solutions, visit our website. Bookmark the Security blog to keep up with our expert coverage on security matters. Also, follow us on LinkedIn (Microsoft Security) and X (@MSFTSecurity) for the latest news and updates on cybersecurity.
1AI brands as bait: How threat actors are using the AI hype in social engineering, Microsoft Threat Intelligence. June 8, 2026.
The post Detect and disrupt AI-themed attacks with Microsoft Defender appeared first on Microsoft Security Blog.
Authorities extradited a 36-year-old Russian national from the Republic of Georgia under accusations of widespread bank-account takeover attacks, including a scheme to defraud two banks of more than $6.3 million, the Justice Department said Tuesday.
Sergei Anatolyevich Filimonov and unnamed co-conspirators ran an extensive operation starting in November 2023 to spoof domains of banks, obtain credentials of legitimate customers and use those details to steal money from accounts with large balances, according to court records.
Filimonov and his co-conspirators allegedly collected more than 5,000 victim login credentials to various banks, including those assigned to employees with access to a company headquartered in Atlanta and another business with offices in Cumming, Ga.
Authorities said Filimonov and his co-conspirators registered and maintained spoofed domains of banks, purchased sponsored links to direct unsuspecting victims to those domains, and stole credentials from those banks’ customers when they attempted to log into the fraudulent sites.
The alleged bank-account takeover crew also created infrastructure to store victim login credentials and tricked victims into providing additional details to bypass security controls.
Prosecutors said Filimonov and his co-conspirators caused and attempted to cause the unauthorized transfer of nearly $5.58 million from one unnamed bank in June 2024 and $735,000 from another bank in November 2024. Both banks have local branches in the Northern District of Georgia and maintain headquarters in North Carolina, according to the indictment.
Officials previously seized the domain, which the co-conspirators allegedly used to store credentials harvested from the spoofed banking sites in December 2025. The FBI at the time said it identified at least 19 victims in the U.S. linked to the domain and put total attempted losses at about $28 million, including confirmed losses of about $14.6 million.
Filimonov is charged with conspiracy to commit bank and wire fraud, access device fraud conspiracy, multiple counts of bank and wire fraud, possession of unauthorized access devices and aggravated identity theft. He faces up to 175 years in prison.
He pleaded not guilty Sept. 4 and remains detained in the Northern District of Georgia.
The post Russian national extradited to US for alleged involvement in bank-account takeover scheme appeared first on CyberScoop.
Grand Theft Auto VI, widely heralded as the game event of the decade, took a significant hit last week after a cybercriminal sent much of the internet into pandemonium after publishing gameplay footage a week before the game’s publisher planned to reveal core portions of the game to the public.
The files posted by the online persona “CyberLeek” indicate either a hacker had direct access to Rockstar Games’ most sensitive systems or was given proprietary data by an insider, eventually becoming one of the highest-profile data extortion attacks of the year — a vexing, almost-daily occurrence hitting industries of all types.
While most data extortion attacks rattle companies due to regulatory or privacy concerns, this particular incident has caused an outsized response from Rockstar’s parent company, Take-Two Interactive Software, because it has an audience. While no lives are at risk, as they would be in an attack on critical infrastructure, the financial and reputational stakes are magnified precisely because people are watching every drip of stolen footage become a news story or a trending topic.
“IP theft — whether it’s conducted by a cybercriminal, an insider, or even potentially [an artificial intelligence] model — rips away the hard work, passion, and livelihood among employees and companies that created the product in the first place,” Cynthia Kaiser, senior vice president of Halycon’s ransomware research center, told CyberScoop.
The game’s prior release, GTA V, along with its online component, has sold over 230 million copies and earned Take-Two over $11 billion since its release in 2013. Industry analysts say GTA VI is on pace to make between $3.3 billion to $5.2 billion in cumulative global sales by the end of its launch week in November.
“The crown jewels of a company are whatever makes it differentiated and special,” said Kaiser, the former deputy assistant director of the FBI’s cyber division. “For some, that means customer data or source. For a studio in the final stretch before launch, the crown jewel is the surprise.”
While Take-Two hasn’t said anything publicly about the leaks, it has responded feverishly via its legal team. The company petitioned a federal court for subpoenas under the Digital Millennium Copyright Act against Discord, Google, Microsoft and X, seeking the identity of CyberLeeks and other user accounts it accuses of copyright infringement.
Federal judges granted the subpoenas against Discord, Microsoft and X, but the petition against Google remained unapproved as of Monday. Take-Two’s legal representatives also sent copyright notices to the four companies, informing them of the copyrighted material published on their platforms, but it’s unclear if any of the tech companies have been formally served with the signed subpoenas.
Take-Two and Rockstar did not respond to a request for comment.
The subpoenas may have been enough to spook those responsible for the leaked footage. As of Monday, the websites where those behind CyberLeek were posting leaked information and links to a memecoin were offline.
Zach Edwards, staff threat researcher at Infoblox and a self-proclaimed fan of the series, initially thought the leaks were part of a Rockstar guerrilla marketing campaign. But the company’s response “confirms that this is a real investigation, and the content being shared is likely real to some degree,” he said.
Take-Two’s actions thus far indicate the company is approaching the breach and leaks like an insider threat investigation, Edwards said. Whoever leaked the footage may have had access to an actual build of the game, he added. That could point to an insider, someone who could have saved a copy to a cloud service, uploaded it to a file-hosting site, or walked out with it on an external drive.
The hacker or group behind CyberLeek claim they are releasing the gameplay videos to protest Rockstar’s decision to not release physical copies of the game. Yet, watermarks on the leaked videos include addresses to crypto wallets, which indicate CyberLeek is also, and perhaps primarily, seeking a payout.
“The persona behind the leaks, CyberLeek, published an anti-corporate manifesto targeting digital pre-orders and disc-less releases to frame the breach as hacktivism,” Ben Bernstein, manager of Huntress’ cybersecurity advisors team, told CyberScoop. “Yet behind the political posturing, there’s clear financial monetization and clout-chasing.”
Kaiser draws the same conclusion. “Let’s separate stated motive from observed behavior,” she said. “Threat actors who talk about principle while running a monetization channel are usually only telling you what they think will land with an audience, not actually what is driving them.”
Katie Moussouris said “this is what the alternative vulnerability economy looks like.” The founder and CEO at Luta Security has spent decades building legitimate channels for people who find security problems to get paid without turning to crime.
“The leaker launched a cryptocurrency token, watermarked stolen footage with a buy link, and offered to sell ad space on future leaks. Each of those pays out in proportion to how many people are watching. The manifesto is what keeps them watching,” Moussouris said.
“That is a genuinely new monetization model for stolen pre-release content, and it means the usual playbook of negotiating a ransom payment quietly or paying to make it stop won’t work,” she added.
Despite its unique characteristics, the rhythm of the attack and its fallout is familiar territory for cybersecurity experts.
“Steal, publish a sample, promise more, deliver, repeat. Just like ransomware attacks, in cases like these criminals use every lever of pressure they can against a company — including the fear of what is coming next — to profit from their actions,” Kaiser said.
“The attackers are crowdsourcing their pressure tactics. A meaningful share of the player base is treating the leaks as free content and amplifying them,” she added.
Kaiser also sees some clear parallels with previous attacks targeting major entertainment companies, including the 2014 attack on Sony Pictures and the HBO hack in 2017.
“The Sony comparison is useful for how these things escalate, but this incident reminds me more of the Iranian hackers’ leak of ‘Game of Thrones’ episodes a few years back,” she said. “North Korea attacked Sony for political purposes, destroying its data along the way; Iranian threat actors compromised HBO, along with hundreds of universities and over forty other companies, in a hacking-for-hire scheme stealing American intellectual property.”
Federal authorities earlier this month unsealed a second wave of indictments against 17 Iranians affiliated with the tech firm Mabna Institute who allegedly stole troves of data from government agencies and dozens of companies, including HBO.
This isn’t the first time Rockstar has been hit with a security incident. In 2022, an 18-year old British man who was a member of the Lapsus$ cybercriminal gang was sentenced to an indefinite hospital order after leaking gameplay footage. According to the BBC, the incident cost Rockstar, along with ridehauling company Uber and chipmaker Nvidia, over $10 million.
Security professionals expect the situation to escalate on all sides. Leaks have hit the internet daily for the past eight days, including a series of leaks Tuesday morning. Meanwhile, Take-Two has not relented on its subpoenas. Its broadest move was a subpoena against Discord, seeking identifying data on CyberLeek, two other users and every member of three Discord servers where the copyrighted material was posted.
Moussouris said the scope of that inquiry should worry people well beyond this case.
“Take-Two asked for Windows device identifiers, login records, and cloud storage contents for every person who spoke in three Discord servers going back to June,” she said. “The people with the best chance of uncovering the culprits are those doing the unglamorous investigation forensics work of figuring out how the build may have leaked.”
Discord would not say whether it had been formally served or what it has done in response. A company spokesperson said it reviews and complies with valid subpoenas when they are received.
While the breach and leak of ‘GTA VI’ material is a serious matter, Edwards noted that Take-Two is also benefiting from greater interest in the unreleased game on a daily basis.
“The threat actor leaking these videos has failed by essentially creating a successful underground marketing campaign for the game while also putting themselves at serious risk of being eventually caught,” he said.
“This incident is playing out like a classic insider threat exploitation scheme. Someone got access to sensitive data, they had a political agenda which clashed with the owner of the sensitive data, and they decided to do something stupid to try and force a change,” Edwards added. “This attack has done nothing but spread ‘GTA VI’ content further than it would have otherwise, and it’s creating ripples across other industries like cybersecurity who would have never covered ‘GTA 6’ issues previously.”
The post The GTA VI leaks are breaking the internet. Security researchers have seen this before. appeared first on CyberScoop.
A notorious cybercrime group has once again exploited a critical zero-day vulnerability on a large scale, claiming it stole data from dozens of organizations, including some of the world’s largest publicly traded companies.
Clop, a prolific but calculated data theft extortion group that’s been active since 2020, began sending threatening emails to its alleged victims in mid-July, according to researchers.
The fallout from the attack spree, which followed a familiar pattern for Clop and its targeted pool of victims, is still evolving as companies hunt for potential signs of compromise.
The vulnerability at the center of Clop’s latest campaign affects a pair of software products from PTC — Windchill and FlexPLM — which manufacturers and retailers, particularly in the manufacturing, aerospace, and automotive industries, use to automate supply chain systems and manage product lifecycles.
“This continues Clop’s trend of targeting SaaS logistics companies’ platforms with zero-days and carrying out mass-exploitation campaigns,” Allan Liska, field chief information security officer at Recorded Future, told CyberScoop.
PTC disclosed the vulnerability — CVE-2026-12569 — on June 17 and issued a patch and initial indicators of compromise the following day.
Yet, that was too late for some of Clop’s known victims who were likely compromised by exploitation of the zero-day in early June, according to Ransom-ISAC.
The Cybersecurity and Infrastructure Security Agency added the defect, which allows unauthenticated attackers to execute code remotely, to its known exploited vulnerabilities catalog June 25.
PTC consistently added new indicators of compromise as they were discovered by researchers. But the company hasn’t said how it first became aware of the vulnerability and ensuing attacks, when the earliest known instance of exploitation occurred or how many customers are known to be compromised.
PTC did not respond to a request for comment.
Clop’s claimed victim set is diverse. The point-of-sale restaurant management platform Toast and software vendor Zebra both told CyberScoop they detected and contained system intrusions, but claimed limited impacts. Other alleged victims, including GE, Philips and Shell, did not respond to requests for comment.
Researchers continue to uncover new details about the tools Clop used once it exploited and gained access to PTC customer systems. ReliaQuest said the group used a custom web shell that gave attackers a direct path to credential theft and large-scale data theft.
The fully equipped extortion platform, which was purpose-built for Windchill, decrypts credentials, delivers malware, and includes tools for sustained access, network traversal and data encryption, ReliaQuest researchers wrote in a report Tuesday.
The toolkit allows attackers to move quickly from initial access to data theft and additional post-exploitation activity without executing manual commands — a framework that mimics Windchill’s standard functions and limits defenders’ ability to detect any malicious activity.
“This campaign is another reminder that Clop remains a sleeping dragon, always looking and preparing to mass exploit vulnerabilities in software that holds sensitive data,” ReliaQuest researchers wrote in the report. “The group commonly goes inactive between campaigns but springs to life with custom-built web shells whenever there is another opportunity for mass extortion.”
The drawn-out impact of Clop’s latest attack spree also mirrors some of its previous campaigns. The threat group has successfully exploited zero-days across multiple technology vendors’ systems, allowing it to steal sensitive data for weeks — sometimes months — from many downstream customers.
Clop targeted dozens of Oracle E-Business Suite customers for more than three months, beginning in the summer of 2025, before it started bombarding victims with extortion emails. The group also achieved mass exploitation as it infiltrated MOVEit environments in 2023, ultimately exposing data from more than 2,300 organizations, making it the largest and most significant cyberattack that year.
The post The long tail of Clop’s PTC hack is just beginning to emerge appeared first on CyberScoop.
A cybercrime group responsible for a string of recent attacks against private equity firms, law firms and financial rating agencies remains active and continued to target new victims as of late last week, according to researchers.
BlackFile, which Google Threat Intelligence Group tracks as UNC6671 and associates more broadly with The Com, has been active since the start of the year, shifting its focus from one sector to the next.
“We have seen continued targeting against the financial sector with additional targeting of other organizations including in the med tech space,” Austin Larsen, principal threat analyst at GTIG, told CyberScoop.
The extortion group impersonates IT support in voice-phishing and social engineering attacks, and recently split its extortion operations across four brands with shared infrastructure: Redact, Pink, Helix and Falcon.
Several organizations received new extortion demands from Redact in the last week, according to Google.
BlackFile and its various affiliates have impacted organizations in multiple industries, including healthcare, technology, transportation, logistics, wholesale, retail and hospitality.
“BlackFile does go after some of the largest organizations in the sectors that they go for. They’re not going after small companies,” Larsen said. “This is big-game hunting.”
The group’s extortion demands often start around $3 million and payments, including several in the past few weeks, have typically been negotiated down to less than $1 million, according to Google.
Flashpoint researchers told CyberScoop they have observed malicious infrastructure targeting Blackstone, Bain Capital, Moody’s, CME and Apollo, but it’s unclear if any of those firms were compromised.
BlackFile’s steady pace of activity underscores the persistent threat it poses, as it targets an average of 1.5 new victims daily, researchers said.
Some of the group’s recent victims have been subject to threatening messages and other forms of escalation, including swatting incidents, a tactic adopted by several subsets of The Com, according to Google.
The attackers use hundreds of callers, often lower-level people that are recruited for a small fee or an opportunity to earn goodwill with the group, who make the voice phishing calls to obtain initial access. Larsen estimates less than a dozen core operators run the different brands under the BlackFile umbrella.
“From the intrusion data that we’re seeing, this does appear to be essentially the same group,” he said, adding that different people may be operating the various brands, but they’re all linked back to the same threat cluster using shared infrastructure.
Mandiant incident responders encounter BlackFile often, having been engaged by more than two dozen organizations successfully compromised by the threat group since January. New victims in the financial sector were calling Mandiant in for help earlier this month.
Voice-based phishing attacks for data theft extortion aren’t sophisticated or novel, but BlackFile and other cybercrime groups consistently prove their continued effectiveness across virtually any sector or organization. “They’re really hitting on the human weakness element here,” Larsen said.
The post Details emerge on BlackFile’s recent attacks on financial companies appeared first on CyberScoop.
Microsoft Threat Intelligence tracks DeadLock ransomware as an emerging financially motivated operation distinguished by its use of decentralized infrastructure to support victim communications and data leak operations. Its recovery ecosystem combines the Session messaging network with blockchain-backed services that store and deliver resources used throughout the extortion process. This architecture likely increases the resilience of portions of its communication, leak-hosting, and negotiation infrastructure, allowing DeadLock operators to recover from some disruption efforts while maintaining continuity for victims. Microsoft has observed DeadLock ransomware being deployed by multiple groups including an affiliate of the Lynx and INC ransomware ecosystems.
First observed in July 2025, DeadLock operators employ double extortion tactics, encrypting victim environments while threatening to publicly release exfiltrated data. As of July 2026, the operators have published more than 80 compromised organizations on their data leak site, called the DeadLock blog, with more than half of the claimed victims in Europe. Microsoft identified DeadLock ransomware impacting organizations across information technology (IT), mining, transportation and logistics, manufacturing, hospitality, consumer goods, and other sectors in Europe, Asia, North America, South America, and Africa.
The DeadLock encryptor includes a resource-aware throttling mechanism designed to maintain system responsiveness during encryption. In addition to its encryption capabilities, the ransomware also appears to implement language or country-based geofencing designed to avoid running in environments associated with former Soviet and Commonwealth of Independent States (CIS)-linked countries as well as select Middle Eastern countries, a pattern commonly observed among ransomware operators believed to operate from those regions. Together, these capabilities demonstrate how DeadLock combines established ransomware tradecraft with decentralized infrastructure designed to improve operational resilience.
In this blog, we present a technical analysis of the DeadLock ransomware encryptor, covering its execution flow, defense evasion techniques, encryption design, and post-encryption behaviors, including a decentralized recovery chat system. We also provide indicators of compromise (IOCs), Microsoft Defender detections, and mitigation guidance to help organizations defend against this threat and similar ransomware activity.
Before performing any malicious activity, the DeadLock encryptor decrypts an embedded configuration blob using XOR decoding with an 8-byte key.
