A Canadian man pleaded guilty to playing a central role in one of the most far-reaching cyberattacks of 2024 — the widespread compromise of more than 165 Snowflake customer environments, resulting in massive data theft for extortion, the Justice Department said Wednesday.
Connor Moucka earned $495,000 by extorting his victims, offering stolen data for sale online, and in one case re-extorted a victim with stolen data of a government official and members of a then-former government official’s immediate family, authorities said.
Moucka and his alleged co-conspirators John Binns and Cameron Wagenius stole billions of sensitive records and received more than $2.5 million in extortion payments combined, according to prosecutors. Victims of the attack spree included AT&T, Ticketmaster, Advance Auto Parts and Santander.
“Hiding behind a screen is no shield from justice,” Brett Leatherman, assistant director of the FBI’s Cyber Division, said in a statement. “Moucka learned that when he was arrested just months after he began targeting U.S. companies, stealing sensitive information, and extorting victims for millions of dollars.”
Authorities arrested Moucka relatively quickly because he caused significant damage, said Allison Nixon, chief research officer at Unit 221B.
“His gang went on a spree of maximizing harm, which directly correlated to maximizing the resources devoted to stopping it,” she said.
“His behavior was bizarre throughout. Even while stealing data and extorting victims, he did many unnecessary things like threatening me because he thought I was working on his case. I was not working on his case before he threatened me,” Nixon added.
Moucka, who used several aliases online, including “Waifu,” “Judische,” “Catist” and “Ellyel8,” was arrested Oct. 30, 2024, in Kitchener, a city in the Canadian province of Ontario, at the behest of U.S. authorities. He was extradited to the United States in March 2025.
Moucka and his co-conspirators used stolen credentials to access the data storage platform’s customers’ accounts en masse. Records of more than 100 million people were exposed by the data theft campaign, including call and text history records, banking and other financial information, payroll records, government ID numbers and other personally identifiable data.
Officials said victim companies bore more than $9.5 million in losses combined, not including losses attributable to their respective customers.
Moucka’s threats and re-extortion tactics were calculated and predatory, and his actions did real harm to his victims, be they companies targeted for theft and extortion or the millions of everyday people who are their customers,” W. Mike Herrington, special agent in charge of the FBI Seattle field office, said in a statement.
Researchers said Moucka and his co-conspirators are all associated with The Com, a sprawling cybercriminal network of minors and young adults who engage in violence, extortion, sextortion and various forms of cybercrime.
“His legacy is one of failure. He extorted and then scammed his victims by not deleting the data, casting doubt on all future pay-or-leak extortion gangs,” Nixon said.
“The pay-or-leak business model was popularized by him and his gang,” and his claims of data deletion were a lie, she added. “With copycat gangs, defenders grapple with the uncertainty of whether the threat actors are honest.”
Moucka pleaded guilty to computer fraud, wire fraud, aggravated identity theft and a related conspiracy. He is scheduled for sentencing Oct. 27 and faces up to 32 years in prison.
TeamPCP, the threat actor behind an unrelenting flurry of attacks on open-source software this year, has been active much longer than previously thought, according to research Oligo Security shared exclusively with CyberScoop.
The threat actor, which gained notoriety and has captivated threat hunters as it compromised and injected malicious code into more than 1,000 software packages in less than four months earlier this year, was also responsible for attacks dating back to 2020, Oligo Security found.
The security vendor’s research team found multiple attacks that bear the markings of TeamPCP, including a late 2025 campaign involving the exploitation of a ShadowRay vulnerability that resulted in the first self-propogating botnet running on hijacked AI infrastructure.
Evidence uncovered during that investigation into the ShadowRay 2.0 campaign was linked to more historical attacks originating from the same IPs, domains and other infrastructure TeamPCP used in attacks that captured widespread attention earlier this year.
“The scariest thing in this campaign is the speed at which the payloads evolved and changed and adapted to the environment they run in. We saw changes in the speed that we’re not used to seeing in these kinds of attacks. They’re usually slow, careful,” said Uri Katz, director of research at Oligo Security. “This was clearly with the help of AI — the payloads changed rapidly to adjust and change to the environment that they were trying to attack.”
One of the domains that Oligo Security identified in July 2025 was in the profile of TeamPCP’s official GitHub account, said Avi Lumelsky, AI security researcher at Oligo Security. “It’s public, they’re not even trying to hide their identity,” he said.
From there, Oligo linked TeamPCP to activity tracked under multiple names, including TA-NATALSTATUS and IronErn, spanning from 2020 to late 2025. Much of that activity was traced to the same IPs, domain names, a file server and command-and-control server, researchers said.
TeamPCP emerged publicly as a brand in late 2025. Soon after, “TeamPCP started to go really broad and do campaigns, which are much more noisy,” said Gal Elbaz, co-founder and CTO at Oligo Security.
Widespread adoption of AI and TeamPCP’s use of the technology supported this growth as the threat actor built a brand, got more active on social media and boasted publicly about its activities and claimed victims.
“The ability to control the infrastructure and orchestrate the attack with AI was also super new, and I’m sure it helps them,” Elbaz said.
“All of the companies in the world are in this race to adopt AI because they are afraid their business will die, and they understand, of course, the opportunity. But it’s also what gives the attacker this power to go into it,” he added. “If you don’t really have visibility in what’s going on there or how it behaves, that’s exactly what attackers are after.”
TeamPCP’s more recent attacks have capitalized on new security gaps created by developers’ increasing reliance on AI and the automated systems companies use to deploy code. The threat actor is also consistently wrecking the open-source frameworks and software packages these systems rely on.
“Most AI infrastructure is open source by design because nobody has the manpower and money to develop everything from scratch,” Lumelsky said.
“We love open source. We use many of these products ourselves, but it’s all about reading the documentation, and I think many of these tools place the responsibility of using it right and security on the user, and developers are not used to these new kinds of animals,” he added. “That’s why the trust can be exploited at scale.”
As it uncovered a long operational history spanning multiple campaigns, Oligo Security has gained more confidence in understanding how TeamPCP operates. It also means TeamPCP was likely involved in other attacks that haven’t been attributed to it yet or attacks that haven’t been detected.
“There’s a lot more out there that we haven’t caught or been able to prove up until now,” Elbaz said.
The UK’s AI Security Institute said that their AI research system took “unsanctioned” actions over the internet to engage in “sustained, potentially harmful activity directed at real people.”
According to a blog post and technical report released Tuesday, the organization noticed “unusual data transfers” leaving their research systems through the pseudo-anonymous Tor network on July 28. The models, which included Anthropic’s Mythos 5 and OpenAI’s GPT-5.6-Sol models, were being tested for their cybersecurity capabilities.
