OpenAI announced Monday  it was expanding access to its frontier models for defensive cybersecurity, detailing different defensive and red-teaming workflows and a new partner program with major cybersecurity product providers.

In a pair of blogs posted Monday, OpenAI said it was updating its Daybreak program  – which provides unreleased frontier models to private organizations and governments for defensive cybersecurity work – and introducing a new model variant.

Daybreak Blue, powered by OpenAI’s ChatGPT-5.6-Sol, would operate with lower cybersecurity safeguards compared to other commercially available models and is described as “a recommended starting point for most defenders” that supports tasks like vulnerability discovery, secure code review, malware analysis, incident response and patch validation. 

Daybreak Red, meant for more advanced red-teaming, would provide access to a new model, dubbed GPT-5.6-Cyber, that the company said is more purpose-trained for finding vulnerabilities and testing (or exploiting) them. The model is also less likely to refuse requests around “dual-use cyber tasks.”

According to OpenAI, the organizations in Daybreak Red will have their use closely monitored and supervised, as GPT-5.6-Cyber is significantly more capable in carrying out malicious cyber tasks than Sol. A security evaluation the company devised tested both models on complex requests, including exploit chain development, authentication bypass, privilege escalation and other hacking tasks. Sol succeeded in 1.5% of the requests, while Cyber completed 95%.

OpenAI said it plans to publish a more detailed system card for GPT-5.6-Cyber at a later date.

“Models running with reduced safeguards carry risks beyond standard model usage, whether from misuse or misalignment,” the company said in a blog. “Despite these risks, we believe that democratizing access to frontier intelligence for defenders is crucial to accelerating and automating cyber defense.”

Additionally, OpenAI announced a partnership program with 16 major cybersecurity providers, saying organizations could access their models through their existing security services. The partners include IBM, CrowdStrike, Accenture, Ernst & Young, KPMG, Palo Alto Networks, Cisco, Cloudflare, Sophos and others. 

“These partners bring deep security expertise and established relationships with organizations around the world,” OpenAI said in its blog. “By bringing our frontier cyber models into their services, we can help more defenders find serious vulnerabilities, validate which ones matter, and fix them faster.”

Companies like OpenAI, Anthropic and others are trying to rebalance their priorities after a string of AI-agent sandbox escapes have rattled policymakers and caused some cybersecurity experts to question if AI companies are doing enough to properly isolate the models from the internet during testing. Last week, OpenAI said it was intentionally slowing down development of its newer “Astra” model in order to develop better guardrails to restrain its behavior.

Cybersecurity and AI experts have told CyberScoop that while AI systems have greatly improved at finding and exploiting vulnerabilities in software code, they still require substantial human guidance and supporting infrastructure to operate as intended.

Additionally, some research has shown that without such guidance, even near-frontier models can struggle to fully patch a discovered vulnerability or avoid introducing new bugs with their fixes.

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U.S. and South Korean cyber agencies warned Monday about a ransomware-as-a-service outfit, Gunra, that reportedly recruits ethical hackers and penetration testers and benefits from North Korean government-linked hackers’ tools to target government and critical infrastructure organizations.

Gunra has gone after sectors such as academia, financial services and insurance, government services and facilities, healthcare, manufacturing and construction, media, retail, transportation and utilities. Its global scope is far-ranging, according to Monday’s alert: Africa, the Americas, the Asia-Pacific, Europe and the Middle East.

“Gunra is another variant in the ongoing trend of ransomware attacks causing disruption and harm to U.S. and international organizations,” said Chris Butera, acting assistant director for cybersecurity at the Cybersecurity and Infrastructure Security Agency, which produced the advisory with the Department of Defense’s Cyber Crime Center, FBI, National Security Agency, Secret Service and Republic of Korea’s National Police Agency.

The alert is part of the #StopRansomware series, a joint FBI-CISA project aimed at network defenders.

The FBI first took notice of Gunra in April of last year. The double-extortion group established a data leak site on Tor to list victims and publish purloined data. By January of this year, Gunra had launched a formal ransomware-as-a-service affiliate and was growing in its ambition, Monday’s alert states.