Below are the malware’s configuration fields and their values.
| Field | Value |
| Victim UID | <redacted> |
| Malware public key | 03bf50bbf97c4e951e66ff12b689a37a3ce675b4921e254eae76da77573843e4a9 |
| Encryption rule | 1000,05052429880,025124288000,010524288000,F991114288000 |
| Language exclude list | Geofencing language IDs (see Language geofencing) |
| Process stop list | Processes to terminate (see Process and service termination) |
| Service stop list | Services to stop and delete (see Process and service termination) |
| File exclude list | Extensions and file names to avoid encrypting (see Directory traversal) |
| Directory exclude list | Pre-traversal filter with directories to avoid encrypting (see Directory traversal) |
| Sub-path Exclude List | Sub-paths to avoid encrypting during traversal (see Directory traversal) |
| Text ransom note | Full text ransom note content (see Ransom notes deployment) |
| HTML recovery chat | Full HTML/JS interactive chat page (see Recovery chat: Technical architecture) |
As an early exit check, the malware queries the system’s default and user interface (UI) languages. If either language matches the exclude list in the configuration, the malware self-deletes immediately without performing any encryption.
The following languages trigger this exit behavior:
| LANGID | Language | Country |
| 1049 | Russian | Russia |
| 1058 | Ukrainian | Ukraine |
| 1059 | Belarusian | Belarus |
| 1064 | Tajik (Cyrillic) | Tajikistan |
| 1065 | Persian | Iran |
| 1067 | Armenian | Armenia |
| 1068 | Azeri (Latin) | Azerbaijan |
| 1079 | Georgian | Georgia |
| 1087 | Kazakh | Kazakhstan |
| 1088 | Kyrgyz | Kyrgyzstan |
| 1090 | Turkmen | Turkmenistan |
| 1114 | Syriac | Syria |
| 2072 | Romanian (Moldova) | Moldova |
| 2092 | Azeri (Cyrillic) | Azerbaijan |
| 2115 | Uzbek (Cyrillic) | Uzbekistan |
| 8193 | Arabic | Oman |
| 9217 | Arabic (Yemen) | Yemen |
The encryptor’s behavior branches based on command-line arguments and the current privilege level. If a target directory path is provided as the command-line argument, the malware skips all preparation steps and jumps directly to encryption. This feature allows the operator to invoke the encryptor with specific targets for focused encryption. If no sub-commands are provided and the process is already elevated, the malware proceeds normally through all execution phases.
The more interesting case occurs when no command-line argument is provided while the process is not elevated. In this scenario, the malware attempts to gain administrator privileges through a batch-script-based elevation technique. It generates a randomly named .cmd file (8 uppercase characters, such as ESYEKQSY.cmd) and executes it using ShellExecuteW with the RunAs verb, which triggers the Windows User Account Control (UAC) consent dialog. If the user denies the prompt, the malware retries up to 10 times before giving up and exiting.
During dynamic analysis, the sample did not successfully relaunch itself with elevated privileges. As a result, full pre-encryption preparation appears to require execution from an already elevated context. When invoked with a target path, the malware bypasses preparation and proceeds directly to encrypt accessible files. This behavior is specific to the analyzed sample and may change in later variants.
When running with administrator privileges, the malware further expands its access by enabling SeDebugPrivilege, SeRestorePrivilege, SeBackupPrivilege, SeTakeOwnershipPrivilege, SeAuditPrivilege, and SeSecurityPrivilege. These privileges increase the malware’s ability to interact with system processes, protected files, and security-related settings, helping it overcome common access restrictions and maximize the scope of files and resources it can target during the encryption phase.
The malware silently empties the recycle bin on all drives without any UI or confirmation dialog, eliminating a potential source of file recovery for victims.
To visually brand encrypted files, the malware writes an embedded .ico file to C:\ProgramData\<UID>.ico and registers it as the default icon for files with the extension .dlock.
To associate the custom icon with encrypted files, the ransomware creates the HKLM\SOFTWARE\Classes\.dlock\DefaultIcon registry key and sets its (Default) value to the path of the dropped icon file.
Below is the malware’s embedded .ico file.
Before starting encryption, the malware terminates processes and disables services that could interfere with file access or provide defensive capabilities. This approach ensures that locked files become accessible for encryption while simultaneously disrupting the environment’s ability to detect, respond to, or recover from the attack.
For services, the malware enumerates all active Win32 services and compares them against the stop list in the configuration. For each matching service, DeadLock sets its start type to DISABLED and sends a stop command to terminate that service. Notable targets include windefend (Windows Defender), vss/swprv/wbengine (Volume Shadow Copy and Backup services), mssearch, Hyper-V services (vmcompute, vmms), and Active Directory services (adws, ntds, kdc). Below is the full service stop list in the malware configuration:
For processes, the malware enumerates all running processes and terminates any matching its stop list while skipping its own process ID. Targeted processes include security tools (msmpeng, securityhealthservice, smartscreen), backup and cloud sync applications (onedrive, dropbox, googledrivefs, owncloud), remote access tools (anydesk, putty, mstsc, rustdesk), shell and system processes (explorer, powershell, taskmgr, cmd), and search/indexing services. Below is the full process stop list in the malware configuration:
To eliminate forensic evidence, the malware employs three complementary methods that collectively ensure every event log channel on the system is cleared of existing entries, disabled from recording future events, and has its access permissions locked down:
By combining API-based clearing, registry manipulation, and full channel enumeration, the malware covers multiple log sources, including third-party application logs and custom diagnostic channels, to minimize existing forensic evidence on the infected device.
To maintain system stability and ensure the victim can access ransom instructions, the malware excludes specific directories, file extensions, and file names from encryption. This selective encryption model is a common ransomware design pattern where the system must remain operational enough for the victim to receive instructions and facilitate payment.
Extensions and file names from the configuration’s file exclude list are skipped during encryption:
For directory processing, the malware uses a two-tier directory exclusion system applied at different stages of the encryption pipeline. Tier 1 provides rough filtering that saves significant time by avoiding traversal overhead, while tier 2 provides granular path-specific exclusions within directories that are traversed. Both prevent encryption, but they operate at different stages of the traversal pipeline.
In its pre-traversal phase (tier 1), the malware checked at the drive batch level before threads are spawned for traversal. If a top-level directory matches against the configured directory exclude list (\users\*\appdata, program files (x86)\, program files\, and programdata\), the entire tree is skipped without being walked.
In its during-traversal phase (tier 2), the malware checked the file name during recursive directory enumeration and applied to both subdirectories and files as they are encountered. In this tier, the directory and file names are checked against the configured sub-path exclude list below.
One of the more distinctive aspects of the DeadLock encryptor is its resource-aware throttling mechanism, designed to keep the infected system responsive during encryption. The malware spawns a dedicated monitoring/dispatch thread per drive batch that acts as a gatekeeper for file encryption dispatch. Before dispatching each new file to be encrypted, this thread polls system resource utilization and checks against hardcoded thresholds:
With this mechanism, worker threads already encrypting files are not interrupted, and only the dispatch of new files is gated. This means partially encrypted files are expected to complete, and the throttling manifests as reduced parallelism rather than stop/start behavior. This approach can prevent system hangs that would alert the user and reduce the likelihood of behavioral detection by maintaining normal-looking resource consumption patterns.
For the encryption work itself, the malware spawns directory processing threads, with the thread count being 2 times the CPU core number. Each thread recursively traverses directories, dropping ransom notes and dispatching files for encryption. Individual file encryption threads are tasked with handling the actual cryptographic operations.
The DeadLock ransomware implements a hybrid cryptographic design that combines Curve25519 elliptic-curve cryptography with the XChaCha20 stream cipher for file encryption. Key encapsulation uses the Networking and Cryptography Library (NaCl) crypto_box construction, which pairs an asymmetric key exchange with authenticated encryption to securely wrap each file’s symmetric key.
| Layer | Algorithm | Purpose |
| File content encryption | XChaCha20 | Symmetric stream cipher |
| Key encapsulation | Curve25519 Elliptic Curve Diffie-Hellman (ECDH) + XSalsa20-Poly1305 | Asymmetric key wrapping (NaCl crypto_box) |
| Random generation | Windows CryptoAPI | All key material random generation |
The configuration’s operator public key 03bf50bbf97c4e951e66ff12b689a37a3ce675b4921e254eae76da77573843e4a9 is 33 bytes. The leading 03 byte is a SEC1 compressed point format prefix borrowed from Bitcoin/secp256k1. The malware validates this prefix byte against a lookup table that accepts 00, 02, 03, 04, and 05, mapping each to an expected key length.
After format validation, only the remaining 32 bytes are used in the actual Curve25519 ECDH scalar multiplication. This SEC1 prefix is non-standard for Curve25519, which natively uses bare 32-byte keys, and the malware author has likely adopted it for format versioning across their builder and decryptor tooling.
For each target file, the malware performs the following sequence of operations:
The use of a zero crypto_box nonce is worth noting. This is cryptographically safe because each file generates a unique ephemeral Curve25519 keypair, which produces a unique ECDH shared secret per file. With this, a constant zero nonce never repeats with the same key.
The entire design ensures that each file is encrypted with a distinct key derived from a per-file ephemeral key exchange, eliminating any possibility of key reuse across files. Overall, the cryptographic construction is sound and does not present a practical path to decryption without the attacker’s private key.
To balance encryption thoroughness with speed, the malware implements a tiered encryption policy based on file size. The encryption rule in the configuration 1000,05052429880,025124288000,010524288000,F991114288000 encodes this policy. Each comma-separated entry is parsed by splitting at position 3: the first 3 characters represent the encryption percentage (decimal), and the remaining characters represent the file size threshold (decimal bytes). The special prefix F replaces the percentage field with a chunked-full mode.
| Rule | Encryption percent | File size threshold | Behavior |
| 1000 | 100% | ≥ 0 bytes | Default: encrypt entire file |
| 05052429880 | 50% | ≥ ~50 MB | Encrypt 50% of file in distributed chunks |
| 025124288000 | 25% | ≥ ~118 MB | Encrypt 25% in distributed chunks |
| 010524288000 | 10% | ≥ ~500 MB | Encrypt 10% in distributed chunks |
| F991114288000 | Chunked | ≥ ~1 GB | Special full-chunk mode with calculated intervals |
Rules are evaluated in order, and the last matching rule wins. For example, when the malware processes a 2 GB file, all rules match, but the final F99… entry will determine the encryption behavior.
For partial encryption, the malware calculates:
This creates an intermittent encryption pattern where 512-byte blocks are encrypted at regular intervals throughout the file. The result is a file that is rendered unusable while requiring only a fraction of the time needed for full encryption. This is a crucial optimization for the ransomware when targeting large files such as databases, virtual machine images, and backups.
After encryption, the malware appends a structured metadata blob to the end of each file. This footer contains all the information the decryptor needs to reverse the encryption, along with markers for format validation:
The footer serves several important functions:
Key and nonce reconstruction: The cleartext ephemeral Curve25519 public key (33 bytes) at the end of the footer allows the decryptor to recompute the ECDH shared secret and open the crypto_box to recover the XChaCha20 key and nonce used for file content encryption.
Inner dDlK magic (decryption validation): After the decryptor opens the crypto_box, it checks for the dDlK marker at the expected offset (32 + 24 + padding_length bytes into the plaintext) to confirm the correct private key was used and that decryption succeeded. While the Poly1305 Message Authentication Code (MAC) already provides cryptographic integrity verification, this marker offers a fast format-level sanity check.
FA flag (decryption mode indicator): This flag is used by the decryptor to determine which read strategy to use when reversing the encryption. It is present when the file was encrypted using sequential/contiguous block encryption, and absent when intermittent/skip encryption was used. Specifically, FA is appended in two cases:
Without this flag, the 8-byte chunk parameters in the footer would be ambiguous as they could represent either a block count or a skip interval. The FA flag resolves this ambiguity and enables the decryptor to correctly reconstruct the original file.
File identifier/format tag: The 12-byte random value in the cleartext footer serves as a file identifier (with the first byte used to derive the padding length inside the encrypted payload).
As an immediate visual indicator of compromise, the malware generates a custom BMP wallpaper file at runtime using the victim’s screen resolution. Below is an example of the generated BMP wallpaper:
The wallpaper is written to C:\ProgramData\<UID>.bmp (on Vista and later) or C:\Documents and Settings\All Users\Application Data\<UID>.bmp (on XP), set as the desktop background, and persisted in the registry at HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\Wallpaper.
After encrypting files, the malware deploys two types of ransom notes, each with distinct deployment logic and purpose:
Text note (HOW_RECOVER.<UID>.txt): The text note is dropped into every encrypted directory, but with a notable timing behavior: it is only deployed during the second pass of the directory processing loop. The malware iterates over drive batches multiple times, and the text note drop is gated by an iteration counter. On the first pass, the text note is suppressed, likely to prioritize encryption speed before littering the file system with ransom note files. For defenders and analysts, this has a practical implication: if testing with a minimal drive configuration that only triggers a single iteration, the text note will never appear.
Below is the text note content from the malware’s configuration.
HTML note (RECOVERY_CHAT.<UID>.html): This file is dropped to all drive root directories and all Desktop folders. Unlike the text note, the HTML note is a full interactive web application with a self-contained single-page application that implements end-to-end encrypted chat, a paginated data leak blog, and a file browser, all without requiring a traditional backend server. The technical architecture of this recovery chat system is detailed in Recovery chat: Technical architecture.
The most distinctive feature of the DeadLock ransomware is its recovery chat system. The RECOVERY_CHAT.<UID>.html file is a self-contained HTML application that implements a full end-to-end encrypted chat system, a paginated data leak blog, and a file browser, all without requiring a traditional backend server.
The architecture is designed with three decentralized components.
Rather than relying on traditional domain-based infrastructure that can be seized or taken offline, the DeadLock operators store configuration data on the Polygon blockchain. Two smart contracts serve as censorship-resistant infrastructure:
| Contract | Address | Function selector | Purpose |
| Chat proxy | 0x8EF7c3e531d871D3B9D559722DE77EB1dEc19dAe | 0x933a9ce8 | Stores the proxy server URL |
| Blog | 0x757984507c82c8dA1d3969c535dB5706eEE6426C | 0xd4070542 | Stores actor’s blog posts |
The HTML page issues eth_call requests to public Polygon Remote Procedure Call (RPC) endpoints (no wallet required with read-only calls) to obtain the proxy server address. The blog contract takes offset and limit parameters (for pagination) and returns structured data including post titles, bodies, timestamps, image URLs, and file attachment links.
On-chain storage provides several strategic advantages for the threat actor: the proxy URL can be updated by modifying the smart contract without changing any victim-facing infrastructure, and no domain registration or DNS infrastructure is required. This represents a notable evolution in ransomware infrastructure design.
The HTML recovery chat cycles through six public RPC endpoints for redundancy: polygon-bor-rpc.publicnode[.]com, polygon.drpc[.]org, polygon-pokt.nodies[.]app, polygon-rpc[.]com, 1rpc[.]io/matic, and polygon.meowrpc[.]com.
For victim-operator communication, chat messages are routed through the Session decentralized messenger network, which is an onion-routed, swarm-based messaging protocol that provides anonymity for both parties. The proxy server (whose URL is retrieved from the blockchain) acts as a relay between the victim’s browser and Session swarm nodes.
Key generation: DeadLock’s design choice is that the victim’s Session identity is derived deterministically from their sign-in credentials. When the victim enters their credentials on the HTML page, the following derivation occurs:
This deterministic derivation means the same credentials always produce the same keypair, and no account registration is needed as the victim’s Session identity exists only when they enter the correct credentials. If the victim forgets their credentials, the identity is unrecoverable (as stated by the actor in the chat UI). The 05 prefix is Session’s standard network identifier for user accounts.
Sending a message: The following sequence occurs when a message is sent:
Receiving a message: The following sequence occurs when a message is received:
The recovery chat page also provides access to a data leak blog whose content is stored on the Polygon blockchain.
Blog posts retrieved from the smart contract support BBCode formatting, image galleries, and file attachments using either direct URLs or Wasabi protocol links that open an in-browser file explorer. The HTML application contains a full Amazon Web Services (AWS) S3-compatible file browser that parses the Wasabi credentials from the URI, generates AWS4-HMAC-SHA256 signed requests, lists bucket contents with folder navigation, and generates pre-signed download URLs for individual files. This allows the attacker to host stolen data on Wasabi and provide victims or the public with browsable access to the leaked files without running a web server.
The architecture is significantly more resilient to takedown and censorship efforts, but it is not independent of off-chain infrastructure:
This infrastructure model represents a meaningful evolution from traditional ransomware communication channels and poses new challenges for takedown efforts.
As a final cleanup step after encryption completes, the malware creates a batch to delete its own binary from disk. The cleanup batch loops until it successfully deletes the malware binary, then removes itself:
Microsoft recommends the following mitigations to reduce the impact of this threat.
You can assess how an attack surface reduction rule might impact your network by opening the security recommendation for that rule in Vulnerability management. In the Recommendation details pane, check the user impact to determine what percentage of your devices can accept a new policy enabling the rule in blocking mode without adverse impact to user productivity.
Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.
Microsoft Defender Antivirus detects threat components as the following malware:
The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.
The following alerts might indicate threat activity associated with DeadLock ransomware if Defender for Endpoint is set to block mode.
The following alert might indicate threat activity associated with this threat. This alert, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.
Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.
Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:
Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.
Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.
Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.
| Indicator | Type | Description |
| a1fdf65020ce4a0f0940c793c6425baf8a0b994ec48b9baaf72788661a9d29f4 | SHA-256 | DeadLock ransomware encryptor |
| deadlock.liveblog365[.]com | URL | Leak site domain |
| dlock.liveblog365[.]com | URL | Leak site domain |
| deadblogdbdu5wprek7wa2o4ce7rnt6u6ntqeud3hzjjcveosgpsqqqd[.]onion | URL | Leak site domain |
| deadlockblog.great-site[.]net | URL | Leak site domain |
| deadlockblog.medianewsonline[.]com | URL | Leak site domain |
For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.