Like the OpenAI and Anthropic incidents before it, the offending agents were attempting to solve a challenge. On 10 of 122 runs taken by two models, they took a combined 19 malicious actions, including attempting to insert malicious code into a real open-source software project and creating fake online identities to contact human maintainers and press them to approve it.
It also inserted malicious prompt injection instructions in places “where it reasoned that other automated AI systems might pick them up and execute them.” Sometimes multiple agents would collaborate on a task, with one model leaving public messages or notes for the other on GitHub.
However, AISI said their incident differs in one critical way.
“Importantly, this was not a case of a model escaping its secure test environment, or ‘sandbox,’” the institute wrote in an unsigned blog. “As was standard in our cyber testing, we had intentionally permitted internet access, and model-provider cyber classifiers were deliberately disabled – conditions that do not reflect how frontier models are made available to the public.”
The institute said that while their own design and evaluation choices “to some degree” enabled the malicious behavior, the models still displayed “novel, potentially deceptive behaviors” and were executed “to an extent and severity that we did not anticipate.”
The same day, OpenAI acknowledged AISI and another third-party cybersecurity tester, private firm Irregular, had recently reported incidents where their models exceeded “beyond their intended testing boundaries.”
That included GPT-5.6-Sol reusing GitHub tokens left by another agent to attempt to recover accounts and to access a DNS server that contained malicious payloads meant to exploit a software vulnerability.
The setup did not work, there is no evidence any real resolver queried it, and the infrastructure was removed when the evaluation ended,” the company wrote in an unsigned blog post Tuesday.
OpenAI said it would review its own third-party testing procedures to focus on higher risk evaluations, assess requests by third-parties to enable internet access, stop conditions and other features for their models.
The incident with Irregular occurred on July 29 during a Capture-the-Flag cybersecurity evaluation of OpenAI’s models. Due to a “misconfiguration” the models were allowed to access the public internet, where they encountered and exploited a real domain, mistakenly believing it was still in a test environment.
OpenAI said an investigation by Irregular is ongoing, but also found that the models had found and used credentials for the site at one point. The blog also references other additional potential cybersecurity incidents.
“Irregular has informed us that all of the issues identified pertaining to the incident are no longer active and relevant safeguards were added to the testing environment,” the blog said. “Irregular has also communicated about related incidents involving other labs from the same testing environment.”
CyberScoop has reached out to Irregular for comment.
The incidents were made public the same day that the White House met with Anthropic, Open AI and other frontier AI companies to preview a new framework for evaluating models before they’re released publicly. Some media outlets have reported that after an executive order, export controls and other actions, the administration does not plan to make the new framework public.
In less than four hours early Tuesday, an attacker compromised a GitHub maintainer account and unleashed a self-replicating piece of malware which injected malicious code into more than 440 distinct npm packages, according to multiple security firms.
The worm, built on the open-source Mini Shai-Hulud repository that TeamPCP published in May, was initially let loose in keyv, a data management interface software package with more than 600 million monthly downloads. The attacker spent the next 30 minutes compromising additional packages controlled by the same maintainer, including cacheable, flat-cache, file-entry-cache.
The attack spread to other maintainers, eventually compromising more than 860 packages with a “combined total of over 2 billion monthly installs,” Ilyas Makari, malware researcher at Aikido Security, wrote in a blog post.
Wiz researchers told CyberScoop it hasn’t observed any new malicious packages since the initial wave moved through a massive footpoint of cloud and code environments in those first four hours.
“This is the most critical initial compromise, with over 155 million weekly downloads on the root packages,” Wiz Research said in an email.
Some of the compromised packages, including keyv, flat-cache and file-entry-cache, are present in more than 46% of all cloud environments, according to Wiz. “By comparison, back in the Shai-Hulud 2.0 campaign the most prevalent packages were only in about 28% of environments,” the company said.
“Time will tell whether the eventual cost and impact outpaces past attacks, or whether adoption of hardening mechanisms such as package aging, and the usage of the relatively less aggressive Mini Shai-Hulud code as basis, will defray the final toll here,” Wiz Research added.
Researchers from multiple firms sprung into action to monitor the widening attack spree and published indicators of compromise to help potential victims hunt for malicious activity in their systems.
The Mini Shai-Hulud variant used in these attacks scoops up a trove of sensitive data, including npm, GitHub, AWS and continuous integration credentials. It also steals AI-related configuration files and cryptocurrency wallets, researchers said.
Microsoft, Aikido, Socket and Wiz all said the same payload and pattern was observed across all affected packages, indicating a single attacker or threat cluster was behind the supply-chain attack and using multiple stolen tokens.
The malware showcased a few pieces of new functionality, but retained the same core mechanisms that are hallmarks of Mini Shai-Hulud.
“The evolution is consistent with what we’ve seen from them in past waves, however we don’t yet have the hard links” to confidently attribute the attacks to TeamPCP, Wiz Research said.
The notorious threat actor, which Google previously told CyberScoop it attributes to one core operator that was located in South Africa during at least some of the attacks, compromised and injected malicious code into more than 1,000 software packages in less than four months earlier this year.
Huntress researchers spotted an active and ongoing series of attacks targeting SonicWall VPN and firewall accounts, which compromised 30 organizations in less than two days, the company said in a threat advisory Tuesday.
The credential stuffing campaign started Saturday and grew rapidly, ultimately compromising 92 unique user accounts during the next 41 hours, according to Huntress. Researchers said the attacks were broad and opportunistic, hitting various SonicWall devices, rather than targeting specific types of organizations.
SonicWall hasn’t released a security advisory about the malicious activity as of press time. A spokesperson told CyberScoop the company is still investigating and hopes to have more information soon.
The attacks ended — at least for now — as abruptly as they began. The last compromise occurred Monday, according to Michael Tigges, principal tactical response analyst at Huntress.
“This fits campaign trends,” he said. “A rash of compromise will break out, followed by silence until the adversary rotates infrastructure.”
Attackers, which haven’t been identified, have also refrained from initiating any post-compromise activity, indicating the intrusions could be pre-positioning for future attacks.
“With local network access, the sky is essentially the limit for most networks that do not have proper topology controls in place,” Tigges said.
Huntress’ observations are limited to telemetry it collects from its customers, meaning all of the identified victims were Huntress customers using SonicWall devices, so the number of organizations impacted could be greater.
Researchers haven’t identified a root cause for the attacks, noting that they begin with authorized logins. Attackers are validating credentials against remote access portals to compromise as many vulnerable accounts as possible, the cybersecurity vendor and threat intelligence firm said.
“This could be an aggregation of stealer malware logs, previously compromised SonicWall configuration files, or historic CVE compromise that resulted in more credentials than the adversary could use at the time,” Tigges said.