“The FBI observed the group adopting new branding aliases (notably operating under the name Golden Community) to support this expansion,” it reads. “Gunra has further commercialized its platform by actively recruiting penetration testers and ethical hackers to serve as initial access brokers, offering a share of the ransom profits in exchange for enterprise network access.”

Gunra seeks initial access with known vulnerabilities in internet-facing devices like firewalls or virtual private networks, and is based on or influenced by the Conti ransomware code leaked in 2022, according to the agencies.

Research published in July by a South Korean cybersecurity firm took note of Gunra overlap with Lazarus Group, although it doesn’t explicitly mention the latter group’s name.

“These commonalities suggest that although the state-sponsored threat group and the Gunra ransomware group appear to be separate threat actors with different ultimate objectives, they may have shared certain techniques, tools, and infrastructure or collaborated to a limited extent during the attacks,” AhnLab wrote in its report.

That kind of North Korean government-ransomware gang collaboration dates back to at least 2024. Nor is Gunra alone among ransomware-as-a-service outfits recruiting penetration testers.

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As AI-generated code continues to be injected into all corners of the internet, concerns have risen about an expanding attack surface for malicious hackers to exploit.

Some have argued that the enhanced cybersecurity capabilities of large language models could serve as a check, finding and fixing vulnerabilities nearly as fast as they’re created.

But new research that tested the patching capabilities of two popular commercial models, OpenAI’s ChatGPT 5.5 and Anthropic’s Claude Opus 4.8, found that generative AI is more likely to create an exploitable patch or introduce entirely new bugs than close off a vulnerability.

Researchers at 1Password tested the models ability to patch six “high-impact, high-complexity” CVEs, including the “Copy Fail” vulnerability, a kernel flaw that can give an attacker root access to Linux cloud environments. The overall success rate (or fully patching the vulnerability without introducing new problems), was less than a coin flip at 47%.

“Our research findings show that, in aggregate across a variety of scenarios, both Claude and ChatGPT had a low rate of successful patch generation, which we define as full remediation of all known exploit paths with no erroneous changes to application behavior,” wrote Keith Hoodlet, Axel Mierczuk and Spencer Michaels.

“The models often addressed only a subset of vulnerable code paths, added fragile guard code that satisfied tests while failing to address the vulnerability’s root cause, and sometimes introduced subtle changes in the application’s behavior while patching the immediate vulnerability,” the authors continued.

The research suggests that largely autonomous vulnerability-discovery and patching may not yet be effective in fixing the explosion of vulnerable code that is being created in the AI era.

Other private sector research has pointed to a similar problem. A report this year from Veracode found that while LLMs have made “enormous strides” in crafting workable code, “security is a different story.” Testing across a range of frontier models found the average security “pass rate” for AI generated code is around 56%. Newer models like GPT 5.5 push closer to 70%, while more than half sit between 50-53%.

Veracode tested 100 different models and while there was variability, in general a small number of models were showing progress on security patching while the rest have experienced “stagnation.” Similar to the 1Password research, in 44% of Veracode tests the models introduced a detectable OWASP Top 10 vulnerability into the codebase.

An important caveat: neither report tested newer models, like Anthropic’s Mythos or OpenAI’s GPT-5.6-Sol, that frontier companies tout as having significantly higher cybersecurity capabilities.

Those advanced models can identify and fix vulnerable code. Anthropic and OpenAI are distributing them to key industries through Project Glasswing and Daybreak before foreign or open-source alternatives can compete.

Tim Jarret, vice president of product at Veracode, told CyberScoop that AI tools are still subject to a range of limitations that can make them unreliable for cybersecurity patching without knowledgeable humans in the loop.

While some vulnerabilities – like SQL injections – can be easily patched through automation, other bugs like cross-site scripting, can be exploitable in several different ways and require either a human touch, additional context or both to fully close off. Additionally, models can slowly lose context from prior sessions over time, affecting their ability to complete tasks correctly and raising the possibility they’ll hallucinate to fill in the missing gaps.

“I think we would say, at this point, that Iits premature to treat those as anything other than another code change to the code base that needs to be reviewed and accepted by the team, as opposed to letting the agent merge the code freely,” said Jarrett.