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The post DeadLock ransomware: Breaking down a Rust-based encryptor with decentralized recovery infrastructure appeared first on Microsoft Security Blog.
Microsoft Threat Intelligence tracks DeadLock ransomware as an emerging financially motivated operation distinguished by its use of decentralized infrastructure to support victim communications and data leak operations. Its recovery ecosystem combines the Session messaging network with blockchain-backed services that store and deliver resources used throughout the extortion process. This architecture likely increases the resilience of portions of its communication, leak-hosting, and negotiation infrastructure, allowing DeadLock operators to recover from some disruption efforts while maintaining continuity for victims. Microsoft has observed DeadLock ransomware being deployed by multiple groups including an affiliate of the Lynx and INC ransomware ecosystems.
First observed in July 2025, DeadLock operators employ double extortion tactics, encrypting victim environments while threatening to publicly release exfiltrated data. As of July 2026, the operators have published more than 80 compromised organizations on their data leak site, called the DeadLock blog, with more than half of the claimed victims in Europe. Microsoft identified DeadLock ransomware impacting organizations across information technology (IT), mining, transportation and logistics, manufacturing, hospitality, consumer goods, and other sectors in Europe, Asia, North America, South America, and Africa.
The DeadLock encryptor includes a resource-aware throttling mechanism designed to maintain system responsiveness during encryption. In addition to its encryption capabilities, the ransomware also appears to implement language or country-based geofencing designed to avoid running in environments associated with former Soviet and Commonwealth of Independent States (CIS)-linked countries as well as select Middle Eastern countries, a pattern commonly observed among ransomware operators believed to operate from those regions. Together, these capabilities demonstrate how DeadLock combines established ransomware tradecraft with decentralized infrastructure designed to improve operational resilience.
In this blog, we present a technical analysis of the DeadLock ransomware encryptor, covering its execution flow, defense evasion techniques, encryption design, and post-encryption behaviors, including a decentralized recovery chat system. We also provide indicators of compromise (IOCs), Microsoft Defender detections, and mitigation guidance to help organizations defend against this threat and similar ransomware activity.
Before performing any malicious activity, the DeadLock encryptor decrypts an embedded configuration blob using XOR decoding with an 8-byte key.
Below are the malware’s configuration fields and their values.
| Field | Value |
| Victim UID | <redacted> |
| Malware public key | 03bf50bbf97c4e951e66ff12b689a37a3ce675b4921e254eae76da77573843e4a9 |
| Encryption rule | 1000,05052429880,025124288000,010524288000,F991114288000 |
| Language exclude list | Geofencing language IDs (see Language geofencing) |
| Process stop list | Processes to terminate (see Process and service termination) |
| Service stop list | Services to stop and delete (see Process and service termination) |
| File exclude list | Extensions and file names to avoid encrypting (see Directory traversal) |
| Directory exclude list | Pre-traversal filter with directories to avoid encrypting (see Directory traversal) |
| Sub-path Exclude List | Sub-paths to avoid encrypting during traversal (see Directory traversal) |
| Text ransom note | Full text ransom note content (see Ransom notes deployment) |
| HTML recovery chat | Full HTML/JS interactive chat page (see Recovery chat: Technical architecture) |
As an early exit check, the malware queries the system’s default and user interface (UI) languages. If either language matches the exclude list in the configuration, the malware self-deletes immediately without performing any encryption.
The following languages trigger this exit behavior:
| LANGID | Language | Country |
| 1049 | Russian | Russia |
| 1058 | Ukrainian | Ukraine |
| 1059 | Belarusian | Belarus |
| 1064 | Tajik (Cyrillic) | Tajikistan |
| 1065 | Persian | Iran |
| 1067 | Armenian | Armenia |
| 1068 | Azeri (Latin) | Azerbaijan |
| 1079 | Georgian | Georgia |
| 1087 | Kazakh | Kazakhstan |
| 1088 | Kyrgyz | Kyrgyzstan |
| 1090 | Turkmen | Turkmenistan |
| 1114 | Syriac | Syria |
| 2072 | Romanian (Moldova) | Moldova |
| 2092 | Azeri (Cyrillic) | Azerbaijan |
| 2115 | Uzbek (Cyrillic) | Uzbekistan |
| 8193 | Arabic | Oman |
| 9217 | Arabic (Yemen) | Yemen |
The encryptor’s behavior branches based on command-line arguments and the current privilege level. If a target directory path is provided as the command-line argument, the malware skips all preparation steps and jumps directly to encryption. This feature allows the operator to invoke the encryptor with specific targets for focused encryption. If no sub-commands are provided and the process is already elevated, the malware proceeds normally through all execution phases.
The more interesting case occurs when no command-line argument is provided while the process is not elevated. In this scenario, the malware attempts to gain administrator privileges through a batch-script-based elevation technique. It generates a randomly named .cmd file (8 uppercase characters, such as ESYEKQSY.cmd) and executes it using ShellExecuteW with the RunAs verb, which triggers the Windows User Account Control (UAC) consent dialog. If the user denies the prompt, the malware retries up to 10 times before giving up and exiting.
During dynamic analysis, the sample did not successfully relaunch itself with elevated privileges. As a result, full pre-encryption preparation appears to require execution from an already elevated context. When invoked with a target path, the malware bypasses preparation and proceeds directly to encrypt accessible files. This behavior is specific to the analyzed sample and may change in later variants.
When running with administrator privileges, the malware further expands its access by enabling SeDebugPrivilege, SeRestorePrivilege, SeBackupPrivilege, SeTakeOwnershipPrivilege, SeAuditPrivilege, and SeSecurityPrivilege. These privileges increase the malware’s ability to interact with system processes, protected files, and security-related settings, helping it overcome common access restrictions and maximize the scope of files and resources it can target during the encryption phase.
The malware silently empties the recycle bin on all drives without any UI or confirmation dialog, eliminating a potential source of file recovery for victims.
To visually brand encrypted files, the malware writes an embedded .ico file to C:\ProgramData\<UID>.ico and registers it as the default icon for files with the extension .dlock.
To associate the custom icon with encrypted files, the ransomware creates the HKLM\SOFTWARE\Classes\.dlock\DefaultIcon registry key and sets its (Default) value to the path of the dropped icon file.
Below is the malware’s embedded .ico file.
Before starting encryption, the malware terminates processes and disables services that could interfere with file access or provide defensive capabilities. This approach ensures that locked files become accessible for encryption while simultaneously disrupting the environment’s ability to detect, respond to, or recover from the attack.
For services, the malware enumerates all active Win32 services and compares them against the stop list in the configuration. For each matching service, DeadLock sets its start type to DISABLED and sends a stop command to terminate that service. Notable targets include windefend (Windows Defender), vss/swprv/wbengine (Volume Shadow Copy and Backup services), mssearch, Hyper-V services (vmcompute, vmms), and Active Directory services (adws, ntds, kdc). Below is the full service stop list in the malware configuration:
For processes, the malware enumerates all running processes and terminates any matching its stop list while skipping its own process ID. Targeted processes include security tools (msmpeng, securityhealthservice, smartscreen), backup and cloud sync applications (onedrive, dropbox, googledrivefs, owncloud), remote access tools (anydesk, putty, mstsc, rustdesk), shell and system processes (explorer, powershell, taskmgr, cmd), and search/indexing services. Below is the full process stop list in the malware configuration:
To eliminate forensic evidence, the malware employs three complementary methods that collectively ensure every event log channel on the system is cleared of existing entries, disabled from recording future events, and has its access permissions locked down:
By combining API-based clearing, registry manipulation, and full channel enumeration, the malware covers multiple log sources, including third-party application logs and custom diagnostic channels, to minimize existing forensic evidence on the infected device.
To maintain system stability and ensure the victim can access ransom instructions, the malware excludes specific directories, file extensions, and file names from encryption. This selective encryption model is a common ransomware design pattern where the system must remain operational enough for the victim to receive instructions and facilitate payment.
Extensions and file names from the configuration’s file exclude list are skipped during encryption:
For directory processing, the malware uses a two-tier directory exclusion system applied at different stages of the encryption pipeline. Tier 1 provides rough filtering that saves significant time by avoiding traversal overhead, while tier 2 provides granular path-specific exclusions within directories that are traversed. Both prevent encryption, but they operate at different stages of the traversal pipeline.
In its pre-traversal phase (tier 1), the malware checked at the drive batch level before threads are spawned for traversal. If a top-level directory matches against the configured directory exclude list (\users\*\appdata, program files (x86)\, program files\, and programdata\), the entire tree is skipped without being walked.
In its during-traversal phase (tier 2), the malware checked the file name during recursive directory enumeration and applied to both subdirectories and files as they are encountered. In this tier, the directory and file names are checked against the configured sub-path exclude list below.
One of the more distinctive aspects of the DeadLock encryptor is its resource-aware throttling mechanism, designed to keep the infected system responsive during encryption. The malware spawns a dedicated monitoring/dispatch thread per drive batch that acts as a gatekeeper for file encryption dispatch. Before dispatching each new file to be encrypted, this thread polls system resource utilization and checks against hardcoded thresholds:
With this mechanism, worker threads already encrypting files are not interrupted, and only the dispatch of new files is gated. This means partially encrypted files are expected to complete, and the throttling manifests as reduced parallelism rather than stop/start behavior. This approach can prevent system hangs that would alert the user and reduce the likelihood of behavioral detection by maintaining normal-looking resource consumption patterns.
For the encryption work itself, the malware spawns directory processing threads, with the thread count being 2 times the CPU core number. Each thread recursively traverses directories, dropping ransom notes and dispatching files for encryption. Individual file encryption threads are tasked with handling the actual cryptographic operations.
The DeadLock ransomware implements a hybrid cryptographic design that combines Curve25519 elliptic-curve cryptography with the XChaCha20 stream cipher for file encryption. Key encapsulation uses the Networking and Cryptography Library (NaCl) crypto_box construction, which pairs an asymmetric key exchange with authenticated encryption to securely wrap each file’s symmetric key.
| Layer | Algorithm | Purpose |
| File content encryption | XChaCha20 | Symmetric stream cipher |
| Key encapsulation | Curve25519 Elliptic Curve Diffie-Hellman (ECDH) + XSalsa20-Poly1305 | Asymmetric key wrapping (NaCl crypto_box) |
| Random generation | Windows CryptoAPI | All key material random generation |
The configuration’s operator public key 03bf50bbf97c4e951e66ff12b689a37a3ce675b4921e254eae76da77573843e4a9 is 33 bytes. The leading 03 byte is a SEC1 compressed point format prefix borrowed from Bitcoin/secp256k1. The malware validates this prefix byte against a lookup table that accepts 00, 02, 03, 04, and 05, mapping each to an expected key length.
After format validation, only the remaining 32 bytes are used in the actual Curve25519 ECDH scalar multiplication. This SEC1 prefix is non-standard for Curve25519, which natively uses bare 32-byte keys, and the malware author has likely adopted it for format versioning across their builder and decryptor tooling.
For each target file, the malware performs the following sequence of operations:
The use of a zero crypto_box nonce is worth noting. This is cryptographically safe because each file generates a unique ephemeral Curve25519 keypair, which produces a unique ECDH shared secret per file. With this, a constant zero nonce never repeats with the same key.
The entire design ensures that each file is encrypted with a distinct key derived from a per-file ephemeral key exchange, eliminating any possibility of key reuse across files. Overall, the cryptographic construction is sound and does not present a practical path to decryption without the attacker’s private key.
To balance encryption thoroughness with speed, the malware implements a tiered encryption policy based on file size. The encryption rule in the configuration 1000,05052429880,025124288000,010524288000,F991114288000 encodes this policy. Each comma-separated entry is parsed by splitting at position 3: the first 3 characters represent the encryption percentage (decimal), and the remaining characters represent the file size threshold (decimal bytes). The special prefix F replaces the percentage field with a chunked-full mode.
| Rule | Encryption percent | File size threshold | Behavior |
| 1000 | 100% | ≥ 0 bytes | Default: encrypt entire file |
| 05052429880 | 50% | ≥ ~50 MB | Encrypt 50% of file in distributed chunks |
| 025124288000 | 25% | ≥ ~118 MB | Encrypt 25% in distributed chunks |
| 010524288000 | 10% | ≥ ~500 MB | Encrypt 10% in distributed chunks |
| F991114288000 | Chunked | ≥ ~1 GB | Special full-chunk mode with calculated intervals |
Rules are evaluated in order, and the last matching rule wins. For example, when the malware processes a 2 GB file, all rules match, but the final F99… entry will determine the encryption behavior.
For partial encryption, the malware calculates:
This creates an intermittent encryption pattern where 512-byte blocks are encrypted at regular intervals throughout the file. The result is a file that is rendered unusable while requiring only a fraction of the time needed for full encryption. This is a crucial optimization for the ransomware when targeting large files such as databases, virtual machine images, and backups.
After encryption, the malware appends a structured metadata blob to the end of each file. This footer contains all the information the decryptor needs to reverse the encryption, along with markers for format validation:
The footer serves several important functions:
Key and nonce reconstruction: The cleartext ephemeral Curve25519 public key (33 bytes) at the end of the footer allows the decryptor to recompute the ECDH shared secret and open the crypto_box to recover the XChaCha20 key and nonce used for file content encryption.
Inner dDlK magic (decryption validation): After the decryptor opens the crypto_box, it checks for the dDlK marker at the expected offset (32 + 24 + padding_length bytes into the plaintext) to confirm the correct private key was used and that decryption succeeded. While the Poly1305 Message Authentication Code (MAC) already provides cryptographic integrity verification, this marker offers a fast format-level sanity check.
FA flag (decryption mode indicator): This flag is used by the decryptor to determine which read strategy to use when reversing the encryption. It is present when the file was encrypted using sequential/contiguous block encryption, and absent when intermittent/skip encryption was used. Specifically, FA is appended in two cases:
Without this flag, the 8-byte chunk parameters in the footer would be ambiguous as they could represent either a block count or a skip interval. The FA flag resolves this ambiguity and enables the decryptor to correctly reconstruct the original file.
File identifier/format tag: The 12-byte random value in the cleartext footer serves as a file identifier (with the first byte used to derive the padding length inside the encrypted payload).
As an immediate visual indicator of compromise, the malware generates a custom BMP wallpaper file at runtime using the victim’s screen resolution. Below is an example of the generated BMP wallpaper:
The wallpaper is written to C:\ProgramData\<UID>.bmp (on Vista and later) or C:\Documents and Settings\All Users\Application Data\<UID>.bmp (on XP), set as the desktop background, and persisted in the registry at HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\Wallpaper.
After encrypting files, the malware deploys two types of ransom notes, each with distinct deployment logic and purpose:
Text note (HOW_RECOVER.<UID>.txt): The text note is dropped into every encrypted directory, but with a notable timing behavior: it is only deployed during the second pass of the directory processing loop. The malware iterates over drive batches multiple times, and the text note drop is gated by an iteration counter. On the first pass, the text note is suppressed, likely to prioritize encryption speed before littering the file system with ransom note files. For defenders and analysts, this has a practical implication: if testing with a minimal drive configuration that only triggers a single iteration, the text note will never appear.
Below is the text note content from the malware’s configuration.
HTML note (RECOVERY_CHAT.<UID>.html): This file is dropped to all drive root directories and all Desktop folders. Unlike the text note, the HTML note is a full interactive web application with a self-contained single-page application that implements end-to-end encrypted chat, a paginated data leak blog, and a file browser, all without requiring a traditional backend server. The technical architecture of this recovery chat system is detailed in Recovery chat: Technical architecture.
The most distinctive feature of the DeadLock ransomware is its recovery chat system. The RECOVERY_CHAT.<UID>.html file is a self-contained HTML application that implements a full end-to-end encrypted chat system, a paginated data leak blog, and a file browser, all without requiring a traditional backend server.
The architecture is designed with three decentralized components.
Rather than relying on traditional domain-based infrastructure that can be seized or taken offline, the DeadLock operators store configuration data on the Polygon blockchain. Two smart contracts serve as censorship-resistant infrastructure:
| Contract | Address | Function selector | Purpose |
| Chat proxy | 0x8EF7c3e531d871D3B9D559722DE77EB1dEc19dAe | 0x933a9ce8 | Stores the proxy server URL |
| Blog | 0x757984507c82c8dA1d3969c535dB5706eEE6426C | 0xd4070542 | Stores actor’s blog posts |
The HTML page issues eth_call requests to public Polygon Remote Procedure Call (RPC) endpoints (no wallet required with read-only calls) to obtain the proxy server address. The blog contract takes offset and limit parameters (for pagination) and returns structured data including post titles, bodies, timestamps, image URLs, and file attachment links.
On-chain storage provides several strategic advantages for the threat actor: the proxy URL can be updated by modifying the smart contract without changing any victim-facing infrastructure, and no domain registration or DNS infrastructure is required. This represents a notable evolution in ransomware infrastructure design.
The HTML recovery chat cycles through six public RPC endpoints for redundancy: polygon-bor-rpc.publicnode[.]com, polygon.drpc[.]org, polygon-pokt.nodies[.]app, polygon-rpc[.]com, 1rpc[.]io/matic, and polygon.meowrpc[.]com.
For victim-operator communication, chat messages are routed through the Session decentralized messenger network, which is an onion-routed, swarm-based messaging protocol that provides anonymity for both parties. The proxy server (whose URL is retrieved from the blockchain) acts as a relay between the victim’s browser and Session swarm nodes.