In 2025, an undisclosed state-sponsored threat actor intruded SonicWalls’s cloud environment and stole firewall configurations of every customer.
SonicWall customers have also been hit by a barrage of actively exploited zero-days, including a pair of zero-days that were exploited for three weeks before the vendor disclosed and patched the defects earlier this month, and previously disclosed defects in SonicWall devices for years.
Seventeen defects affecting the vendor’s products have been added to CISA’s known exploited vulnerabilities catalog since late 2021. Ten of those defects are known to be used in ransomware campaigns, according to CISA, including a wave of about 40 Akira ransomware attacks between mid-July and early August 2025.
“Edge devices are one of the most targeted interfaces, comprising over 70% of active intrusions triaged by Huntress, including the overwhelming majority of ransomware deployments,” Tigges said. “Organizations that do not spend significant time architecting secure remote access solutions and networks that are resilient to edge-device compromise will likely continue to feel the burn in the coming months and years.”
Malware targeting AI coding assistants and software developers’ automated workflows is spreading into more environments with more capabilities, placing defenders at a growing disadvantage.
A malware strain dubbed Sandworm_Mode, first discovered by Socket in February, represents a growing threat to software development. According to a CrowdStrike report, the self-propagating worm can spread through code repositories with minimal detection, raising alarms about software supply chains.
The malware’s capabilities are extensive, but not especially unique compared to the series of supply-chain worms known as Shai-Hulud, and more recently Mini Shai-Hulud.
“This is the new trend,” Adam Meyers, senior vice president of counter adversary operations at CrowdStrike, told CyberScoop. “This is something we’re seeing more and more. It’s the new hotness right now.”
Sandworm_Mode targets and steals sensitive data, including credentials, keys and secrets that unlock paths to additional services and dependencies throughout the AI toolchain. This includes AI assistants, cloud providers, API keys for nine major LLM providers, CI/CD pipelines and automated systems that build, test and publish code.
These actions blend in with tens of thousands of other commands occurring daily in any given environment infused with AI development tools.
“Trying to find the signal of something malicious happening is very difficult because there’s so much noise out there,” Meyers said.
The worm also paces itself, setting multi-day delays to separate initial access from follow-on malicious activity — creating a gap in victims’ telemetry windows, which makes it even more challenging for defenders to detect and attribute the chain of infection properly.
“AI agents are pulling down all of these different dependencies continuously throughout the day,” Meyers said. “When you’re looking downrange from the perspective of the security operations team, you’re just seeing everybody pulling down these dependencies, and these dependencies self-unpacking and executing, so it just gets really, really noisy to try to find something bad happening.”
The malware covers its tracks further with a bit of a mean streak, by automatically destroying compromised environments if it can’t spread or accomplish its objectives.
“It’s well thought-through, and well developed, so somebody spent some time caring and feeding this thing,” Meyer said.
Despite CrowdStrike’s four-month review of Sandworm_Mode, the cybersecurity firm has yet to gain a firm handle on its intent, but Meyers said it is designed to attain a strong foothold, which could enable long-term access.
CrowdStrike hasn’t determined who is responsible for the malware, yet Meyers said he doesn’t think TeamPCP, a threat group that’s been on a rampage through open-source software this year, is involved.
“It could be a nation-state threat actor, or it could be an e-crime actor that’s looking to use this to then sell access to other organizations,” he said. “We don’t really know what the intention is.”
The state of Sandworm_Mode and whether it remains active is also unclear. CrowdStrike said it continues to observe recently active malicious supply-chain packages that follow similar but technically divergent patterns.
Ultimately, “the world has changed,” Meyers said, adding that many attackers are pursuing similar paths in the AI toolchain, requiring defenders and threat hunters to place a greater focus on this burgeoning mode of aggression.
A cyberattack that poisoned the data pipeline of a major AI code platform was carried out using OpenAI’s ChatGPT, the company said Tuesday.
Last week, Hugging Face, a platform for sharing and working on AI code, disclosed that an external attacker had compromised its data processing pipeline. According to a July 21 blog post, the attacker poisoned a dataset to run code on a processing worker, eventually gaining node-level access and stealing cloud credentials.
The attack is notable, the blog said, because it appears to have been carried out by an autonomous AI system, which executed “many thousands of individual actions across a swarm of short-lived sandboxes, with self-migrating command-and-control staged on public services.”
At the time, Hugging Face said it wasn’t clear which LLM was used in the attack, but noted that their own attempts to recreate parts of the attack using an in-house commercial model failed due to guardrail restrictions.
The incident and its ultimate impact are still being investigated, and Hugging Face said it reported the incident to law enforcement and is engaging with third-party cybersecurity forensic specialists to learn more.
“This experience points to a gap worth planning for,” the company wrote. “We do not know which model powered the attacker’s agents, whether a jailbroken hosted model or an unrestricted open-weight one; either way, the attacker was bound by no usage policy, while our own forensic work was blocked by the guardrails of the hosted models we first tried.”
Now OpenAI is confirming one of their models was used in the attack.
“After investigating, we now know that this particular incident was driven by a combination of OpenAI models — including GPT‑5.6 Sol and an even more capable pre-release model, all with reduced cyber refusals for evaluation purposes — while being internally tested on a benchmark of cyber capabilities,” the company wrote in a blog post Tuesday.
OpenAI called the incident “unprecedented” but also predicted that such attacks would become increasingly more common as AI adoption continues to grow.
According to the company , the incident happened during an internal evaluation, where the company deliberately prompts models to “pursue advanced exploitation using complex attack paths” in order for the company to study and measure the model’s cybersecurity capabilities.
To assess the model’s full potential, the team disabled the production classifiers that normally prevent OpenAI models from carrying out high-risk cyber activity. Without these safeguards, the models were able to install software packages through registries like Hugging Face.
The model collected and chained vulnerabilities from OpenAI’s systems as well as Hugging Face’s production infrastructure.
OpenAI further explained that the activity stemmed from models attempting to solve a specific challenge posed by ExploitGym, a benchmarking system for AI agents.While such tests normally run in isolated environments, in this instance, the model spent a “substantial” amount of compute resources figuring out how to access the open internet. It did so by using a zero-day vulnerability in a third-party vendor’s system used by OpenAI (the company said it disclosed the flaw to the vendor).
“After gaining Internet access, the models inferred that Hugging Face potentially hosted models, datasets and solutions for ExploitGym,” OpenAI wrote. “Knowing this, the model searched for and successfully found ways to gain access to secret information that it could use to cheat the evaluation.”
In one instance, the model chained together multiple stolen credentials and zero-day vulnerabilities to find a remote code execution path on Hugging Face servers.
OpenAI said it was implementing new controls for infrastructure configuration, something that would come at “the cost of research velocity while the vulnerabilities are patched.”