However, he acknowledged that may not be possible in a world where AI agents are generating exponentially more code for human defenders to review. Some kind of automated code review will be necessary – preferably not by the same automation tool that produced the code. The ultimate goal is the same as it has always been in security: “trust but verify.”

“Ninety percent of the time, the human check might just be ‘did the cross check look good?’ Do we have a thumbs up?’” Jarrett said. “In those cases where there’s still something wrong, that’s where you focus your attention a little bit more.”

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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.

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Like seemingly everything else these days, artificial intelligence will re-shape the way voters gather information on candidates running in the 2026 midterm elections.

In some ways, this is already the reality. Voters are increasingly turning to AI chatbots for information instead of Google.  Political campaigns are deploying deepfakes of their opponents. And AI systems have been developed to carry out increasingly complex  hacks.

Since the last major U.S. election in 2024, major tech companies have  embedded AI into their products while hundreds of millions of people have adopted the tools, either by purchasing subscriptions to commercial models or using open-source models. Yet both research and experts state that while AI systems have gotten better at handling basic facts, they’re nowhere near reliable enough to be a main source of  accurate or complete information. 

While chatbots are becoming a primary way that voters gather information on  local races, candidates, issues, and voting information, they are not substitutes for more authoritative sources, like a voter’s state or local election office. 

“I think this is one of the first elections we’re seeing…where AI is just everywhere,” said Thania Sanchez, senior vice president of research and analytics at the nonprofit States United Democracy Center. “Even if you just Google it, [now] the first thing that comes up is the AI overview.”

While AI companies have worked to cut down on errors in their model’s responses for questions around basic election information, they continue to fall short in important ways.

In new research shared exclusively with CyberScoop ahead of its release, States United Democracy Center tested two of the most popular tools — OpenAI’s ChatGPT’s free tier and the AI interface used alongside Google Search — for their performance on a series of basic questions around elections, such as how to register to vote, or a list of candidates in a race.

The models were chosen because they are free and easy to access. For Google AI, the nonprofit tested two types of accounts: ones running in Incognito Mode and ones that had a history of browsing election-skeptical websites.

The nonprofit ran two rounds of testing in 2025 and 2026, collecting nearly one thousand responses from the models submitted by users across six swing states (Arizona, Michigan, North Carolina, Nevada, Pennsylvania and Wisconsin).

In 2025 tests, 6.9% of responses from Google AI and 8.2% responses from ChatGPT“contained verifiable factual errors,” like not listing the correct candidates in a race or false guidance around polling site locations.

However, follow up tests in 2026 across Arizona, Pennsylvania and Michigan found that the error rates in both models had dropped to zero. The study notes that “this is real progress and should be acknowledged.”

But underneath those topline numbers, a more murky picture emerges around the tools’  reliability.

An AI response can sound accurate without actually being complete.  To wit: ChatGPT provided incomplete lists of current gubernatorial primary race candidates 88.9% of the time when queried.

Linking to a state election website – an output the study considers the single most important measure of voter utility  — happened less than 40% of the time. Whether due to formatting issues or the model ingesting outdated information, it’s a problem if voters use them as their primary information source for elections.

“It will be like ‘this person is the Republican candidate and this person is the Democratic candidate’ but it is not telling you there’s also these other third-party candidates,” said Sanchez. “It’s not giving you complete information, so the voter thinks these are the [only] two people running.”

A June survey from the Pew Research Center found that about half of U.S. adults reported having used chatbots at least once, up from a third in 2024, while a quarter reported using them daily. The top use case listed for engaging with the chatbot was searching for information.

Isabel Linzer, an elections policy analyst at the Center for Democracy and Technology, told CyberScoop that voters, campaigns and governments alike are using AI more freely and with fewer restrictions.

Bad actors in the information space have followed suit, and “we are in a phase now of generative engine optimization” where information operations are structured to rank higher in AI model responses.

“We’ve moved beyond [SEO] to [Generative Engine Optimization], and that’s where we’re seeing campaigns thinking about how to structure their materials to make sure that they are in a format that AI models want to use when they’re searching the web…to develop their responses to user queries,” she said.