Key generation: DeadLock’s design choice is that the victim’s Session identity is derived deterministically from their sign-in credentials. When the victim enters their credentials on the HTML page, the following derivation occurs:
This deterministic derivation means the same credentials always produce the same keypair, and no account registration is needed as the victim’s Session identity exists only when they enter the correct credentials. If the victim forgets their credentials, the identity is unrecoverable (as stated by the actor in the chat UI). The 05 prefix is Session’s standard network identifier for user accounts.
Sending a message: The following sequence occurs when a message is sent:
Receiving a message: The following sequence occurs when a message is received:
The recovery chat page also provides access to a data leak blog whose content is stored on the Polygon blockchain.
Blog posts retrieved from the smart contract support BBCode formatting, image galleries, and file attachments using either direct URLs or Wasabi protocol links that open an in-browser file explorer. The HTML application contains a full Amazon Web Services (AWS) S3-compatible file browser that parses the Wasabi credentials from the URI, generates AWS4-HMAC-SHA256 signed requests, lists bucket contents with folder navigation, and generates pre-signed download URLs for individual files. This allows the attacker to host stolen data on Wasabi and provide victims or the public with browsable access to the leaked files without running a web server.
The architecture is significantly more resilient to takedown and censorship efforts, but it is not independent of off-chain infrastructure:
This infrastructure model represents a meaningful evolution from traditional ransomware communication channels and poses new challenges for takedown efforts.
As a final cleanup step after encryption completes, the malware creates a batch to delete its own binary from disk. The cleanup batch loops until it successfully deletes the malware binary, then removes itself:
Microsoft recommends the following mitigations to reduce the impact of this threat.
You can assess how an attack surface reduction rule might impact your network by opening the security recommendation for that rule in Vulnerability management. In the Recommendation details pane, check the user impact to determine what percentage of your devices can accept a new policy enabling the rule in blocking mode without adverse impact to user productivity.
Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.
Microsoft Defender Antivirus detects threat components as the following malware:
The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.
The following alerts might indicate threat activity associated with DeadLock ransomware if Defender for Endpoint is set to block mode.
The following alert might indicate threat activity associated with this threat. This alert, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.
Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.
Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:
Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.
Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.
Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.
| Indicator | Type | Description |
| a1fdf65020ce4a0f0940c793c6425baf8a0b994ec48b9baaf72788661a9d29f4 | SHA-256 | DeadLock ransomware encryptor |
| deadlock.liveblog365[.]com | URL | Leak site domain |
| dlock.liveblog365[.]com | URL | Leak site domain |
| deadblogdbdu5wprek7wa2o4ce7rnt6u6ntqeud3hzjjcveosgpsqqqd[.]onion | URL | Leak site domain |
| deadlockblog.great-site[.]net | URL | Leak site domain |
| deadlockblog.medianewsonline[.]com | URL | Leak site domain |
For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.
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The post DeadLock ransomware: Breaking down a Rust-based encryptor with decentralized recovery infrastructure appeared first on Microsoft Security Blog.
With identity protection services for millions of victims of the 2015 Office of Personnel Management breach set to expire, a group of lawmakers is making a push to extend them forever.
Sen. Mark Warner, D-Va., and Del. Eleanor Holmes Norton, D-D.C., introduced legislation to give lifetime identity protection coverage to around 4.2 million federal employees exposed in the historic breach by alleged Chinese hackers, which affected 22.1 million people. Warner said “the threat remains,” necessitating lifetime coverage.
That coverage is due to end at the end of September, as set by a 10-year authorization from Congress. That prompted the pair of lawmakers to introduce Reducing the Effects of the Cyberattack on OPM Victims Enduring Response and Protecting Identifiable Information Act, or RECOVER PII Act.
“The data stolen included workers’ most sensitive and personal information – from Social Security numbers to security clearance records – and once that information is in the hands of a bad actor, you don’t get it back,” Warner said in a news release Monday. “We have a responsibility to stand by the federal workers who were put at risk through no fault of their own. This legislation will ensure those affected continue to receive the identity protection they need, while helping better safeguard personal information from future exploitation.”
But the bill could have an uphill climb, given the makeup of Congress and stance of the Trump administration.
The Democratic co-sponsors in the Senate are Tim Kaine of Virginia, with Angela Alsobrooks of Chris Van Hollen, both of Maryland. The Democratic House cosponsors are Reps. Don Beyer and James Walkinshaw of Virginia, with Steny Hoyer of Maryland.
Warner and Norton listed no co-sponsors from the GOP, which controls both chambers of Congress and the White House. And OPM has declared the program too expensive based on the cost relative to the number of claims.
Similar legislation to extend the coverage, including from Norton, has fallen short in recent years.
“Lifetime identity protection is the only solution that will give the workers whose data was compromised the peace of mind they deserve,” Norton said Monday. “Because there is no limit on how long personal information can be exploited, Congress must protect these federal employees and contractors in perpetuity.”
Some watchdog scrutiny of the OPM program has been critical, and while consumer advocates say identity theft protections are helpful, they nonetheless say they aren’t adequate.
The Warner-Norton legislation also would offer reimbursements to federal employees and contractors for privacy services.
The post Lawmakers spring to save ID theft services for OPM breach victims, with expiration looming appeared first on CyberScoop.
Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945, a sub-cluster of Midnight Blizzard, conducting widespread but targeted traffic manipulation attacks involving hospitality sector networks served by captive portals worldwide. Despite some tactic, technique, and procedure (TTP) similarities to the Forest Blizzard DNS hijacking operation that we publicly disclosed in April 2026, we attribute this campaign, which we call CaptiveCrunch, to Storm-2945. As reported by ReliaQuest on July 23, a portion of this activity leverages doppelganger domains mimicking Microsoft online services to conduct follow-on adversary-in-the-middle (AitM) phishing operations that abuse the device code authentication flow in Microsoft Entra ID. Microsoft Threat Intelligence has also identified active traffic manipulation attacks leading to the delivery of malware on impacted systems. Microsoft has observed Storm-2945 leveraging AI to support a significant portion of these operations.
Today, we are sharing our findings on these ongoing intrusions to raise awareness of this threat and enable customers to protect their devices, especially while traveling. We provide our assessment of Storm-2945’s relationship to Midnight Blizzard and analysis of the CaptiveCrunch campaign, detailing the malware and tradecraft used in these operations. We also provide mitigation, detection, and hunting guidance to help organizations identify and defend against Storm-2945 and related activity.
Microsoft Threat Intelligence would like to thank our partners at Anthropic and OpenAI for their collaboration and support during this investigation.
Since February 2026, Storm-2945 has conducted AI-augmented operations including targeted device code and OAuth code phishing campaigns leading to Entra device registration and subsequent data collection from Microsoft 365. Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945 manipulating DNS and HTTP traffic from networks served by captive portals to redirect user traffic through actor-controlled infrastructure. Although our investigation into the initial compromise vector for the captive portal networks is ongoing, we have observed notable commonalities in the equipment and management systems used across multiple affected networks. These similarities suggest that the activity might not be limited to isolated compromises of individual venues and could reflect access to shared services within portions of the captive portal ecosystem.
As part of the CaptiveCrunch campaign, Storm-2945 has leveraged their AitM position to redirect users through actor-controlled phishing infrastructure and has also delivered malware purporting to be browser or operating system updates in response to automated connectivity checks issued by users’ browsers. Multiple variants have been delivered, including fully-featured Windows remote access trojans (RAT) in compiled Golang, with functionality to conduct system enumeration, collect files and keystrokes, steal credentials and session tokens, conduct audio and video surveillance, monitor for removable media, and provide the threat actor a remote shell on infected systems.
The threat actor infrastructure leverages a variety of ClickFix techniques to elicit the user into downloading and executing the malware:
In addition to variants of malware targeting Windows systems, Microsoft Threat Intelligence is also aware of indications that the threat actor might be targeting Android devices with similar techniques as the ClickFix landings also include instructions for Android devices to download and install an APK file.
To date, Microsoft has identified widespread compromise of Wi-Fi networks at hospitality-related organizations and other networks serviced by captive portal equipment in several countries. ReliaQuest has identified this activity not only at hotels, but also conference centers and other shared venues, and assesses that the goal of this activity is to access the accounts of corporate travelers.
Microsoft Threat Intelligence assesses that Storm-2945 is an operational sub-cluster of Midnight Blizzard based on distinctive technical and operational overlaps. These include technical similarities to Storm-2372, a Midnight Blizzard initial access operations sub-cluster, also notable for their device code and OAuth code phishing operations tracked throughout 2025, Microsoft Graph-based email exfiltration, social engineering delivered via commercial messaging apps, and significant similarities in victimology.
Midnight Blizzard is a Russia-based threat actor attributed by the US and UK governments to the Foreign Intelligence Service of the Russian Federation, also known as the SVR. This threat actor is known to primarily target governments, diplomatic entities, non-governmental organizations (NGOs), and information technology (IT) service providers, primarily in the US and Europe. Midnight Blizzard is consistent and persistent in their operational targeting, and their objectives rarely change. Their focus is to collect intelligence through longstanding and dedicated espionage in support of Russian foreign policy interests.
Midnight Blizzard operations often involve compromise of valid accounts and, in some highly targeted cases, advanced techniques to compromise authentication mechanisms within an organization to expand access and evade detection. They utilize diverse initial access methods, and Midnight Blizzard is also adept at identifying and abusing OAuth applications to move laterally across cloud environments and for post-compromise activity, such as email collection.
CornFlake is a full-featured Windows RAT written in Go that serves as Storm-2945’s primary persistent implant. Microsoft has observed the threat actor rapidly iterating on this malware layer, which features customizable capabilities from the social engineering user interface and data collection capabilities to anti-detection and evasion techniques.
On initial execution, CornFlake operates in dropper mode: it displays a convincing fake progress window designed to occupy the victim’s attention while the binary copies itself to %APPDATA%\svchost32\svchost32.exe and establishes persistence.
Fake window options configurable by the threat actor at build time:
CornFlake registers as a Windows service named svchost32 with the display name “Cloud Sync Service” and description “Synchronizes files with the cloud storage provider”, deliberately mimicking the legitimate svchost.exe process. It establishes redundant persistence mechanisms: Windows service registrations, Registry Run keys, named scheduled tasks, and a persistence watchdog routine that runs continuously to restore any persistence mechanism that is removed by defenders or endpoint protection.
For command and control (C2), CornFlake performs an Elliptic Curve Diffie-Hellman (ECDH) P-256 ephemeral key exchange with the C2 server, derives a session key via SHA-256, and communicates over a custom JSON protocol framed within the encrypted channel. This provides an encrypted channel to the C2 server, with each C2 session using a unique ephemeral key, making decryption of captured traffic impossible without the session-specific private key. The runtime configuration file sync.dat supports hot reconfiguration of C2 servers, watched directories, file targeting patterns, and Transport Layer Security (TLS) settings without requiring redeployment.
Once established on a victim system, CornFlake provides the operator with a comprehensive collection toolkit, gated by configuration flags that allow selective activation post-deployment:
| Capability | Description |
| Keylogging | Raw input API-based keylogger capturing all keystrokes, including password fields |
| Clipboard monitoring | Captures clipboard changes with SHA-256 deduplication and records the active window title at time of capture |
| Screenshot capture | Idle-triggered and on-demand screenshots with configurable idle threshold |
| Audio surveillance | Windows Audio Session API (WASAPI)-based microphone capture, encoded as WAV files |
| Video surveillance | Media Foundation-based webcam capture, encoded as JPEG |
| Browser credential theft | ChromeKatz-derived module supporting live cookie extraction from process memory (Chromium browsers) and stored password extraction from on-disk databases, including Chrome App-Bound Encryption (ABE) bypass and Firefox NSS/SDR decryption |
| File exfiltration | Targets files based on file extensions with real-time file system monitoring and an upload throttle (1,000 files or 500 MB per cycle). File extensions are categorized as Documents, Archives, Images, Code, Data, Emails, and Keys |
| USB drive monitoring | Detects and scans removable media when inserted |
| Security posture sweep | Collects 18 categories of host intelligence including installed software, antivirus (AV)/endpoint detection and response (EDR) products, Defender exclusions, User Account Control (UAC) level, Remote Desktop Protocol (RDP) history, Office most recently used (MRU) files, and credential hints |
| Remote shell | Arbitrary command execution via cmd.exe or PowerShell (with -NoP flag to suppress profile-based detection) |
CornFlake also exposes a localhost HTTP API server (/upload, /reload, /status) that transforms the RAT into a modular platform: companion or next-stage payloads such as ChocoShell could task file exfiltration, trigger configuration hot reloads or check C2 connectivity using the pre-established secure C2 channel for communication.
ChocoShell is the campaign’s Powershell-based infostealer, delivered and executed entirely in-memory. Its primary objective is the high-volume theft of browser session cookies, saved passwords, Microsoft 365 Single Sign-On (SSO) tokens, and Wi-Fi credentials from compromised systems. Where CornFlake provides the operator with a persistent, long-running foothold on the device, ChocoShell is designed to extract the most operationally valuable credentials, giving the operator access to victim cloud environments.
The ChocoShell script was authored with full developer comments that reveal the operator’s intent behind each code decision, including explicit references to Microsoft detection signatures and the reasoning behind specific evasion choices. The consistent coding standard and descriptive commentary suggest the author might have leveraged AI-assisted code generation.
Defense evasion. Upon execution, ChocoShell beacons to a hardcoded C2 server at 213.145.86[.]112 and implements several evasion techniques in sequence. It disables the Antimalware Scan Interface (AMSI) via .NET reflection to prevent ScriptBlock scanning and evades Microsoft behavioral detection that triggers on suspicious PowerShell web request cmdlets. A timing-based sandbox detection check is also employed as a virtual machine (VM) detection mechanism, silently exiting without performing any collection if detected.
C2 communication. ChocoShell communicates with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel. Additional tooling is fetched from /cdn/chunks/polyfill-7e2b.min.js, disguised as a JavaScript polyfill file. This downloaded module is Base64-decoded and executed in memory via [ScriptBlock]::Create(), providing browser encryption key extraction capabilities, SYSTEM token impersonation, and Defender signature locking. Exfiltrated data is sent by POST to /t/event as GZip-compressed, Base64-wrapped JSON.
Privilege escalation. ChocoShell requires administrative privileges for its most impactful capabilities: SYSTEM token impersonation for Chrome ABE decryption, Volume Shadow Copy Service (VSS) shadow copy creation, Defender signature locking. It implements three silent UAC bypass techniques with ordered fallback:
If none of the silent bypasses succeed (for example, the user is not a local administrator), ChocoShell falls back to a visible UAC prompt via Start-Process -Verb RunAs. Notably, the script also contains a variant designed to execute within the WinGet Desired State Configuration (DSC) host process (ConfigurationRemotingServer), suggesting an attack vector through malicious WinGet DSC configuration used in Windows machine provisioning.
Credential and session theft. Once running with elevated permissions, ChocoShell locks Defender signature updates and systematically harvests data from multiple sources. For Chromium-based browsers (Chrome, Edge, Brave, Opera, Opera GX, Vivaldi), it extracts the master encryption key from the browser’s Local State file, handling both the modern ABE scheme (Chrome v127+) and the legacy data protection API (DPAPI)-only scheme. ABE decryption requires SYSTEM-level DPAPI access, which the malware obtains by impersonating a SYSTEM process token borrowed from winlogon.exe, wininit.exe, or services.exe. Locked browser SQLite databases are accessed through three strategies: shared file access, Volume Shadow Service snapshots, and direct copy as a fallback.
As a parallel collection path, ChocoShell launches Chrome, Edge, and Brave with the –remote-debugging-port flag and issues Network.getAllCookies through the Chrome DevTools Protocol (CDP). This completely bypasses ABE, enabling the browser to perform its own internal decryption and returns plaintext cookie values. To handle privilege issues (SYSTEM-launched browsers inherit the wrong token), the malware creates transient scheduled tasks with TASK_LOGON_INTERACTIVE_TOKEN to launch the browser under the signed-in user’s session. After extraction, the browser is stopped and relaunched with –restore-last-session to avoid alerting the user.
For Firefox family browsers (Firefox, Waterfox, LibreWolf, Floorp, Zen), the malware copies unencrypted cookies.sqlite databases from each profile. Additionally, ChocoShell collects Microsoft 365 and Azure Active Directory (AD) access tokens, refresh tokens, and Web Account Manager (WAM) tokens from .tbres files in the Token Broker cache. Collection of these tokens represents a significant threat to enterprise environments, as threat actors could replay SSO sessions without browser cookies. Additionally, Wi-Fi credentials are harvested via netsh wlan show profile with key=clear.
Exfiltration and cleanup. All collected data is aggregated into a JSON structure, GZip-compressed, Base64-encoded, and sent by POST to the C2’s /t/event endpoint. After exfiltration, all collected data variables are nulled, garbage collection is forced, VSS shadow copies are deleted via Windows Management Instrumentation (WMI), temporary elevation scripts are removed, and all UAC bypass registry keys (already cleaned during escalation) are verified removed.
FruitStone is the web-based C2 panel that Storm-2945 operators use to manage the entire CaptiveCrunch campaign infrastructure. Implemented as a single-page application (HTML and JavaScript) serving as the front-end of the C2 server with all functionality exposed without authentication, FruitStone provides a centralized dashboard for managing compromised endpoints, building and deploying new campaign payloads, and reviewing all collected data (such as screenshots, keystrokes, browser credentials).
Operational cover. The panel is branded as “CloudSync Console” with a footer reading “Acuity Systems, Inc. — Cloud Infrastructure Portal v3.2.1,” designed to appear as legitimate enterprise cloud management software if the panel URL is discovered by defenders or hosting providers. This masquerading extends to the CornFlake agent’s service name (Cloud Sync Service) and description (“Synchronizes files with the cloud storage provider”), creating a consistent cover story across the toolchain.