Hugging Face was also added to OpenAI’s Trusted Access for Cyber program, which will give them access to more advanced models like Daybreak to scour their systems for other AI-discovered vulnerabilities.
After a year and a half spent downplaying calls for AI safety regulations, the Trump administration has sharply reversed course, embracing a level of government scrutiny of frontier AI systems before public release–a far stricter stance than the Biden administration took.
An executive order designed to be friendly to the AI industry was meant to let the federal government briefly review some new models on a voluntary basis.
When the Trump administration, suddenly and without much warning, slapped export controls on Anthropic’s Fable 5 and Mythos 5 in response to private sector threat intelligence reporting, the U.S. AI industry officially entered its regulatory era.
But key questions and gaps remain. It’s not clear why the administration drew the line where it did, or whether they will move it again in the future.
While newer models like Mythos and OpenAI’s Daybreak do have stronger cybersecurity capabilities, the private sector reports the administration relied on describe capabilities already available in older commercial, open-source and Chinese models that nearly anyone can access.
CyberScoop spoke with current users of the latest frontier models, including OpenAI’s ChatGPT 5.5 and Fable 5, to learn more about what these models are currently capable of in offensive and defensive cybersecurity.
Cybersecurity experts and former government officials say the administration may be playing catch up on threats that have been building for years as it has more fully realized the national security implications of the technology.
Are the models breaking new ground or just breaking things?
Users of Chat GPT 5.5, introduced this past April, and Fable 5 tell CyberScoop those models have been largely helpful to their work, even as they complained about high token usage and safety guardrails that hinder, but don’t meaningfully prevent, defensive cyber tasks.
Eyal Webber Zvik, chief strategy officer at Cato Networks, a cloud and cybersecurity network provider in OpenAI’s Trusted Access in Cyber program, said they use GPT 5.5 and later OpenAI models to scan and triage internal codebases for vulnerabilities, test new safeguards and provide “highly autonomized service” to their customers.
Zvik wouldn’t disclose how many bugs 5.5 has found but said the company’s view is that it helps both find bugs that humans missed and rank which ones to patch based on factors like each bug’s exploitability.
“It is now a native part of our development environment and cycles, and we use those models to scale our entire codebase and make sure what we release into the service that our customers use to run their networks and network security has the least likelihood of having any vulnerabilities that can be exploited,” said Zvik.
John Hopper, vice president of engineering at SpecterOps, an identity security company, said newer models like GPT 5.5 are sharper and more persistent in pursuing their tasks.
“That can be a good or bad thing,” he noted.
One metric that SpecterOps tracks is how long it can keep a particular agent working before it moves off task or fails. That metric “matters a lot” because the longer an agent works without human help , the more agents a single operator can run at once.
Hopper said this provides defenders with immense value, and pushed back on the idea that the offensive capabilities the models offer are automatically more beneficial to malicious hackers. There is “a modicum of grounding that the industry needs when we talk about these models.”
“Yes, AI frontier tools will lower the barrier of entry, but these problems have always existed,” he said. “I don’t actually believe that AI is going to remove the needle in the haystack problem, but by howdy, using my two hands to find that damn needle, compared to using a backhoe, I can tell you which one I’d rather be driving.”
Eran Kinsbruner, vice president of product marketing at software security firm Checkmarx, told CyberScoop that later models like OpenAI’s Codex Security and GPT 5.5 are noticeably easier to set up and run with local systems, even for less technical users. That alone gives them an edge over many cybersecurity tools where interoperability is a constant concern.
However, GPT 5.5 burns through tokens at a much faster rate. He recalled one instance of using it to scan a medium-sized repository in three different programming languages.
“After 26 minutes I almost ran out of tokens, and it didn’t provide anything, just created a threat model for me and told me you want to buy more tokens?” he said.
In other instances, some of the scan results he received were not comprehensive.
Further, he expressed frustration with some of the guardrails designed to prevent risk – like only allowing users to scan local files but not code repositories like GitHub – “makes not too much sense” given how often developers must work with remote code.
Those kinds of guardrails – which can prevent models or developers from injecting malicious code or prompting into their models – sit at the heart of the debate in Washington D.C. and around the world. Some users feel differently about their utility.
Kinsbruner said that doesn’t make sense for organizations like his, which work with thousands of different enterprise organizations with thousands of different code repositories spread across the internet.
“I cannot imagine how large-scale developers could just jump into this solution and make it an enterprise-grade, enterprise-level, de facto cybersecurity solution” out of it, said Kinsbruner.
OpenAI did not respond to a request from CyberScoop for an interview on GPT 5.5. The company has since released another model, GPT 5.6, that they said is more efficient at token use.
The White House’s crash course in AI cyber risk
The White House keeps changing its line on whether and how the U.S. government should limit the release of commercial frontier models. The shift comes from lessons learned since coming into office in Jan. 2025. Trump threw out Biden-era regulations meant to steer the industry toward safer models. Top officials like Vice President JD Vance argued against restricting industry progress.
Less than two years later, administration officials worry about the impact of speed and scale – two things AI excels at – in cyberspace.
According to Will Loucks, senior director of intelligence at the Office of the National Cyber Director, over the past two years the number of exposed and known vulnerabilities has shot up. Threat actors exploit those flaws faster before defenders can fix them. Once inside, the time from initial access to full network control shrinks.
“So in other words, every stage of the cyber operations lifecycle that a threat actor has to move through to get to a victim network and achieve an outcome, they’re just moving through more quickly faster,” said Loucks at a July 16 event in Washington D.C.
Speaking about AI in particular, Loucks said one of the defining characteristics of the technology is its ability to lower barriers for threat actors.
“Sometimes speed and volume have a threatening aspect alone, even if sophistication isn’t quite increasing in the same way, and the reason for that is because it places pressure on defenders…to triage alerts more quickly,” he said.
Jordan Rae Kelly, former director for cyber and incident response on the White House’s National Security Council during Trump’s first term, told CyberScoop that the changes over the past two years reflect the lessons the White House has learned on the issue since returning to office.
In the early days of this administration, Kelly said, “there is a sense and a spirit that the Biden administration was limiting AI and there was a kind of a rip-it-all-off [attitude], everybody go and do whatever, we will be the biggest and boldest and brightest.”
“I love that talking point, but I think what you’ve seen is probably an education over the last 19 months, where people [in the White House] have said that’s a challenging premise to put into place, knowing about the potential downsides and capabilities,” she added.
Michael Daniel, former White House cyber coordinator under President Barack Obama, thinks the horse may already be out of the barn.
Daniel, now head of the Cyber Threat Alliance, a membership nonprofit group focused on cyber threat information sharing between industry and government, said his members report that AI is being used to do things “faster and at a slightly bigger scale” but aren’t yet seeing the flood of exploitation that analysts have warned about. Not yet.
“I think what we’re seeing right now [and] talking about is ‘okay, where are the step changes [in the cyber threat landscape] actually going to occur?” said Daniel. “Are we and when will we see the explosion in vulnerability reporting from these Mythos-like capabilities? That’s what’s really got their attention right now.”
But Mythos and OpenAI’s Daybreak models are restricted to select organizations, and neither has publicly released its most powerful cybersecurity models to the public. That dynamic won’t last.
The UK’s AI Security Institute estimates that open source and foreign LLM models are between 4-7 months behind frontier U.S. models. In that setting, it’s hard to stop the development of AI models worldwide through export controls or other limits.
“It’s not like we’re buying ourselves five to ten years on this,” he said. “We’re not, and so I’m not sure the impact on the defenders who are trying to obey the law is worth whatever small hiccup we cause for our adversaries.”
Kelly said there’s merit to the administration’s current position, even if it took time to get there. Many federal cybersecurity procedures that operated even a decade ago – such as a Vulnerabilities Equities Process that could take days or weeks to consider the pros and cons of keeping an exploit – are no longer practical.
“All of that work to some degree, is out the window, because you can’t meet with the regularity you would need to meet to adjudicate vulnerabilities that are being found in seconds and exploited in minutes,” said Kelly.
But Kelly and others say that’s also because AI capabilities in cybersecurity are developing faster than policymakers can react, even in the best of times.
Key questions remain and the administration’s balance between national security and backing domestic industry will likely shift in response to new events. The administration wants a framework that can predict and manage the risks of AI models today and tomorrow. That may be harder than it sounds.
“Do I think they’ve been clear? No,” said Kelly. “But I think it’s a place where clarity is really hard to achieve.”
State and local officials and election security experts largely panned a Thursday night primetime speech by President Donald Trump, saying it was reflective of White House “desperation” to find any credible evidence to support their claims that U.S. elections have been rigged against the two-term president.
While the White House teased explosive new claims about the potential compromise of U.S. elections by China, Trump’s speech was a rehash of claims that both have no supporting evidence and have been repeatedly debunked when investigated.
David Becker, executive director of the Center for Election Innovation and Research and a former voting and civil rights attorney at the Department of Justice, said none of Trump’s claims or allegations were new or substantively different from previous theories he’s been espousing over the past six years.
“The White House promised a bombshell and they delivered a dud,” Becker said on a call with reporters Friday. “There was nothing that even calls into question past elections — certainly not the 2020 election.”
The administration declassified a huge tranche of documents from the intelligence agencies, and news outlets continue to sift through them, but thus far nothing has been found that remotely validates the administration’s claims about foreign interference from China costing Trump the 2020 election.
In fact, some of the most relevant documents found at this point have supported the opposite conclusion, with agencies assessing that while China engaged in influence campaigns around the election, it was not attempting to outright interfere with U.S. election infrastructure, hack voting machines or manipulate ballots.
John Solomon, a former journalist and opinion writer at The Hill brought in by the White House to lead the investigation, also told reporters Thursday that his search hasn’t turned up evidence that the 2020, 2022 or 2024 elections were affected by fraud.
The one new major claim by Trump — that the Department of Homeland Security determined hundreds of thousands of noncitizens were registered to vote across four states — is almost certainly false or overinflated, given that it contradicts post-election state audits that have routinely found single or double-digit numbers of noncitizens registered to vote within a single state across multiple elections.
Over the past six years, similar claims by GOP secretaries of state and political activists purporting to find mass numbers of noncitizens registered to vote have turned out to be grossly inflated due to shoddy data analysis, and the vast majority of cases involving “suspected noncitizens” turn out to be U.S. citizens who are legally registered to vote.
The White House has provided little to no information on the methodology used to flag and identify supposed noncitizen voters, other than alluding to the use of “commercial data” and federal databases. A federal court recently ordered DHS to dismantle the SAVE database, its primary database for verifying the citizenship status of U.S. voters, because it was unreliable and violated longstanding privacy laws.
Apart from DHS admitting its own data on citizenship is incomplete, Becker said using a list that relies on matching voter files with commercial data is not a reliable way of determining citizenship.
“It is impossible to take a public voter file with very little information that is uniquely identified, like a driver’s license number, and compare it to a commercial database and say for sure the Maria Rodriguez or the John Lee or the Shawn O’Hara you have on that is the same person,” he said.
Election officials also responded forcefully. Nevada Democratic Secretary of State Francisco Aguilar said that Trump has spent a decade attempting to manufacture a crisis around voter fraud and the president’s speech Thursday night was an extension of that effort.
“As Nevada’s chief elections officer, it’s my job to call balls and strikes — so when the President lies, I am obligated to call him out,” Aguilar said in a statement. “The facts have not changed: Nevada’s elections are among the safest, most secure and accessible in the nation.”
It’s not just Democrats that have objected to the administration’s efforts. GOP states have gone to court to block the Department of Justice from obtaining their voter data, and Idaho’s Republican secretary of state responded to a DOJ letter threatening prosecution of election officials as “not well met” and potentially illegal under state ethics laws.
Trump’s speech potentially casts additional light on recent White House decisions, such as firing all three commissioners on the Election Assistance Commission. The agency helps certify voting machines for security, and all three commissioners have served across administrations and maintain close relationships with state and local election officials.
Pamela Smith, CEO of the nonprofit Verified Voting, said that while the EAC can’t take certain actions that need commissioner approval, “critical functions like voting system testing and certification can continue under the existing framework and should not be affected.”
In 2020, Trump’s initial claims of widespread election fraud were undercut by leaders at the Cybersecurity and Infrastructure Security Agency, which said there was no evidence the election was compromised. The removal of EAC commissioners could represent an attempt to preempt any efforts to rebut or criticize White House claims that elections and voting machines have been compromised.
Some have worried that Trump could use the speech as a pretext to declare a national emergency or cancel elections.
Tom Lopach, CEO of the Voter Participation Center, said “you don’t dismantle election security infrastructure if you’re serious about protecting elections.”
“You dismantle it if you’re planning to claim, without evidence, that the system failed you,” he said.
While Becker takes Trump’s broadsides against state election authority seriously, he also said it’s important not to lose sight of the fact that, in his view, the administration is losing the argument across the board.
More than a dozen federal courts have unanimously rejected the federal government’s attempts to forcibly obtain state voter data, while other courts have rejected core pieces of his election-related executive orders. State officials have publicly — and at times, angrily — pushed back on the administration’s demands as blatant federal overreach.