Session management and multi-operator support. FruitStone uses JSON Web Token (JWT)-based authentication, session revocation, and rate limiting with IP blocking to prevent brute force attacks against the panel sign in. Multiple operators could be provisioned with individual accounts, and all active sessions are visible with IP address, user-agent, and creation time to enable operational security awareness across the operators.
Agent management. The panel displays all registered CornFlake agents in a dashboard with real-time status updates via Server-Sent Events (SSE). Each agent card shows comprehensive system information including hostname, username, OS version, CPU, RAM, disk usage, screen resolution, timezone, domain membership, and camera/microphone presence, all collected during the CornFlake posture sweep. Agents are grouped by country and subnet, with geographic distribution visualized on a map.
Operators could interact with individual agents through:
Campaign builder. A step-by-step wizard enables operators to configure and build new CornFlake payloads directly from the panel:
Infrastructure management. FruitStone provides management interfaces for three layers of supporting infrastructure:
Since July 16, Microsoft has observed a portion of CaptiveCrunch landing pages redirecting users to device code authentication flow experiences. In these cases, users served these landings might be instructed to enter a device code into a legitimate Microsoft sign-in page, a technique commonly referred to as device code phishing.
Device code authentication is a legitimate OAuth workflow designed for devices that cannot support a traditional sign-in experience. However, threat actors could abuse this flow by initiating an authentication request on behalf of a user then convincing the user to enter an actor-controlled device code into a legitimate Microsoft authentication page. When successful, the victim authenticates the threat actor’s session rather than their own.
This activity is consistent with previously reported device code phishing operations conducted by Midnight Blizzard since August 2024. The observed technique does not appear fundamentally novel; however, integrating device code phishing into captive portal and traffic manipulation operations might increase the likelihood that users perceive the authentication request as legitimate. For additional details on Midnight Blizzard-related device code phishing techniques, see: Storm-2372 conducts device code phishing campaign. To understand other threat actors’ use of device code phishing and associated mitigations, see Inside an AI‑enabled device code phishing campaign.
When traveling, users should treat hotel, conference, airport, and other guest wireless networks as untrustworthy.
Organizations should assume that public and hospitality network infrastructure might not be trustworthy and should adopt controls that limit exposure to traffic manipulation, credential theft, and device code phishing.
Organizations should review what information employees provide to hospitality providers when connecting to guest networks.
Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.
Microsoft Defender for Endpoint detects Storm-2945 activity under the detection Suspicious activity linked to a Russian state-sponsored threat actor has been detected. However, these alerts might be triggered by unrelated threat actor activity. The following chart lists Microsoft Defender detections specific to the TTPs utilized by Storm-2945 in this attack.
| Tactic | Observed activity | Microsoft Defender coverage |
| Initial access | File download via captive portal redirection | Microsoft Defender for Endpoint – Suspicious downloaded file |
| Initial access | ClickFix technique, fake browser or OS update, initial file download | Microsoft Defender for Endpoint – Possible initial access from an emerging threat – Possible ClickFix activity |
| Persistence | CornFlake registers a Windows service, a Registry Run key, a scheduled task | Microsoft Defender for Endpoint – Suspicious Scheduled Task Process Launched – Suspicious scheduled task – Suspicious file added to run key – Suspicious service registration Microsoft Entra ID Protection – Microsoft Entra threat intelligence – Verified threat actor IP |
| Stealth/Defense evasion | ChocoShell disables AMSI | Microsoft Defender for Endpoint – Possible Antimalware Scan Interface (AMSI) tampering |
| Credential access | ChocoShell’s theft of browser session cookies, saved passwords, Microsoft 365 SSO tokens, and Wi-Fi credentials. Device code abuse. | Microsoft Defender for Endpoint – Possible theft of passwords and other sensitive web browser information – Suspicious DPAPI activity Microsoft Defender For Identity – Anomalous OAuth device code authentication activity Microsoft Defender XDR – User account compromise via OAuth device code phishing – Malicious sign in from an IP address associated with recognized attacker infrastructure – Suspicious Azure authentication through possible device code phishing |
| Collection | CornFlake monitoring and logging | Microsoft Defender for Endpoint – Activity that might lead to information stealer |
| Privilege escalation | ChocoShell UAC bypass techniques | Microsoft Defender for Endpoint – UAC bypass was detected – Possible Component Object Model (COM) hijacking |
Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.
Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:
Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.
Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.
Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.
Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:
Detect file creation after Wi-Fi connectivity test on devices
The following query checks for a file creation on a device within two minutes of the device performing built‑in Network Connectivity Status Indicator (NCSI) test, which occurs when network connectivity is established to a Wi-Fi network with a captive portal. This activity might indicate an attacker’s initial access file presence on a device.
Please note that not all files discovered through this query might be malicious or related to this threat activity.
Login
let ncsi_endpoints = dynamic(["msftconnecttest.com","edge-http.microsoft.com","msftncsi.com","captive.apple.com","clients1.google.com",
"clients3.google.com","clients4.google.com","clients6.google.com","connectivitycheck.gstatic.com","connectivitycheck.android.com",
"android.clients.google.com","www.gstatic.com","detectportal.firefox.com","detectportal.brave-http-only.com","cloudflareportal.com",
"cloudflarecp.com","cloudflareok.com","connectivity-check.warp-svc","connectivity.cloudflareclient.com","spectrum.s3.amazonaws.com",
"nmcheck.gnome.org"]);
let NCSIEvents = DeviceNetworkEvents
| where Timestamp > ago(7d)
| where RemoteUrl has_any (ncsi_endpoints)
| project NCSI_Timestamp = Timestamp, DeviceId, DeviceName, RemoteUrl, NCSI_ReportId = ReportId, NCSI_InitiatingProcessFileName = InitiatingProcessFileName, NCSI_InitiatingProcessCommandLine = InitiatingProcessCommandLine, NCSI_AccountName = InitiatingProcessAccountName;
let FileDownloadEvents = DeviceFileEvents
| where Timestamp > ago(7d)
| where ActionType == "FileCreated"
| where FileName has_any (".exe",".msi",".zip",".rar",".7z")
| project Download_Timestamp = Timestamp, DeviceId, FileName, FolderPath, Download_ReportId = ReportId, Download_InitiatingProcessFileName = InitiatingProcessFileName, Download_InitiatingProcessCommandLine = InitiatingProcessCommandLine, Download_AccountName = InitiatingProcessAccountName;
NCSIEvents
| join kind=inner (
FileDownloadEvents
) on DeviceId
| where Download_Timestamp >= NCSI_Timestamp and Download_Timestamp Detect connectivity to Storm-2945 infrastructure
The following query checks for connectivity to Storm-2945 infrastructure observed in this attack activity.
let target_domains = dynamic(["ms365-device.com", "ms365-live.com", "m365-owa.com", "owa-ms365.com"]);
let target_ips = dynamic(["31.57.243.154", "38.146.28.75", "38.146.28.132", "104.194.159.150", "107.189.26.194", "213.145.86.112"]);
DeviceNetworkEvents
| where RemoteUrl has_any(target_domains) or RemoteIP in (target_ips)
| project
Timestamp,
DeviceName,
DeviceId,
RemoteUrl,
RemoteIP,
LocalIP,
InitiatingProcessFileName,
InitiatingProcessCommandLine,
AccountName = InitiatingProcessAccountName,
ReportId
Detect CornFlake RAT presence on affected systems
The following query checks for the presence of the CornFlake RAT binary.
DeviceProcessEvents | where FolderPath == "%APPDATA%\\svchost32\\svchost32.exe" or FolderPath endswith @"\svchost32\svchost32.exe" | project Timestamp, DeviceName, DeviceId, FileName, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine, AccountName, ReportId
Detect CornFlake RAT Windows service registration
The following query checks for the CornFlake RAT Windows service registration.
DeviceRegistryEvents
| where RegistryKey has @"\SYSTEM\CurrentControlSet\Services\svchost32"
| where ActionType == "RegistryValueSet"
| where (RegistryValueName == "DisplayName" and RegistryValueData == "Cloud Sync Service")
or (RegistryValueName == "Description" and RegistryValueData == "Synchronizes files with the cloud storage provider")
| project
Timestamp,
DeviceName,
DeviceId,
RegistryKey,
RegistryValueName,
RegistryValueData,
ActionType,
InitiatingProcessFileName,
InitiatingProcessCommandLine,
InitiatingProcessAccountName,
ReportId
Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.
Detect network IP and domain indicators of compromise using ASIM
The following query checks IP addresses and domain IOCs across data sources supported by ASIM network session parser:
//IP list and domain list- _Im_NetworkSession let lookback = 30d; let ioc_ip_addr = dynamic(["213.145.86.112"]); let ioc_domains = dynamic(["213.145.86.112/t/pixel.gif", "213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "213.145.86.112/t/event"]); _Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now()) | where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains) | summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor
Detect web sessions IP and file hash indicators of compromise using ASIM
The following query checks IP addresses, domains, and file hash IOCs across data sources supported by ASIM web session parser:
//IP list - _Im_WebSession let lookback = 30d; let ioc_ip_addr = dynamic(["213.145.86.112"]); let ioc_sha_hashes =dynamic([“918fa52ae45ed60ba7cc8bdc99c3cbe9ab92e0375ec31fc05d0d4513be11c593”, “be99857449d2856dd5a84e21c8a3d5e0e01456adb44062ddec5a6b4970d8d42c”]); _Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now()) | where DstIpAddr in (ioc_ip_addr) or FileSHA256 in (ioc_sha_hashes) | summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor
Detect domain and URL indicators of compromise using ASIM
The following query checks domain and URL IOCs across data sources supported by ASIM web session parser:
// file hash list - imFileEvent // Domain list - _Im_WebSession let ioc_domains = dynamic(["https://213.145.86.112/t/pixel.gif", "https://213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "https://213.145.86.112/t/event"]); _Im_WebSession (url_has_any = ioc_domains)
ChocoShell C2 communications
The following query detects ChocoShell communications with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel.
let lookback = 30d; let ioc_url_artifacts = dynamic(["/t/pixel.gif?m="]); _Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now()) | where DstDomain in (ioc_url_artifacts) | summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor
| Indicator | Type | Description | First seen |
| ms365-device[.]com | Domain | CaptiveCrunch DCF redirect | 2026-07-23 |
| ms365-live[.]com | Domain | CaptiveCrunch DCF redirect | 2026-05-14 |
| m365-owa[.]com | Domain | CaptiveCrunch AitM infrastructure | 2026-07-20 |
| owa-ms365[.]com | Domain | CaptiveCrunch AitM infrastructure | 2026-07-16 |
| 31.57.243[.]154 | IP address | CaptiveCrunch AitM infrastructure | 2026-07-16 |
| 38.146.28[.]75 | IP address | CaptiveCrunch AitM infrastructure | 2026-07-01 |
| 38.146.28[.]132 | IP address | CaptiveCrunch DNS Resolver | 2026-07-15 |
| 104.194.159[.]150 | IP address | CaptiveCrunch AitM infrastructure | 2026-04-28 |
| 107.189.26[.]194 | IP address | ChocoShell C2 / CaptiveCrunch DNS Resolver | 2026-02-27 |
| 213.145.86[.]112 | IP address | ChocoShell C2 | 2026-07-01 |
| 918fa52ae45ed60ba7cc8bdc99c3cbe9ab92e0375ec31fc05d0d4513be11c593 | File hash | CornFlake | 2026-07-03 |
| be99857449d2856dd5a84e21c8a3d5e0e01456adb44062ddec5a6b4970d8d42c | File hash | ChocoShell | 2026-07-10 |
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The post CaptiveCrunch: Midnight Blizzard targets travelers worldwide for malware delivery and credential theft appeared first on Microsoft Security Blog.
Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945, a sub-cluster of Midnight Blizzard, conducting widespread but targeted traffic manipulation attacks involving hospitality sector networks served by captive portals worldwide. Despite some tactic, technique, and procedure (TTP) similarities to the Forest Blizzard DNS hijacking operation that we publicly disclosed in April 2026, we attribute this campaign, which we call CaptiveCrunch, to Storm-2945. As reported by ReliaQuest on July 23, a portion of this activity leverages doppelganger domains mimicking Microsoft online services to conduct follow-on adversary-in-the-middle (AitM) phishing operations that abuse the device code authentication flow in Microsoft Entra ID. Microsoft Threat Intelligence has also identified active traffic manipulation attacks leading to the delivery of malware on impacted systems. Microsoft has observed Storm-2945 leveraging AI to support a significant portion of these operations.
Today, we are sharing our findings on these ongoing intrusions to raise awareness of this threat and enable customers to protect their devices, especially while traveling. We provide our assessment of Storm-2945’s relationship to Midnight Blizzard and analysis of the CaptiveCrunch campaign, detailing the malware and tradecraft used in these operations. We also provide mitigation, detection, and hunting guidance to help organizations identify and defend against Storm-2945 and related activity.
Microsoft Threat Intelligence would like to thank our partners at Anthropic and OpenAI for their collaboration and support during this investigation.
Since February 2026, Storm-2945 has conducted AI-augmented operations including targeted device code and OAuth code phishing campaigns leading to Entra device registration and subsequent data collection from Microsoft 365. Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945 manipulating DNS and HTTP traffic from networks served by captive portals to redirect user traffic through actor-controlled infrastructure. Although our investigation into the initial compromise vector for the captive portal networks is ongoing, we have observed notable commonalities in the equipment and management systems used across multiple affected networks. These similarities suggest that the activity might not be limited to isolated compromises of individual venues and could reflect access to shared services within portions of the captive portal ecosystem.
As part of the CaptiveCrunch campaign, Storm-2945 has leveraged their AitM position to redirect users through actor-controlled phishing infrastructure and has also delivered malware purporting to be browser or operating system updates in response to automated connectivity checks issued by users’ browsers. Multiple variants have been delivered, including fully-featured Windows remote access trojans (RAT) in compiled Golang, with functionality to conduct system enumeration, collect files and keystrokes, steal credentials and session tokens, conduct audio and video surveillance, monitor for removable media, and provide the threat actor a remote shell on infected systems.
The threat actor infrastructure leverages a variety of ClickFix techniques to elicit the user into downloading and executing the malware:
In addition to variants of malware targeting Windows systems, Microsoft Threat Intelligence is also aware of indications that the threat actor might be targeting Android devices with similar techniques as the ClickFix landings also include instructions for Android devices to download and install an APK file.
To date, Microsoft has identified widespread compromise of Wi-Fi networks at hospitality-related organizations and other networks serviced by captive portal equipment in several countries. ReliaQuest has identified this activity not only at hotels, but also conference centers and other shared venues, and assesses that the goal of this activity is to access the accounts of corporate travelers.
Microsoft Threat Intelligence assesses that Storm-2945 is an operational sub-cluster of Midnight Blizzard based on distinctive technical and operational overlaps. These include technical similarities to Storm-2372, a Midnight Blizzard initial access operations sub-cluster, also notable for their device code and OAuth code phishing operations tracked throughout 2025, Microsoft Graph-based email exfiltration, social engineering delivered via commercial messaging apps, and significant similarities in victimology.
Midnight Blizzard is a Russia-based threat actor attributed by the US and UK governments to the Foreign Intelligence Service of the Russian Federation, also known as the SVR. This threat actor is known to primarily target governments, diplomatic entities, non-governmental organizations (NGOs), and information technology (IT) service providers, primarily in the US and Europe. Midnight Blizzard is consistent and persistent in their operational targeting, and their objectives rarely change. Their focus is to collect intelligence through longstanding and dedicated espionage in support of Russian foreign policy interests.
Midnight Blizzard operations often involve compromise of valid accounts and, in some highly targeted cases, advanced techniques to compromise authentication mechanisms within an organization to expand access and evade detection. They utilize diverse initial access methods, and Midnight Blizzard is also adept at identifying and abusing OAuth applications to move laterally across cloud environments and for post-compromise activity, such as email collection.
CornFlake is a full-featured Windows RAT written in Go that serves as Storm-2945’s primary persistent implant. Microsoft has observed the threat actor rapidly iterating on this malware layer, which features customizable capabilities from the social engineering user interface and data collection capabilities to anti-detection and evasion techniques.
On initial execution, CornFlake operates in dropper mode: it displays a convincing fake progress window designed to occupy the victim’s attention while the binary copies itself to %APPDATA%\svchost32\svchost32.exe and establishes persistence.
Fake window options configurable by the threat actor at build time:
CornFlake registers as a Windows service named svchost32 with the display name “Cloud Sync Service” and description “Synchronizes files with the cloud storage provider”, deliberately mimicking the legitimate svchost.exe process. It establishes redundant persistence mechanisms: Windows service registrations, Registry Run keys, named scheduled tasks, and a persistence watchdog routine that runs continuously to restore any persistence mechanism that is removed by defenders or endpoint protection.
For command and control (C2), CornFlake performs an Elliptic Curve Diffie-Hellman (ECDH) P-256 ephemeral key exchange with the C2 server, derives a session key via SHA-256, and communicates over a custom JSON protocol framed within the encrypted channel. This provides an encrypted channel to the C2 server, with each C2 session using a unique ephemeral key, making decryption of captured traffic impossible without the session-specific private key. The runtime configuration file sync.dat supports hot reconfiguration of C2 servers, watched directories, file targeting patterns, and Transport Layer Security (TLS) settings without requiring redeployment.