Becker predicted that such an act would be quickly shot down by courts as well, noting that the U.S. has never canceled or postponed an election in its 250-year history, including when British troops were marauding on American soil during the War of 1812 or even at the height of the Civil War.
It’s important not to conflate the White House’s bluster and intentions with its actual authorities or capability to seize control of U.S. elections.
“This is what panic and desperation look like,” Becker said. “They’ve had 18 months in total control of the federal government and they have found nothing that would support President Trump’s lies about the 2020 election, and so they’re just trying to grab as much garbage as they can and throw it up against the wall, and it’s not sticking.”
If you spend your days building, shipping, defending, or fixing systems, you already know how this goes. A new technique shows up in a research thread, someone drops a “has anyone checked if we’re exposed?” comment, and suddenly you’re juggling risk, patches, logging gaps, and whatever tool is in the blast radius this week.
That day-to-day reality is why Rapid7 Labs is launching Hacktics and Telemetry, a bi-weekly video and audio podcast with episodes built to fit into a lunch break or a commute. It’s hosted by Rapid7's Douglas McKee, bringing to the pod years of deep technical and leadership experience, then co-hosted by Jonah ‘CryptoCat’ Burgess – a strong researcher with a solid pulse on the cybersecurity community.
The format stays consistent on purpose. Each episode starts with a scan of what’s emerging, shifts into a guest conversation, then closes with a short segment that ties the story back to mitigation and tooling. The goal is simple: move past theory, show what’s happening with real examples, and leave you with something you can act on.
Episode 1: OpenClaw Risks, RCEs, and Metasploit Pro Updates
Doug and Jonah open by digging into two AI-centric stories from the past week. The first is PhoneLeak, described as data exfiltration in Gemini via phone call. It’s the kind of uncomfortable example that forces practical questions: how do you defend against mobile clickjacking when it's disguised as a routine CAPTCHA? When an AI assistant has deep extensions into a user's workspace, how do you prevent malicious prompts from quietly accessing sensitive data like 2FA codes? And perhaps most importantly, how do defenders anticipate and monitor for bizarre, out-of-the-box exfiltration methods—like an AI bypassing SMS confirmations to leak data via DTMF tones on a phone call?
The second story comes from the other side of the AI conversation: an AI agent reportedly identifying an RCE in BeyondTrust remote support, plus discussion of older privileged remote access versions. More automation can mean faster discovery, which shrinks the window between “interesting finding” and “you need to patch this.” That changes how defenders think about exposure, patch prioritization, and what “good enough” means (and looks like) when it comes to monitoring.
In the guest segment, Greg Richardson (Global Advisory CISO & AI Thought Leader, 6 Levers AI) walks through how he uses AI agents in his workflow while keeping control tight. He talks about setting tasks while he sleeps, but the constraints are the point: access is locked down, the agent only touches files he explicitly provides, communication is limited, and token limits help cap the size of any mistake. He also makes a strong case for starting small, with one task at a time, instead of trying to automate dozens of things on day one.
To close out this inaugural episode, the team hits on a SolarWinds Help Desk vulnerability, then shares a quick look at Metasploit Pro 5.0 updates – including more granular payload selection and a walkthrough of the new UI.
If your idea of useful content includes threat trade-offs, concrete mitigations, and a bit of candid “how this actually plays out,” you’re in the right place.
Following our recent published advisories, this publication is intended to outline a summary of the cyber activities associated with the tension. Based on the available information, we believe the conflict is beginning to show signs of expanding beyond a strictly regional crisis. Initial threat reporting pointed to a measurable increase in cyber activity linked to the crisis predominantly focused on hacktivist mobilization, with reports of phishing campaigns, and claims of data theft and disruptive operations. For a companion piece focused around our customers, dive into Rapid7 Detection Coverage for Iran-Linked Cyber Activity.
Cyber activity by groups associated with Iran and their affiliated ecosystems have begun to surface. Much of the visible activity currently appears to have limited immediate operational impact as it consists primarily of website defacements, distributed denial-of-service (DDoS) attacks, coordinated messaging campaigns, phishing attempts, and reconnaissance against exposed digital infrastructure. While these incidents may appear opportunistic or symbolic, historical patterns of such behavior suggest that this activity can represent early-stage signaling, pressure, and preparatory shaping operations rather than isolated disruption.
Iran’s cyber ecosystem operates through a layered structure that includes state-linked advanced persistent threat (APT) groups, proxy actors, hacktivist personas, and sympathetic foreign collectives. Even when not centrally coordinated, these actors often converge on the same narratives and target sets during geopolitical crises, enabling simultaneous visible disruption and covert intelligence-driven intrusion activity. As the conflict evolves, this ecosystem provides a scalable and deniable tool for retaliation that can gradually intensify.
It is very likely that the cyber risk will widen accordingly as the current conflict continues. Governments and organizations located in regions hosting U.S. military infrastructure or closely aligned with U.S. and Israeli positions may face increased exposure, particularly across sectors such as logistics, critical infrastructure, public administration, energy, and telecommunications.
Strategic context and operational trends
Iran does not operate according to a single publicly articulated cyberwarfare doctrine. Instead, its cyber strategy has evolved pragmatically as part of the country’s broader asymmetric security model. Since 2010, there has been an expansion of its cyber capabilities as instruments for intelligence gathering, internal control, retaliation, coercive messaging, and regional influence. Cyber operations are therefore best understood not as a separate military domain with a fully transparent doctrine, but as an adaptable component of the regime’s survival and strategic competition against outsiders.
Broadly speaking, Iranian cyber activity tends to serve three overlapping strategic objectives. The first is regime security and domestic control, in which cyber tools support surveillance, information control, and disruption of dissident or opposition networks. The second is strategic intelligence collection, in which state-linked actors target governments, defense organizations, technology providers, telecommunications firms, and critical infrastructure to gather political, military, and economic intelligence. The third is coercive signaling and regional influence, in which cyber operations impose costs on adversaries, shape perceptions, and demonstrate retaliatory capability while remaining below the threshold of overt interstate war.
A key feature of this regime’s approach is the development of long-term access. Iranian APT groups often conduct sustained intrusion campaigns focused not only on immediate collection but also on access persistence, credential harvesting, and network familiarity. In a crisis environment, these pre-existing footholds can become strategically important, supporting either intelligence collection or later disruptive operations. This is one reason current low-visibility intrusions deserve as much analytical attention as public hacktivist claims. The visible DDoS or defacement campaign may dominate headlines, but the more significant strategic risk often lies in covert access established inside other targets.
Another defining feature of Iran’s cyber strategy is its layered operational model. State-linked APT groups frequently operate alongside contractors, proxies, persona-driven influence actors, and hacktivist collectives. This structure offers several advantages: it creates deniability, increases operational tempo; broadens the range of possible targets; and allows Iran-aligned ecosystems to combine disruptive spectacle with intelligence-driven depth. During periods of heightened tension, this blended model enables visible pressure operations to coexist with quieter espionage or pre-positioning campaigns. Current reporting on the conflict strongly supports this interpretation, with activist and proxy campaigns surging in parallel to concern over state-linked phishing, malware, wipers, and infrastructure-focused targeting.
Iran’s threat actor landscape
State sponsored
Iran’s cyber capabilities are distributed across a hybrid ecosystem of state institutions, intelligence services, military structures, and semi-official operators. Rather than relying on a single centralized cyber command, Tehran appears to allocate responsibilities across different organs, primarily the Islamic Revolutionary Guard Corps and the Ministry of Intelligence and Security, with support from contractors, front entities, and affiliated personas. Strategic coordination of the cyber domain is overseen by the Supreme Council of Cyberspace, while operational activities are carried out through a mix of official and semi-official channels.
IRGC-linked actors
The Islamic Revolution Guard Corp (IRGC) maintains one of Iran’s most visible offensive cyber capabilities and has been associated with cyber espionage, influence operations, credential theft, and politically aligned disruptive activity. Among the principal IRGC-linked actors are APT35 (also known as Charming Kitten or Mint Sandstorm), which has long conducted spear-phishing and credential-harvesting operations against diplomats, journalists, researchers, and policy communities; APT42 is an actor particularly associated with surveillance and social engineering targeting dissidents, activists, journalists, and policy experts. Cotton Sandstorm (also known as Holy Souls and Emennet Pasargad), meanwhile, has been linked to both espionage and influence-oriented operations targeting regional adversaries and Western institutions. Recent reporting also highlights continued concern around malware associated with this broader actor set, including infostealing and espionage tooling used in phishing-led operations.
MOIS-linked actors
The Ministry of Intelligence and Security (MOIS) operates parallel cyber capabilities that tend to emphasize intelligence collection, long-term access, and strategic espionage. The most prominent groups in this cluster include MuddyWater and OilRig (also known as APT34). CISA has previously described MuddyWater as an Iranian government-sponsored actor conducting cyber espionage and malicious cyber operations across multiple sectors, while current reporting continues to place the group among the most operationally relevant Iranian state-linked threats in the present crisis environment. OilRig remains a longstanding espionage actor focused on governments, financial institutions, energy entities, and other strategic organizations.
These actors illustrate Iran’s distributed cyber-operational model: Intelligence-driven access development, influence, psychological pressure, and opportunistic disruptive action are not separate lines of effort but parts of a broader strategic continuum.
Parallel hacktivist and proxies
Beginning in June 2025, a noticeable surge in hacktivist and proxy cyber activity accompanied the broader escalation of tensions in the Middle East. This reflects a recurring pattern observed during previous geopolitical crises, in which ideologically aligned non-state cyber actors mobilize alongside, or in parallel with, state-linked cyber operations. In the current confrontation, this dynamic has again expanded the cyber landscape beyond traditional state-directed espionage or sabotage.
By early March 2026, several dozen hacktivists or proxy collectives emerged related to the conflict. These groups vary significantly in capability and reliability. Some focus on distributed denial-of-service (DDoS) attacks, while others conduct website defacements or hack-and-leak campaigns. Some primarily amplify claims of compromise that are exaggerated or only partially verifiable. Their significance, therefore, lies less in technical sophistication than in the cumulative pressure they place on defenders and the broader information environment.
In crisis situations, this activity can produce strategic effects. Numerous low-impact incidents can consume defensive resources, complicate attribution, and obscure more sophisticated intrusions occurring simultaneously. Hacktivist campaigns may therefore function as distractions, signals, or psychological pressure while more capable actors pursue quieter access to high-value networks. For this reason, the analytical distinction between advanced persistent threat (APT) activity and hacktivism can become blurred during periods of geopolitical confrontation.
Several collectives active in the current environment publicly position themselves as ideologically aligned with Iran or with members of the so-called “Axis of Resistance.” Among the more visible groups are Handala Hack Team, Dienet, FAD Team, APT IRAN, Cyber Islamic Resistance, and Fatimion cyber team.These actors frequently frame their operations as retaliatory cyber campaigns targeting Israeli, Western, or allied regional entities, claiming responsibility for activities such as website defacements, DDoS attacks, and hack-and-leak operations targeting mainly government, telecommunications, energy, and financial entities. Although many claims remain difficult to verify independently, their messaging strategy often emphasizes their psychological and reputational impact.
In parallel, several pro-Russia hacktivist groups have also engaged in operations linked to the confrontation, including NoName057(16), Sever Killer, and Russian Legion. These groups typically conduct large-scale DDoS campaigns targeting government portals, financial services, and transportation or telecommunications infrastructure in states perceived as supporting Israel or broader Western policy positions. Their participation illustrates how regional conflicts can attract cyber actors from outside the immediate theater when ideological alignment or strategic narratives converge.
Cyber activities linked to the ongoing conflict
Iranian APT group operations
Beyond the highly visible hacktivist activity circulating on social media, defacement platforms, and Telegram channels, a quieter but more strategically significant layer of cyber operations is unfolding through Iranian state-linked APT groups. These operations appear ongoing and aligned with broader geopolitical objectives tied to the current conflict environment.
Recent threat reporting indicates continued operations by the Iranian APT group, MuddyWater, which is widely assessed to be linked to MOIS. Since at least early February 2026, reporting has suggested potential compromises or attempted intrusions targeting organizations associated with the United States and allied interests.
According to public reporting, activity linked to the group was reportedly observed within the networks of a United States–based bank, a United States airport, a nonprofit organization operating across the United States and Canada, and a software company with operations in Israel. In several of these incidents, threat actors reportedly deployed a previously undocumented backdoorknown as Dindoor, suggesting a coordinated, ongoing campaign rather than isolated compromise events.
Hacktivist and proxy disruption activities
The most visible form of cyber activity so far remains hacktivist and proxy-led disruption.
DDoS attacks are among the most common tactics employed by hacktivist groups. Pro-Russia groups such as NoName057(16) and Server Killers, along with other pro-Iran collectives affiliated with them, have been linked to waves of coordinated DDoS attacks against Israel, Qatar, Bahrain, and other politically symbolic targets. These attacks are generally inexpensive and cause only short-term technical damage, but they remain strategically useful because they disrupt public services, tie up defense resources, generate media coverage, and fuel the narrative of a sustained cyber response.
Figure 1: Telegram post from pro-Russia hacktivist groups claiming responsibility for targeting an Israeli website in support of Iran
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Website defacement also remains a common tactic. Groups such as FAD Team, 313, and Cyber Islamic Resistance have been associated with claims of attacks on several websites. Although defacements are technically simple to execute, they remain analytically significant: They are highly visible, rapidly disseminated, and psychologically impactful, often creating an exaggerated perception of widespread systemic compromise.