Once established on a victim system, CornFlake provides the operator with a comprehensive collection toolkit, gated by configuration flags that allow selective activation post-deployment:
| Capability | Description |
| Keylogging | Raw input API-based keylogger capturing all keystrokes, including password fields |
| Clipboard monitoring | Captures clipboard changes with SHA-256 deduplication and records the active window title at time of capture |
| Screenshot capture | Idle-triggered and on-demand screenshots with configurable idle threshold |
| Audio surveillance | Windows Audio Session API (WASAPI)-based microphone capture, encoded as WAV files |
| Video surveillance | Media Foundation-based webcam capture, encoded as JPEG |
| Browser credential theft | ChromeKatz-derived module supporting live cookie extraction from process memory (Chromium browsers) and stored password extraction from on-disk databases, including Chrome App-Bound Encryption (ABE) bypass and Firefox NSS/SDR decryption |
| File exfiltration | Targets files based on file extensions with real-time file system monitoring and an upload throttle (1,000 files or 500 MB per cycle). File extensions are categorized as Documents, Archives, Images, Code, Data, Emails, and Keys |
| USB drive monitoring | Detects and scans removable media when inserted |
| Security posture sweep | Collects 18 categories of host intelligence including installed software, antivirus (AV)/endpoint detection and response (EDR) products, Defender exclusions, User Account Control (UAC) level, Remote Desktop Protocol (RDP) history, Office most recently used (MRU) files, and credential hints |
| Remote shell | Arbitrary command execution via cmd.exe or PowerShell (with -NoP flag to suppress profile-based detection) |
CornFlake also exposes a localhost HTTP API server (/upload, /reload, /status) that transforms the RAT into a modular platform: companion or next-stage payloads such as ChocoShell could task file exfiltration, trigger configuration hot reloads or check C2 connectivity using the pre-established secure C2 channel for communication.
ChocoShell is the campaign’s Powershell-based infostealer, delivered and executed entirely in-memory. Its primary objective is the high-volume theft of browser session cookies, saved passwords, Microsoft 365 Single Sign-On (SSO) tokens, and Wi-Fi credentials from compromised systems. Where CornFlake provides the operator with a persistent, long-running foothold on the device, ChocoShell is designed to extract the most operationally valuable credentials, giving the operator access to victim cloud environments.
The ChocoShell script was authored with full developer comments that reveal the operator’s intent behind each code decision, including explicit references to Microsoft detection signatures and the reasoning behind specific evasion choices. The consistent coding standard and descriptive commentary suggest the author might have leveraged AI-assisted code generation.
Defense evasion. Upon execution, ChocoShell beacons to a hardcoded C2 server at 213.145.86[.]112 and implements several evasion techniques in sequence. It disables the Antimalware Scan Interface (AMSI) via .NET reflection to prevent ScriptBlock scanning and evades Microsoft behavioral detection that triggers on suspicious PowerShell web request cmdlets. A timing-based sandbox detection check is also employed as a virtual machine (VM) detection mechanism, silently exiting without performing any collection if detected.
C2 communication. ChocoShell communicates with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel. Additional tooling is fetched from /cdn/chunks/polyfill-7e2b.min.js, disguised as a JavaScript polyfill file. This downloaded module is Base64-decoded and executed in memory via [ScriptBlock]::Create(), providing browser encryption key extraction capabilities, SYSTEM token impersonation, and Defender signature locking. Exfiltrated data is sent by POST to /t/event as GZip-compressed, Base64-wrapped JSON.
Privilege escalation. ChocoShell requires administrative privileges for its most impactful capabilities: SYSTEM token impersonation for Chrome ABE decryption, Volume Shadow Copy Service (VSS) shadow copy creation, Defender signature locking. It implements three silent UAC bypass techniques with ordered fallback:
If none of the silent bypasses succeed (for example, the user is not a local administrator), ChocoShell falls back to a visible UAC prompt via Start-Process -Verb RunAs. Notably, the script also contains a variant designed to execute within the WinGet Desired State Configuration (DSC) host process (ConfigurationRemotingServer), suggesting an attack vector through malicious WinGet DSC configuration used in Windows machine provisioning.
Credential and session theft. Once running with elevated permissions, ChocoShell locks Defender signature updates and systematically harvests data from multiple sources. For Chromium-based browsers (Chrome, Edge, Brave, Opera, Opera GX, Vivaldi), it extracts the master encryption key from the browser’s Local State file, handling both the modern ABE scheme (Chrome v127+) and the legacy data protection API (DPAPI)-only scheme. ABE decryption requires SYSTEM-level DPAPI access, which the malware obtains by impersonating a SYSTEM process token borrowed from winlogon.exe, wininit.exe, or services.exe. Locked browser SQLite databases are accessed through three strategies: shared file access, Volume Shadow Service snapshots, and direct copy as a fallback.
As a parallel collection path, ChocoShell launches Chrome, Edge, and Brave with the –remote-debugging-port flag and issues Network.getAllCookies through the Chrome DevTools Protocol (CDP). This completely bypasses ABE, enabling the browser to perform its own internal decryption and returns plaintext cookie values. To handle privilege issues (SYSTEM-launched browsers inherit the wrong token), the malware creates transient scheduled tasks with TASK_LOGON_INTERACTIVE_TOKEN to launch the browser under the signed-in user’s session. After extraction, the browser is stopped and relaunched with –restore-last-session to avoid alerting the user.
For Firefox family browsers (Firefox, Waterfox, LibreWolf, Floorp, Zen), the malware copies unencrypted cookies.sqlite databases from each profile. Additionally, ChocoShell collects Microsoft 365 and Azure Active Directory (AD) access tokens, refresh tokens, and Web Account Manager (WAM) tokens from .tbres files in the Token Broker cache. Collection of these tokens represents a significant threat to enterprise environments, as threat actors could replay SSO sessions without browser cookies. Additionally, Wi-Fi credentials are harvested via netsh wlan show profile with key=clear.
Exfiltration and cleanup. All collected data is aggregated into a JSON structure, GZip-compressed, Base64-encoded, and sent by POST to the C2’s /t/event endpoint. After exfiltration, all collected data variables are nulled, garbage collection is forced, VSS shadow copies are deleted via Windows Management Instrumentation (WMI), temporary elevation scripts are removed, and all UAC bypass registry keys (already cleaned during escalation) are verified removed.
FruitStone is the web-based C2 panel that Storm-2945 operators use to manage the entire CaptiveCrunch campaign infrastructure. Implemented as a single-page application (HTML and JavaScript) serving as the front-end of the C2 server with all functionality exposed without authentication, FruitStone provides a centralized dashboard for managing compromised endpoints, building and deploying new campaign payloads, and reviewing all collected data (such as screenshots, keystrokes, browser credentials).
Operational cover. The panel is branded as “CloudSync Console” with a footer reading “Acuity Systems, Inc. — Cloud Infrastructure Portal v3.2.1,” designed to appear as legitimate enterprise cloud management software if the panel URL is discovered by defenders or hosting providers. This masquerading extends to the CornFlake agent’s service name (Cloud Sync Service) and description (“Synchronizes files with the cloud storage provider”), creating a consistent cover story across the toolchain.
Session management and multi-operator support. FruitStone uses JSON Web Token (JWT)-based authentication, session revocation, and rate limiting with IP blocking to prevent brute force attacks against the panel sign in. Multiple operators could be provisioned with individual accounts, and all active sessions are visible with IP address, user-agent, and creation time to enable operational security awareness across the operators.
Agent management. The panel displays all registered CornFlake agents in a dashboard with real-time status updates via Server-Sent Events (SSE). Each agent card shows comprehensive system information including hostname, username, OS version, CPU, RAM, disk usage, screen resolution, timezone, domain membership, and camera/microphone presence, all collected during the CornFlake posture sweep. Agents are grouped by country and subnet, with geographic distribution visualized on a map.
Operators could interact with individual agents through:
Campaign builder. A step-by-step wizard enables operators to configure and build new CornFlake payloads directly from the panel:
Infrastructure management. FruitStone provides management interfaces for three layers of supporting infrastructure:
Since July 16, Microsoft has observed a portion of CaptiveCrunch landing pages redirecting users to device code authentication flow experiences. In these cases, users served these landings might be instructed to enter a device code into a legitimate Microsoft sign-in page, a technique commonly referred to as device code phishing.
Device code authentication is a legitimate OAuth workflow designed for devices that cannot support a traditional sign-in experience. However, threat actors could abuse this flow by initiating an authentication request on behalf of a user then convincing the user to enter an actor-controlled device code into a legitimate Microsoft authentication page. When successful, the victim authenticates the threat actor’s session rather than their own.
This activity is consistent with previously reported device code phishing operations conducted by Midnight Blizzard since August 2024. The observed technique does not appear fundamentally novel; however, integrating device code phishing into captive portal and traffic manipulation operations might increase the likelihood that users perceive the authentication request as legitimate. For additional details on Midnight Blizzard-related device code phishing techniques, see: Storm-2372 conducts device code phishing campaign. To understand other threat actors’ use of device code phishing and associated mitigations, see Inside an AI‑enabled device code phishing campaign.
When traveling, users should treat hotel, conference, airport, and other guest wireless networks as untrustworthy.
Organizations should assume that public and hospitality network infrastructure might not be trustworthy and should adopt controls that limit exposure to traffic manipulation, credential theft, and device code phishing.
Organizations should review what information employees provide to hospitality providers when connecting to guest networks.
Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.
Microsoft Defender for Endpoint detects Storm-2945 activity under the detection Suspicious activity linked to a Russian state-sponsored threat actor has been detected. However, these alerts might be triggered by unrelated threat actor activity. The following chart lists Microsoft Defender detections specific to the TTPs utilized by Storm-2945 in this attack.
| Tactic | Observed activity | Microsoft Defender coverage |
| Initial access | File download via captive portal redirection | Microsoft Defender for Endpoint – Suspicious downloaded file |
| Initial access | ClickFix technique, fake browser or OS update, initial file download | Microsoft Defender for Endpoint – Possible initial access from an emerging threat – Possible ClickFix activity |
| Persistence | CornFlake registers a Windows service, a Registry Run key, a scheduled task | Microsoft Defender for Endpoint – Suspicious Scheduled Task Process Launched – Suspicious scheduled task – Suspicious file added to run key – Suspicious service registration Microsoft Entra ID Protection – Microsoft Entra threat intelligence – Verified threat actor IP |
| Stealth/Defense evasion | ChocoShell disables AMSI | Microsoft Defender for Endpoint – Possible Antimalware Scan Interface (AMSI) tampering |
| Credential access | ChocoShell’s theft of browser session cookies, saved passwords, Microsoft 365 SSO tokens, and Wi-Fi credentials. Device code abuse. | Microsoft Defender for Endpoint – Possible theft of passwords and other sensitive web browser information – Suspicious DPAPI activity Microsoft Defender For Identity – Anomalous OAuth device code authentication activity Microsoft Defender XDR – User account compromise via OAuth device code phishing – Malicious sign in from an IP address associated with recognized attacker infrastructure – Suspicious Azure authentication through possible device code phishing |
| Collection | CornFlake monitoring and logging | Microsoft Defender for Endpoint – Activity that might lead to information stealer |
| Privilege escalation | ChocoShell UAC bypass techniques | Microsoft Defender for Endpoint – UAC bypass was detected – Possible Component Object Model (COM) hijacking |
Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.
Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:
Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.
Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.
Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.
Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:
Detect file creation after Wi-Fi connectivity test on devices
The following query checks for a file creation on a device within two minutes of the device performing built‑in Network Connectivity Status Indicator (NCSI) test, which occurs when network connectivity is established to a Wi-Fi network with a captive portal. This activity might indicate an attacker’s initial access file presence on a device.
Please note that not all files discovered through this query might be malicious or related to this threat activity.
let ncsi_endpoints = dynamic(["msftconnecttest.com","edge-http.microsoft.com","msftncsi.com","captive.apple.com","clients1.google.com",
"clients3.google.com","clients4.google.com","clients6.google.com","connectivitycheck.gstatic.com","connectivitycheck.android.com",
"android.clients.google.com","www.gstatic.com","detectportal.firefox.com","detectportal.brave-http-only.com","cloudflareportal.com",
"cloudflarecp.com","cloudflareok.com","connectivity-check.warp-svc","connectivity.cloudflareclient.com","spectrum.s3.amazonaws.com",
"nmcheck.gnome.org"]);
let NCSIEvents = DeviceNetworkEvents
| where Timestamp > ago(7d)
| where RemoteUrl has_any (ncsi_endpoints)
| project NCSI_Timestamp = Timestamp, DeviceId, DeviceName, RemoteUrl, NCSI_ReportId = ReportId, NCSI_InitiatingProcessFileName = InitiatingProcessFileName, NCSI_InitiatingProcessCommandLine = InitiatingProcessCommandLine, NCSI_AccountName = InitiatingProcessAccountName;
let FileDownloadEvents = DeviceFileEvents
| where Timestamp > ago(7d)
| where ActionType == "FileCreated"
| where FileName has_any (".exe",".msi",".zip",".rar",".7z")
| project Download_Timestamp = Timestamp, DeviceId, FileName, FolderPath, Download_ReportId = ReportId, Download_InitiatingProcessFileName = InitiatingProcessFileName, Download_InitiatingProcessCommandLine = InitiatingProcessCommandLine, Download_AccountName = InitiatingProcessAccountName;
NCSIEvents
| join kind=inner (
FileDownloadEvents
) on DeviceId
| where Download_Timestamp >= NCSI_Timestamp and Download_Timestamp Detect connectivity to Storm-2945 infrastructure
The following query checks for connectivity to Storm-2945 infrastructure observed in this attack activity.
let target_domains = dynamic(["ms365-device.com", "ms365-live.com", "m365-owa.com", "owa-ms365.com"]);
let target_ips = dynamic(["31.57.243.154", "38.146.28.75", "38.146.28.132", "104.194.159.150", "107.189.26.194", "213.145.86.112"]);
DeviceNetworkEvents
| where RemoteUrl has_any(target_domains) or RemoteIP in (target_ips)
| project
Timestamp,
DeviceName,
DeviceId,
RemoteUrl,
RemoteIP,
LocalIP,
InitiatingProcessFileName,
InitiatingProcessCommandLine,
AccountName = InitiatingProcessAccountName,
ReportId
Detect CornFlake RAT presence on affected systems
The following query checks for the presence of the CornFlake RAT binary.
DeviceProcessEvents | where FolderPath == "%APPDATA%\\svchost32\\svchost32.exe" or FolderPath endswith @"\svchost32\svchost32.exe" | project Timestamp, DeviceName, DeviceId, FileName, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine, AccountName, ReportId
Detect CornFlake RAT Windows service registration
The following query checks for the CornFlake RAT Windows service registration.
DeviceRegistryEvents
| where RegistryKey has @"\SYSTEM\CurrentControlSet\Services\svchost32"
| where ActionType == "RegistryValueSet"
| where (RegistryValueName == "DisplayName" and RegistryValueData == "Cloud Sync Service")
or (RegistryValueName == "Description" and RegistryValueData == "Synchronizes files with the cloud storage provider")
| project
Timestamp,
DeviceName,
DeviceId,
RegistryKey,
RegistryValueName,
RegistryValueData,
ActionType,
InitiatingProcessFileName,
InitiatingProcessCommandLine,
InitiatingProcessAccountName,
ReportId
Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.
Detect network IP and domain indicators of compromise using ASIM
The following query checks IP addresses and domain IOCs across data sources supported by ASIM network session parser:
//IP list and domain list- _Im_NetworkSession let lookback = 30d; let ioc_ip_addr = dynamic(["213.145.86.112"]); let ioc_domains = dynamic(["213.145.86.112/t/pixel.gif", "213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "213.145.86.112/t/event"]); _Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now()) | where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains) | summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor
Detect web sessions IP and file hash indicators of compromise using ASIM
The following query checks IP addresses, domains, and file hash IOCs across data sources supported by ASIM web session parser:
//IP list - _Im_WebSession let lookback = 30d; let ioc_ip_addr = dynamic(["213.145.86.112"]); let ioc_sha_hashes =dynamic([“918fa52ae45ed60ba7cc8bdc99c3cbe9ab92e0375ec31fc05d0d4513be11c593”, “be99857449d2856dd5a84e21c8a3d5e0e01456adb44062ddec5a6b4970d8d42c”]); _Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now()) | where DstIpAddr in (ioc_ip_addr) or FileSHA256 in (ioc_sha_hashes) | summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor
Detect domain and URL indicators of compromise using ASIM
The following query checks domain and URL IOCs across data sources supported by ASIM web session parser:
// file hash list - imFileEvent // Domain list - _Im_WebSession let ioc_domains = dynamic(["https://213.145.86.112/t/pixel.gif", "https://213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "https://213.145.86.112/t/event"]); _Im_WebSession (url_has_any = ioc_domains)
ChocoShell C2 communications
The following query detects ChocoShell communications with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel.
let lookback = 30d; let ioc_url_artifacts = dynamic(["/t/pixel.gif?m="]); _Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now()) | where DstDomain in (ioc_url_artifacts) | summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated), EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor
| Indicator | Type | Description | First seen |
| ms365-device[.]com | Domain | CaptiveCrunch DCF redirect | 2026-07-23 |
| ms365-live[.]com | Domain | CaptiveCrunch DCF redirect | 2026-05-14 |
| m365-owa[.]com | Domain | CaptiveCrunch AitM infrastructure | 2026-07-20 |
| owa-ms365[.]com | Domain | CaptiveCrunch AitM infrastructure | 2026-07-16 |
| 31.57.243[.]154 | IP address | CaptiveCrunch AitM infrastructure | 2026-07-16 |
| 38.146.28[.]75 | IP address | CaptiveCrunch AitM infrastructure | 2026-07-01 |
| 38.146.28[.]132 | IP address | CaptiveCrunch DNS Resolver | 2026-07-15 |
| 104.194.159[.]150 | IP address | CaptiveCrunch AitM infrastructure | 2026-04-28 |
| 107.189.26[.]194 | IP address | ChocoShell C2 / CaptiveCrunch DNS Resolver | 2026-02-27 |
| 213.145.86[.]112 | IP address | ChocoShell C2 | 2026-07-01 |
| 918fa52ae45ed60ba7cc8bdc99c3cbe9ab92e0375ec31fc05d0d4513be11c593 | File hash | CornFlake | 2026-07-03 |
| be99857449d2856dd5a84e21c8a3d5e0e01456adb44062ddec5a6b4970d8d42c | File hash | ChocoShell | 2026-07-10 |
For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.
To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.
To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.
The post CaptiveCrunch: Midnight Blizzard targets travelers worldwide for malware delivery and credential theft appeared first on Microsoft Security Blog.
The second quarter of 2026 (April–June) was largely defined by the continuing downstream effects following Microsoft’s Digital Crimes Unit-led disruption efforts against the Tycoon2FA phishing-as-a-service (PhaaS) platform in March. Phishing volume linked to the platform fell 92% from pre-disruption averages, including QR code phishing and CAPTCHA-gated phishing both declining from their March highs. Despite ongoing efforts to rebuild operations, Tycoon2FA did not recover its previous scale or influence during Q2, and no single service emerged to replace the platform at comparable scale.
These trends reflect both the measurable impact that disruption operations can have on phishing ecosystems and the adaptability of threat actors as they diversify delivery channels. At the same time, Microsoft Threat Intelligence observed continued growth in Teams-based social engineering, particularly voice phishing (vishing), with weekly malicious call attempts reaching nearly ten times the mid-2025 baseline by the end of the quarter. This activity illustrates how threat actors continue to expand beyond email into trusted workplace communication platforms where communications may appear more trustworthy to users.
Microsoft detected approximately 7.6 billion email-based phishing threats throughout the quarter, with monthly volumes declining modestly from 2.7 billion in April to 2.4 billion in June. Credential phishing remained the dominant objective behind malicious payloads, while business email compromise (BEC) activity largely returned to historical norms after a brief, anomalous surge in April. Notable campaigns observed during the quarter also demonstrated how threat actors combine automation, trusted services, and multi-stage delivery chains to scale operations. These campaigns ranged from an automated BEC campaign that reached more than 67,000 users across 42,000 organizations in under three hours, to a multi-stage phishing campaign that used nested EML files, calendar invitations, and a Microsoft authentication redirect to deliver malware.
April phishing campaign tactics, detections, and mitigations ›
This blog provides a view of email threat activity across the second quarter of 2026, highlighting key trends in phishing techniques, payload delivery, and threat actor behavior observed by Microsoft Threat Intelligence. We examine shifts in QR code and CAPTCHA-gated phishing activity, malicious payload trends, BEC activity, the growth of Teams-based threats, and notable campaigns observed during the quarter. We also provide recommendations and Microsoft Defender detections to help organizations identify and mitigate evolving threats while prioritizing defensive measures.
The disruption operation that Microsoft’s Digital Crimes Unit launched against Tycoon2FA infrastructure in early March continued to produce measurable results throughout Q2 2026. After falling 15% in March and another 22% in April, Tycoon2FA-linked phishing volume dropped 74% in May to just 1.5 million messages, then fell another 20% in June to 1.2 million, by far the lowest monthly volumes observed in at least a year. For reference, the average monthly volume of phishing messages linked to Tycoon2FA during the second half of 2025 was 15.1 million. By the end of Q2, volumes were running at roughly 8% of that baseline, representing a 92% total decline since the disruption operation began.
Tycoon2FA’s influence across two primary phishing tactics, QR code lures and CAPTCHA-gated landing pages, also continued to decline throughout the quarter:
These declines indicate that the platform’s customer base has not migrated to replacement infrastructure at anything close to the scale they previously operated.
After being forced off Cloudflare, which had provided anti-analysis protection that made Tycoon2FA pages harder to scan and take down, the service continued to rely on infrastructure hosted on the .RU top-level domain (TLD), a shift that began in late March. More than 40% of newly observed Tycoon2FA domains used .RU registrations throughout Q2. While this reflects an ongoing effort to find replacement hosting, Tycoon2FA’s role in the phishing ecosystem has nonetheless been significantly diminished and the pace of recovery has been slow.
After peaking at 18.7 million attacks in March, the highest monthly volume in at least a year, QR code phishing declined for three consecutive months in Q2. Volume fell 7% in April to 17.4 million, then dropped more sharply in May (-38%) and June (-22%), closing the quarter at 8.3 million attacks. By June, QR code phishing had returned to levels last seen in mid-2025.
The delivery methods used in QR code attacks shifted notably during Q2. PDF attachments remained the dominant vehicle throughout, but their dominance weakened after April:
After accumulating to nearly 12 million attacks in March, the highest monthly volume observed over the past year, CAPTCHA-gated phishing declined sharply throughout Q2. Volume fell 32% in April to 8.2 million, then dropped another 65% in May and 24% in June, closing the quarter at just 2.2 million attacks. Since the March peak, CAPTCHA-gated phishing has fallen more than 81%, reaching its lowest monthly volume in more than a year.
The rapid rotation of delivery methods that characterized Q1 continued into Q2, with no single payload type maintaining the top position for more than one or two months:
Tycoon2FA’s continued decline was a significant factor in the overall volume reduction. The platform’s share of CAPTCHA-gated phishing fell from 41% in March to 16% in April, 18% in May, and 12% by June, down from a peak of 76% in December 2025. No single service has emerged to fill the gap at comparable scale, contributing to the sustained decline in CAPTCHA-gated phishing activity overall.
Credential phishing continued to dominate the malicious payload landscape throughout Q2, accounting for 94–96% of all payload-based attacks each month. These credential phishing payloads either linked users to phishing pages or locally loaded spoofed sign-in screens on a user’s device. Traditional malware delivery represented just 4–6% of payloads, consistent with its long-term decline.
HTML and PDF attachments remained the two most common malicious payload types across the quarter, together accounting for roughly 60–70% of all payload-based attacks each month:
April 2026 produced the most anomalous BEC data point in more than a year: nearly 9 million attacks, a 121% increase from March and more than double any previous month. The spike was short-lived as volume fell 62% in May to 3.4 million and settled at 3.9 million in June, both figures consistent with the monthly baseline that had held throughout the prior year. The April surge appeared to be driven by a small number of high-volume campaigns rather than a fundamental escalation in BEC activity.
The composition of BEC attacks remained consistent throughout Q2. Generic outreach messages (like “Are you at your desk?”) accounted for 87–92% of initial contact emails each month, while explicit requests for specific financial transactions or documents represented just 3–8%. This pattern underscores that BEC operators overwhelmingly favor establishing conversational rapport with targets before making fraudulent requests, rather than leading with direct financial asks.
Within the smaller subset of explicit financial requests, the most notable trend was the near-disappearance of fake invoice payment requests:
While email remains the dominant initial access vector, threat actors increasingly abused Microsoft Teams during Q2 to deliver social engineering, phishing, and malware payloads. Unlike email, Teams traffic typically bypasses secure email gateways and benefits from the perceived legitimacy of a colleague-initiated chat, which can make lures particularly effective in this environment.
Teams-based phishing volume climbed steadily throughout Q2, with the average number of detected attacks rising 19% from March to April, holding roughly flat into May (+1%), then increasing another 10% into June. Financial and executive impersonation has remained largely absent from Teams-based attacks over the past several months.
The dominant lure theme remained technical support impersonation, with attackers posing as an employee’s information technology (IT) help desk, typically warning of an impending account lockout. However, the way attackers presented themselves continued to evolve:
Vishing through Teams showed the steepest growth of any threat category tracked in this report during Q2. Average weekly malicious call attempts rose 31% from April to May and another 27% into June, with the final two weeks of June recording the two highest weekly volumes on record. Since the beginning of 2026, weekly vishing attempts have increased roughly 80% and now run at nearly ten times the mid-2025 baseline. Attackers time these calls deliberately when targets are most likely to be online and active, with the heaviest activity falling between 14:00 and 20:00 UTC, Monday through Friday, with near-zero weekend activity. Notably, a growing share of these calls go unanswered, end quickly, or are rejected outright, partly reflecting Microsoft’s ongoing efforts to harden the Teams attack surface and improve protections against social engineering abuse.
The following campaigns were observed during the quarter and highlight notable credential phishing, BEC, and malware delivery activity. For analysis of a separate code of conduct-themed credential phishing campaign observed in April of Q2, see Breaking the code: Multi-stage ‘code of conduct’ phishing campaign leads to AiTM token compromise.
On June 1, 2026, Microsoft Defender Research observed a high-volume BEC campaign that used automation to operate at scale. Over a send window of under three hours (14:08–16:52 UTC), the actor reached more than 67,000 users across more than 42,000 organizations, almost exclusively in the United States. Targeting spanned a broad range of industries rather than a single vertical, most notably retail and consumer goods (17%), technology and software (15%), and financial services (14%). The campaign ran two lures in succession from shared infrastructure: arequest impersonating sales executives to obtain aging report data and customer contact details, and a payroll diversion pretext impersonating the CEO or President to redirect salary payments to attacker-controlled bank accounts.
Delivery was fully scripted. The messages were generated programmatically using Python’s email.mime library, identifiable from its default MIME boundary format (===============[integer]==), and dispatched through the Amazon Simple Email Service (SES) API rather than a manual webmail interface, as indicated by the SES Feedback-ID and Message-ID formats. This allowed the actor to iterate through a recipient list and inject per-message variables (like spoofed executive display names, recipient addresses, and unique tracking identifiers) at volume. Messages were sent from a DomainKeys Identified Mail (DKIM)-configured Slovak domain (ecajovna[.]sk) through SES, so they passed Sender Policy Framework (SPF) and achieved DKIM alignment. Neither lure contained a malicious link or attachment; both relied on eliciting a reply to attacker-controlled mailboxes that mimicked legitimate providers (ilyff[.]com, j-gmails[.]com, x2mails[.]com).
Automation also extended to targeting and follow-up. The actor addressed generic role-based mailboxes (like “ar”, “accountsreceivable”, “hr”, “payroll”) rather than named individuals, reducing per-target effort. Each message embedded a 1×1 open-tracking pixel served from an Amazon SES engagement subdomain, with per-message identifiers that let the actor confirm which recipients opened the email and prioritize follow-up against those targets. The combination of scripted message generation, API-based bulk delivery, role-based targeting, and automated engagement tracking allowed a single actor to run a personalized, financially motivated BEC operation at a scale not practical to execute manually.
Between June 14–15, 2026, Microsoft Defender Research observed a phishing campaign targeting more than 107,000 users across nearly 19,000 organizations, almost exclusively in the United States. The campaign targeted a broad range of industries rather than a single vertical, most notably financial services (17%), technology and software (14%), and retail and consumer goods (14%). Emails impersonated an internal “Internal Affairs – Financials & Staff Updates” function at the recipient’s own organization, with the display name and subject line both opening with the recipient’s organization name and closing with constant trailing text. The messages were sent from a Postfix host on 9i6pokerdepot[.]com routed through Barracuda’s outbound mail service, and DKIM passed cleanly for the sending domain.
The visible email body contained minimal content. One line told the reader to download the attached file for the meeting summary, followed by a confidentiality notice. Each message carried two attachments: a nested EML posing as a Teams archive recording, and an ICS calendar invite addressed to placeholder administrative accounts at the recipient’s domain. The nested EML’s file name retained an unfilled template token ( {{DATE2}} ), indicating a per-recipient templating tool.
When opened, the EML displayed a voicemail notification with a single action button. That button pointed to Microsoft’s OAuth sign-in endpoint at login.microsoftonline[.]com, with parameters that asked for a silent sign-in attempt against an Entra application that the attacker had registered as multi-tenant.
Because no active sign-in session could satisfy the silent request, Microsoft’s authentication service redirected the recipient to the destination the attacker had pre-registered on the application. That destination was a path on clickup-attachments[.]com, ClickUp’s public attachment host, and served a Windows batch file named Financial_report.bat. Because the link routed through Microsoft authentication infrastructure, both recipients and URL scanners saw a login.microsoftonline[.]com link.
The batch file ran a hidden PowerShell command that pulled installer.exe from pixeldrain[.]com, saved it under the user’s Temp directory, ran it with a silent flag, and deleted the dropper on exit. Rather than stealing credentials, the campaign ultimately resulted in silent malware execution on the user’s Windows device.
Microsoft recommends the following mitigations to reduce the impact of this threat. Check the recommendations card for the deployment status of monitored mitigations.
Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.
The following alert might indicate threat activity associated with this threat. The alert, however, can be triggered by unrelated threat activity.
The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity.
Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.
Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:
Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.
Microsoft Defender XDR customers can use the following Threat Analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.
Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.
| Indicator | Type | Description | First seen | Last seen |
| 9i6pokerdepot[.]com | Domain | Sending domain; DKIM-signed by the operator | 2026-06-15 | 2026-06-15 |
| Customer.Service[@]9i6pokerdepot[.]com | Email address | Campaign sender address | 2026-06-15 | 2026-06-15 |
| t90141296286.p.clickup-attachments[.]com | Domain | ClickUp attachment subdomain hosting the stage 2 BAT dropper | 2026-06-15 | 2026-06-15 |
| hxxps://t90141296286.p.clickup-attachments[.]com/t90141296286/fb39c3a9-3161-40ad-847b-0683e0409d6f/Financial_report.bat | URL | Stage 2 BAT dropper download URL | 2026-06-15 | 2026-06-15 |
| hxxps://pixeldrain[.]com/api/file/3v92oJiL | URL | Final installer payload download URL | 2026-06-15 | 2026-06-15 |
| Re: Teams Archive Recording for {{DATE2}}.eml | File name | Nested EML attachment template name; the literal {{DATE2}} indicates an unfilled per-recipient template token | 2026-06-15 | 2026-06-15 |
| Financial_report.bat | File name | Stage 2 dropper batch file delivered from the OAuth error redirect | 2026-06-15 | 2026-06-15 |
| ecajovna[.]sk | Domain | Domain used to send campaign emails | 2026-06-01 | 2026-06-01 |
| ilyff[.]com | Domain | Reply-to domain used to receive victim responses | 2026-06-01 | 2026-06-01 |
| j-gmails[.]com | Domain | Reply-to domain used to receive victim responses | 2026-06-01 | 2026-06-01 |
| x2mails[.]com | Domain | Reply-to domain used to receive victim responses | 2026-06-01 | 2026-06-01 |
| contact[@]ecajovna[.]sk | Email address | Address used to send campaign emails | 2026-06-01 | 2026-06-01 |
| mail[@]ilyff[.]com | Email address | Reply-to address | 2026-06-01 | 2026-06-01 |
| me[@]j-gmails[.]com | Email address | Reply-to address | 2026-06-01 | 2026-06-01 |
| me[@]x2mails[.]com | Email address | Reply-to address | 2026-06-01 | 2026-06-01 |
| compliance-protectionoutlook[.]de | Domain | Domain hosting malicious campaign content | 2026-04-14 | 2026-04-16 |
| acceptable-use-policy-calendly[.]de | Domain | Domain hosting malicious campaign content | 2026-04-14 | 2026-04-16 |
| cocinternal[.]com | Domain | Domain hosting sender email address | 2026-04-14 | 2026-04-16 |
| gadellinet[.]com | Domain | Domain hosting sender email address | 2026-04-14 | 2026-04-16 |
| harteprn[.]com | Domain | Domain hosting sender email address | 2026-04-14 | 2026-04-16 |
| cocpostmaster[@]cocinternal[.]cm | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| nationaladmin[@]gadellinet[.]com | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| nationalintegrity[@]harteprn[.]com | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| m365premiumcommunications[@]cocinternal[.]com | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| documentviewer[@]na[.]businesshellosign[.]de | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| 5DB1ECBBB2C90C51D81BDA138D4300B90EA5EB2885CCE1BD921D692214AECBC6 | SHA-256 | File hash of campaign PDF attachment | 2026-04-14 | 2026-04-16 |
| B5A3346082AC566B4494E6175F1CD9873B64ABE6C902DB49BD4E8088876C9EAD | SHA-256 | File hash of campaign PDF attachment | 2026-04-14 | 2026-04-16 |
| 11420D6D693BF8B19195E6B98FEDD03B9BCBC770B6988BC64CB788BFABE1A49D | SHA-256 | File hash of campaign PDF attachment | 2026-04-14 | 2026-04-16 |
For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.
To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.
To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.
The post Email threat landscape: Q2 2026 trends and insights appeared first on Microsoft Security Blog.
The second quarter of 2026 (April–June) was largely defined by the continuing downstream effects following Microsoft’s Digital Crimes Unit-led disruption efforts against the Tycoon2FA phishing-as-a-service (PhaaS) platform in March. Phishing volume linked to the platform fell 92% from pre-disruption averages, including QR code phishing and CAPTCHA-gated phishing both declining from their March highs. Despite ongoing efforts to rebuild operations, Tycoon2FA did not recover its previous scale or influence during Q2, and no single service emerged to replace the platform at comparable scale.
These trends reflect both the measurable impact that disruption operations can have on phishing ecosystems and the adaptability of threat actors as they diversify delivery channels. At the same time, Microsoft Threat Intelligence observed continued growth in Teams-based social engineering, particularly voice phishing (vishing), with weekly malicious call attempts reaching nearly ten times the mid-2025 baseline by the end of the quarter. This activity illustrates how threat actors continue to expand beyond email into trusted workplace communication platforms where communications may appear more trustworthy to users.