Data breaches represent a far more significant dimension of cyber operations. The Iranian-aligned group Handala, in particular, continues to blend political messaging with claims of data theft and the selective release of allegedly compromised information. The group recently asserted that it had infiltrated a Saudi energy company and exfiltrated internal documents, framing the operation as a combination of data exfiltration, coercive pressure, and psychological warfare targeting the energy sector. Even when the full authenticity of released datasets cannot be independently verified, the publication of partially credible material can still generate substantial reputational damage and potential operational disruption for affected organizations.
Targeting critical infrastructure has emerged as one of the most concerning aspects of the current cyber activity by pro-Iran hacktivists and proxy collectives. Groups operating in this ecosystem, including Iranian APTs, Handala, and networks associated with the Cyber Islamic Resistance umbrella, have publicly claimed operations targeting infrastructure across the region. Recent Telegram posts indicate that an Iranian APT group claimed responsibility for attempts to sabotage Jordanian critical infrastructure, while other Iran-aligned hacktivist personas have asserted access to sectors including fuel systems, water utilities, and other operational technology environments.
In a separate case, the Handala Hack Team has alleged that it compromised both Oil and gas companies in the United Arab Emirates and Israel, claiming to have exfiltrated more than 1.3 TB of sensitive data from oil and gas sector networks. These claims, which would represent a significant intrusion into Middle Eastern energy infrastructure if confirmed, have circulated primarily through hacktivist communication channels and social media reporting and have not been independently verified.
Figure 2: IRAN APT group claimed attempts to target Jordanian critical infrastructure
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Although many of these claims remain difficult to independently verify, the recurring focus on industrial control systems and essential services is analytically significant. Hacktivist collectives aligned with Iranian geopolitical narratives frequently leverage infrastructure-related claims as part of information operations designed to amplify perceived impact, generate psychological pressure, and signal the potential for escalation into operational technology environments. Even when technical disruption is limited or exaggerated, the persistent narrative around infrastructure compromise can shape defensive priorities and highlight potential escalation pathways within the broader cyber conflict.
Sectoral exposure and risk landscape
In the current geopolitical context, cyberattacks extend far beyond military networks and defense institutions. Modern cyber operations increasingly aim to affect the broader ecosystem that supports government activity, economic stability, and public trust. Consequently, adversaries seek not only technically vulnerable targets but also organizations whose compromise or disruption can increase visibility, influence public perception, or create cascading effects across interconnected systems.
A successful intrusion into a widely used service provider, a major infrastructure operator, or a publicly accessible institution can quickly produce consequences that extend far beyond the initial target, affecting supply chains, service availability, and public confidence. In this context, cyber operations often serve multiple purposes simultaneously: intelligence gathering, strategic positioning within critical networks, and generating disruption or exerting influence during periods of heightened geopolitical tension.
At present, several sectors appear particularly exposed:
Government institutions and public administration
Defense and aerospace industry
Energy sector, including oil, gas, and electricity
Telecommunications providers
Financial services
Transportation systems
However, the risk landscape extends beyond these sectors themselves. Organizations that form part of the broader digital supply chain supporting these industries may also represent attractive entry points. This includes cloud service providers, managed service providers, technology vendors, and other third-party platforms that maintain privileged access to client environments. Compromising such intermediaries can allow adversaries to reach high-value targets indirectly. By gaining access to a supplier or service provider, attackers may obtain pathways into multiple networks simultaneously, access sensitive information, or move laterally across interconnected operational systems. Supply chain compromise, therefore, offers both scale and stealth, making it an increasingly common tactic in sophisticated cyber campaigns.
Geopolitical alignment can also influence targeting decisions. Organizations based in countries that host United States military assets or are publicly aligned with United States or Israeli policy positions may attract additional attention from adversaries. In these cases, targeting can carry symbolic, political, or strategic value beyond the immediate technical impact of the intrusion. Within this environment, cyber exposure can generally be understood through three overlapping targeting dynamics.
Symbolic targets include municipalities, universities, media outlets, and public institutions. These organizations may be targeted primarily for visibility, messaging, or propaganda purposes. Even limited disruption or data exposure can generate headlines and amplify the perceived reach of the attackers.
Operational targets include sectors that support everyday economic and social activity, such as telecommunications providers, transportation systems, payment networks, and fuel distribution infrastructure. Disruptions in these areas can quickly affect daily life, creating public anxiety and increasing pressure on authorities to respond.
Strategic targets consist of entities whose compromise offers long-term intelligence or operational value. This category includes defense contractors, major financial institutions, government networks, and operators of critical infrastructure. In these cases, adversaries may prioritize persistence and stealth to collect intelligence, monitor decision-making processes, or maintain access that could be leveraged during future crises.
Taken together, these targeting patterns illustrate a broader shift in cyber operations: Attackers are increasingly selecting targets not only for their intrinsic value, but for the broader political, economic, and societal effects that disruption or compromise can produce.
What should organizations monitor?
In the current phase of the conflict, organizations should continue to monitor for indicators that activity is shifting from opportunistic disruption toward deliberate intrusion or access preparation.
Internet-facing infrastructure is often the initial entry point. Elevated scanning or probing of public websites, VPN gateways, remote access portals, cloud services, and email authentication infrastructure may indicate early reconnaissance. While some scanning is routine, sudden increases in probing activity or authentication attempts should be treated as potential precursors to intrusion.
Phishing and social engineering campaigns are also likely to intensify. Threat actors may exploit developments in the conflict by using lures that reference civil defense alerts, battlefield updates, humanitarian messaging, or urgent requests that appear to originate from leadership or trusted partners. In some cases, malicious applications or replicas of legitimate services may be used to harvest credentials or deploy malware.
Credential misuse remains a primary access vector. Security teams should monitor for abnormal authentication patterns, including logins from unusual geographic locations, access at unexpected hours, repeated failed logins followed by success, changes to multi-factor authentication settings, or the creation of new privileged accounts.
Organizations operatingcritical infrastructure should closely monitor activities within their operational environments. Suspicious access to remote management platforms, unusual connectivity between IT and OT networks, or unexpected activity involving engineering workstations or vendor access channels may signal reconnaissance within sensitive systems.
Finally, monitoring the broader information environment can provide early warning and signal the need to increase monitoring. Hacktivist groups frequently use platforms such as Telegram and X to circulate target lists, claim attacks, or release fragments of allegedly stolen data tied to geopolitical events. Tracking these channels can help organizations identify potential targets and strengthen their defensive posture before malicious activity reaches their networks.
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