Microsoft detected approximately 7.6 billion email-based phishing threats throughout the quarter, with monthly volumes declining modestly from 2.7 billion in April to 2.4 billion in June. Credential phishing remained the dominant objective behind malicious payloads, while business email compromise (BEC) activity largely returned to historical norms after a brief, anomalous surge in April. Notable campaigns observed during the quarter also demonstrated how threat actors combine automation, trusted services, and multi-stage delivery chains to scale operations. These campaigns ranged from an automated BEC campaign that reached more than 67,000 users across 42,000 organizations in under three hours, to a multi-stage phishing campaign that used nested EML files, calendar invitations, and a Microsoft authentication redirect to deliver malware.
April phishing campaign tactics, detections, and mitigations ›
This blog provides a view of email threat activity across the second quarter of 2026, highlighting key trends in phishing techniques, payload delivery, and threat actor behavior observed by Microsoft Threat Intelligence. We examine shifts in QR code and CAPTCHA-gated phishing activity, malicious payload trends, BEC activity, the growth of Teams-based threats, and notable campaigns observed during the quarter. We also provide recommendations and Microsoft Defender detections to help organizations identify and mitigate evolving threats while prioritizing defensive measures.
The disruption operation that Microsoft’s Digital Crimes Unit launched against Tycoon2FA infrastructure in early March continued to produce measurable results throughout Q2 2026. After falling 15% in March and another 22% in April, Tycoon2FA-linked phishing volume dropped 74% in May to just 1.5 million messages, then fell another 20% in June to 1.2 million, by far the lowest monthly volumes observed in at least a year. For reference, the average monthly volume of phishing messages linked to Tycoon2FA during the second half of 2025 was 15.1 million. By the end of Q2, volumes were running at roughly 8% of that baseline, representing a 92% total decline since the disruption operation began.
Tycoon2FA’s influence across two primary phishing tactics, QR code lures and CAPTCHA-gated landing pages, also continued to decline throughout the quarter:
These declines indicate that the platform’s customer base has not migrated to replacement infrastructure at anything close to the scale they previously operated.
After being forced off Cloudflare, which had provided anti-analysis protection that made Tycoon2FA pages harder to scan and take down, the service continued to rely on infrastructure hosted on the .RU top-level domain (TLD), a shift that began in late March. More than 40% of newly observed Tycoon2FA domains used .RU registrations throughout Q2. While this reflects an ongoing effort to find replacement hosting, Tycoon2FA’s role in the phishing ecosystem has nonetheless been significantly diminished and the pace of recovery has been slow.
After peaking at 18.7 million attacks in March, the highest monthly volume in at least a year, QR code phishing declined for three consecutive months in Q2. Volume fell 7% in April to 17.4 million, then dropped more sharply in May (-38%) and June (-22%), closing the quarter at 8.3 million attacks. By June, QR code phishing had returned to levels last seen in mid-2025.
The delivery methods used in QR code attacks shifted notably during Q2. PDF attachments remained the dominant vehicle throughout, but their dominance weakened after April:
After accumulating to nearly 12 million attacks in March, the highest monthly volume observed over the past year, CAPTCHA-gated phishing declined sharply throughout Q2. Volume fell 32% in April to 8.2 million, then dropped another 65% in May and 24% in June, closing the quarter at just 2.2 million attacks. Since the March peak, CAPTCHA-gated phishing has fallen more than 81%, reaching its lowest monthly volume in more than a year.
The rapid rotation of delivery methods that characterized Q1 continued into Q2, with no single payload type maintaining the top position for more than one or two months:
Tycoon2FA’s continued decline was a significant factor in the overall volume reduction. The platform’s share of CAPTCHA-gated phishing fell from 41% in March to 16% in April, 18% in May, and 12% by June, down from a peak of 76% in December 2025. No single service has emerged to fill the gap at comparable scale, contributing to the sustained decline in CAPTCHA-gated phishing activity overall.
Credential phishing continued to dominate the malicious payload landscape throughout Q2, accounting for 94–96% of all payload-based attacks each month. These credential phishing payloads either linked users to phishing pages or locally loaded spoofed sign-in screens on a user’s device. Traditional malware delivery represented just 4–6% of payloads, consistent with its long-term decline.
HTML and PDF attachments remained the two most common malicious payload types across the quarter, together accounting for roughly 60–70% of all payload-based attacks each month:
April 2026 produced the most anomalous BEC data point in more than a year: nearly 9 million attacks, a 121% increase from March and more than double any previous month. The spike was short-lived as volume fell 62% in May to 3.4 million and settled at 3.9 million in June, both figures consistent with the monthly baseline that had held throughout the prior year. The April surge appeared to be driven by a small number of high-volume campaigns rather than a fundamental escalation in BEC activity.
The composition of BEC attacks remained consistent throughout Q2. Generic outreach messages (like “Are you at your desk?”) accounted for 87–92% of initial contact emails each month, while explicit requests for specific financial transactions or documents represented just 3–8%. This pattern underscores that BEC operators overwhelmingly favor establishing conversational rapport with targets before making fraudulent requests, rather than leading with direct financial asks.
Within the smaller subset of explicit financial requests, the most notable trend was the near-disappearance of fake invoice payment requests:
While email remains the dominant initial access vector, threat actors increasingly abused Microsoft Teams during Q2 to deliver social engineering, phishing, and malware payloads. Unlike email, Teams traffic typically bypasses secure email gateways and benefits from the perceived legitimacy of a colleague-initiated chat, which can make lures particularly effective in this environment.
Teams-based phishing volume climbed steadily throughout Q2, with the average number of detected attacks rising 19% from March to April, holding roughly flat into May (+1%), then increasing another 10% into June. Financial and executive impersonation has remained largely absent from Teams-based attacks over the past several months.
The dominant lure theme remained technical support impersonation, with attackers posing as an employee’s information technology (IT) help desk, typically warning of an impending account lockout. However, the way attackers presented themselves continued to evolve:
Vishing through Teams showed the steepest growth of any threat category tracked in this report during Q2. Average weekly malicious call attempts rose 31% from April to May and another 27% into June, with the final two weeks of June recording the two highest weekly volumes on record. Since the beginning of 2026, weekly vishing attempts have increased roughly 80% and now run at nearly ten times the mid-2025 baseline. Attackers time these calls deliberately when targets are most likely to be online and active, with the heaviest activity falling between 14:00 and 20:00 UTC, Monday through Friday, with near-zero weekend activity. Notably, a growing share of these calls go unanswered, end quickly, or are rejected outright, partly reflecting Microsoft’s ongoing efforts to harden the Teams attack surface and improve protections against social engineering abuse.
The following campaigns were observed during the quarter and highlight notable credential phishing, BEC, and malware delivery activity. For analysis of a separate code of conduct-themed credential phishing campaign observed in April of Q2, see Breaking the code: Multi-stage ‘code of conduct’ phishing campaign leads to AiTM token compromise.
On June 1, 2026, Microsoft Defender Research observed a high-volume BEC campaign that used automation to operate at scale. Over a send window of under three hours (14:08–16:52 UTC), the actor reached more than 67,000 users across more than 42,000 organizations, almost exclusively in the United States. Targeting spanned a broad range of industries rather than a single vertical, most notably retail and consumer goods (17%), technology and software (15%), and financial services (14%). The campaign ran two lures in succession from shared infrastructure: arequest impersonating sales executives to obtain aging report data and customer contact details, and a payroll diversion pretext impersonating the CEO or President to redirect salary payments to attacker-controlled bank accounts.
Delivery was fully scripted. The messages were generated programmatically using Python’s email.mime library, identifiable from its default MIME boundary format (===============[integer]==), and dispatched through the Amazon Simple Email Service (SES) API rather than a manual webmail interface, as indicated by the SES Feedback-ID and Message-ID formats. This allowed the actor to iterate through a recipient list and inject per-message variables (like spoofed executive display names, recipient addresses, and unique tracking identifiers) at volume. Messages were sent from a DomainKeys Identified Mail (DKIM)-configured Slovak domain (ecajovna[.]sk) through SES, so they passed Sender Policy Framework (SPF) and achieved DKIM alignment. Neither lure contained a malicious link or attachment; both relied on eliciting a reply to attacker-controlled mailboxes that mimicked legitimate providers (ilyff[.]com, j-gmails[.]com, x2mails[.]com).
Automation also extended to targeting and follow-up. The actor addressed generic role-based mailboxes (like “ar”, “accountsreceivable”, “hr”, “payroll”) rather than named individuals, reducing per-target effort. Each message embedded a 1×1 open-tracking pixel served from an Amazon SES engagement subdomain, with per-message identifiers that let the actor confirm which recipients opened the email and prioritize follow-up against those targets. The combination of scripted message generation, API-based bulk delivery, role-based targeting, and automated engagement tracking allowed a single actor to run a personalized, financially motivated BEC operation at a scale not practical to execute manually.
Between June 14–15, 2026, Microsoft Defender Research observed a phishing campaign targeting more than 107,000 users across nearly 19,000 organizations, almost exclusively in the United States. The campaign targeted a broad range of industries rather than a single vertical, most notably financial services (17%), technology and software (14%), and retail and consumer goods (14%). Emails impersonated an internal “Internal Affairs – Financials & Staff Updates” function at the recipient’s own organization, with the display name and subject line both opening with the recipient’s organization name and closing with constant trailing text. The messages were sent from a Postfix host on 9i6pokerdepot[.]com routed through Barracuda’s outbound mail service, and DKIM passed cleanly for the sending domain.
The visible email body contained minimal content. One line told the reader to download the attached file for the meeting summary, followed by a confidentiality notice. Each message carried two attachments: a nested EML posing as a Teams archive recording, and an ICS calendar invite addressed to placeholder administrative accounts at the recipient’s domain. The nested EML’s file name retained an unfilled template token ( {{DATE2}} ), indicating a per-recipient templating tool.
When opened, the EML displayed a voicemail notification with a single action button. That button pointed to Microsoft’s OAuth sign-in endpoint at login.microsoftonline[.]com, with parameters that asked for a silent sign-in attempt against an Entra application that the attacker had registered as multi-tenant.
Because no active sign-in session could satisfy the silent request, Microsoft’s authentication service redirected the recipient to the destination the attacker had pre-registered on the application. That destination was a path on clickup-attachments[.]com, ClickUp’s public attachment host, and served a Windows batch file named Financial_report.bat. Because the link routed through Microsoft authentication infrastructure, both recipients and URL scanners saw a login.microsoftonline[.]com link.
The batch file ran a hidden PowerShell command that pulled installer.exe from pixeldrain[.]com, saved it under the user’s Temp directory, ran it with a silent flag, and deleted the dropper on exit. Rather than stealing credentials, the campaign ultimately resulted in silent malware execution on the user’s Windows device.
Microsoft recommends the following mitigations to reduce the impact of this threat. Check the recommendations card for the deployment status of monitored mitigations.
Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.
The following alert might indicate threat activity associated with this threat. The alert, however, can be triggered by unrelated threat activity.
The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity.
Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.
Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:
Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.
Microsoft Defender XDR customers can use the following Threat Analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.
Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.
| Indicator | Type | Description | First seen | Last seen |
| 9i6pokerdepot[.]com | Domain | Sending domain; DKIM-signed by the operator | 2026-06-15 | 2026-06-15 |
| Customer.Service[@]9i6pokerdepot[.]com | Email address | Campaign sender address | 2026-06-15 | 2026-06-15 |
| t90141296286.p.clickup-attachments[.]com | Domain | ClickUp attachment subdomain hosting the stage 2 BAT dropper | 2026-06-15 | 2026-06-15 |
| hxxps://t90141296286.p.clickup-attachments[.]com/t90141296286/fb39c3a9-3161-40ad-847b-0683e0409d6f/Financial_report.bat | URL | Stage 2 BAT dropper download URL | 2026-06-15 | 2026-06-15 |
| hxxps://pixeldrain[.]com/api/file/3v92oJiL | URL | Final installer payload download URL | 2026-06-15 | 2026-06-15 |
| Re: Teams Archive Recording for {{DATE2}}.eml | File name | Nested EML attachment template name; the literal {{DATE2}} indicates an unfilled per-recipient template token | 2026-06-15 | 2026-06-15 |
| Financial_report.bat | File name | Stage 2 dropper batch file delivered from the OAuth error redirect | 2026-06-15 | 2026-06-15 |
| ecajovna[.]sk | Domain | Domain used to send campaign emails | 2026-06-01 | 2026-06-01 |
| ilyff[.]com | Domain | Reply-to domain used to receive victim responses | 2026-06-01 | 2026-06-01 |
| j-gmails[.]com | Domain | Reply-to domain used to receive victim responses | 2026-06-01 | 2026-06-01 |
| x2mails[.]com | Domain | Reply-to domain used to receive victim responses | 2026-06-01 | 2026-06-01 |
| contact[@]ecajovna[.]sk | Email address | Address used to send campaign emails | 2026-06-01 | 2026-06-01 |
| mail[@]ilyff[.]com | Email address | Reply-to address | 2026-06-01 | 2026-06-01 |
| me[@]j-gmails[.]com | Email address | Reply-to address | 2026-06-01 | 2026-06-01 |
| me[@]x2mails[.]com | Email address | Reply-to address | 2026-06-01 | 2026-06-01 |
| compliance-protectionoutlook[.]de | Domain | Domain hosting malicious campaign content | 2026-04-14 | 2026-04-16 |
| acceptable-use-policy-calendly[.]de | Domain | Domain hosting malicious campaign content | 2026-04-14 | 2026-04-16 |
| cocinternal[.]com | Domain | Domain hosting sender email address | 2026-04-14 | 2026-04-16 |
| gadellinet[.]com | Domain | Domain hosting sender email address | 2026-04-14 | 2026-04-16 |
| harteprn[.]com | Domain | Domain hosting sender email address | 2026-04-14 | 2026-04-16 |
| cocpostmaster[@]cocinternal[.]cm | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| nationaladmin[@]gadellinet[.]com | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| nationalintegrity[@]harteprn[.]com | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| m365premiumcommunications[@]cocinternal[.]com | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| documentviewer[@]na[.]businesshellosign[.]de | Email address | Email address used to send campaign emails | 2026-04-14 | 2026-04-16 |
| 5DB1ECBBB2C90C51D81BDA138D4300B90EA5EB2885CCE1BD921D692214AECBC6 | SHA-256 | File hash of campaign PDF attachment | 2026-04-14 | 2026-04-16 |
| B5A3346082AC566B4494E6175F1CD9873B64ABE6C902DB49BD4E8088876C9EAD | SHA-256 | File hash of campaign PDF attachment | 2026-04-14 | 2026-04-16 |
| 11420D6D693BF8B19195E6B98FEDD03B9BCBC770B6988BC64CB788BFABE1A49D | SHA-256 | File hash of campaign PDF attachment | 2026-04-14 | 2026-04-16 |
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The post Email threat landscape: Q2 2026 trends and insights appeared first on Microsoft Security Blog.
A 19-year-old alleged member of the Scattered Spider extortion crew was extradited to the United States last week and remains in federal custody awaiting several cybercrime charges, the Justice Department said Wednesday.
Peter Stokes, a dual citizen of the United States and Estonia, was allegedly involved in Scattered Spider since it formed in 2022 and boasted on social media about the luxurious globetrotting life he enjoyed while he was still a child.
The cybercrime ring of young, native English-speaking people has infiltrated more than 100 businesses since 2022, and extorted more than $100 million from its victims around the world, officials said.
“Scattered Spider has repeatedly targeted U.S. companies, extorting employees, inflicting millions of dollars in losses, and disrupting essential operations,” Brett Leatherman, assistant director of the FBI’s cyber division, said in a statement. “Through strong domestic and international partnerships, the FBI will continue to identify, disrupt, and hold cybercriminals accountable, no matter where they are located.”
Stokes, also known as “Bouquet” and “Jordan,” is accused of participating in multiple data theft and extortion attempts, but the FBI only provided specific details about some more recent attacks on a luxury jewelry retailer in May 2025 and a U.S.-based insurance company in June 2025.
Cybercrime researchers have been tracking Stokes’ online activity since 2022. Microsoft determined his true identity and implicated Stokes as a member of Scattered Spider in a criminal referral in October 2024, according to court records.
He was still a child at that time, and authorities typically don’t arrest known cybercriminals until they reach adulthood. Stokes lived in Estonia and the United Arab Emirates while he allegedly committed some of his crimes.
Police arrested Stokes in Finland as he attempted to board an April 10 flight to Japan, possessing two hard drives containing allegedly incriminating evidence. He made an initial court appearance in Chicago Tuesday and was ordered to remain in jail.
Stokes exhibited an opulent life before his capture, according to his social media activity and State Department travel records. This included trips and multiple stays in luxury hotels in Paris, Italy, Spain, Germany, New York, Florida, New Mexico, Thailand and Dubai between 2024 and 2025, according to a criminal complaint filed against him in the U.S. District Court for the Northern District of Illinois.
He also posted images of watches, substantial cash and an apparently diamond-encrusted chain depicting the words “Hack the Planet.”
Officials also noted that Stokes’ family appeared to be well off, as his father was a previous executive in two major European companies.
Stokes was charged with conspiracy, cyber intrusion and fraud offenses.
“The malicious attacks from Scattered Spider caused widespread disruption to businesses and organizations throughout the United States,” Andrew Boutros, U.S. attorney for the Northern District of Illinois, said in a statement. “These charges underscore our unwavering commitment to keeping pace with technologically savvy criminal actors and holding accountable those who seek to profit from cyber intrusions, including those located in foreign jurisdictions who do harm to American businesses and victims.”
The post Alleged longstanding member of Scattered Spider extradited to US appeared first on CyberScoop.