There is also the underlying problem of frontier AI companies constantly tinkering with their models, their algorithms and the technologies they are intertwined with. . Election officials, by contrast, have decades of experience educating voters about their options.

A prime example of this churn occurred this past February, in between the first and second round of the study, when Google AI suddenly shifted to providing only links for election related queries in incognito mode, replacing the written summaries that showed up in the first round.

Like the study’s authors, Linzer said most people are still best served by going directly to local sources for accurate information on elections. With issues like ideological bias, the potential for bespoke or sycophantic answers for each user based on their prior chat histories and lack of predictability, voters should still be very careful about using AI chatbots as political truth machines.

The best thing that tech companies can do to educate voters is “making sure that for high-stakes situations like elections, that chats are connecting directly to the most important sources, like the website where you can actually register to vote,” said Linzer.

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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.

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Researchers said INC ransomware, one of the most active ransomware groups globally, has been the main attacker exploiting a pair of SonicWall zero-days soon after they were disclosed last month.

The prolific ransomware-as-a-service operation wasn’t the first group to exploit the flaws, which were actively exploited for three weeks before the vendor disclosed and patched the defects July 14, but it has been the most assertive and concerning group to target and chain both vulnerabilities together for full access.

“Since public disclosure, INC ransomware has emerged as the most commonly named threat actor actively weaponizing this vulnerability chain,” Brett Deroche, director of incident response at Rapid7, told CyberScoop. “While Inc is the name driving the post-disclosure wave, we can’t attribute the full body of exploitation to INC specifically.”

SonicWall did not respond to a request for comment.

The SonicWall vulnerabilities — CVE-2026-15409 and CVE-2026-15410 — are the latest in a series of security issues confronting the vendor’s customers, including actively exploited zero-days, previously disclosed defects, and an attack last year that allowed a state-sponsored threat group to steal the firewall configurations of every SonicWall customer. 

Just last week, Huntress researchers spotted an attack spree that compromised 30 SonicWall customers in less than two days. 

Ransomware groups have taken a special interest in SonicWall. Ten of the 17 SonicWall defects added to the Cybersecurity and Infrastructure Security Agency’s known exploited vulnerabilities (KEV) catalog since late 2021 are known to be used in ransomware campaigns.

INC ransomware, which has claimed nearly 900 victims across 71 countries since it was first discovered three years ago, is just the latest financially-motivated group to target SonicWall customers. 

Researchers haven’t determined how many organizations have been impacted by the latest SonicWall zero-days, including attacks linked to INC ransomware. 

“Attribution here isn’t a single clean answer. The earliest exploitation we observed, beginning June 22, traced back to common hosted infrastructure, though those attacks were largely unsuccessful,” Deroche said. 

“INC’s confirmed activity that we’ve observed came after public disclosure, using different infrastructure and moving from initial access to ransomware deployment in short order. That’s a meaningfully different operational tempo and skill level than what we saw pre-disclosure,” he added. 

Deroche said Rapid7 has successfully prevented data theft and encryption in the majority of recent cases, yet noted ransomware was deployed in at least one case the security vendor observed.

Yet, there could be other attacks outside the purview of Rapid7’s telemetry. INC ransomware has listed multiple new alleged victims on its data leak site, including organizations and government agencies in Australia, the United States, the United Arab Emirates, Colombia and Switzerland, Resecurity said in a blog post Saturday.

The company said it has aided several victims with incident response, and learned multiple victims received emails and phone calls from alleged hackers who pressured them to engage in negotiations.

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While AI is supposed to help defenders, it’s now creating more than twice as much noise as human-triggered incidents CrowdStrike detects as potentially malicious. The company’s threat hunting team and systems triaged an average of 14 million detection leads daily, resulting in about 36,000 customer alerts during the one-year period ending in June.

“AI agent-driven behaviors have surged past human triggers,” said Adam Meyers, senior vice president of counter adversary operations at CrowdStrike. “AI has driven the detections significantly above what humans are causing, and this gives you a sense of how frequently AI is being used, and really just that it’s being used everywhere.”

The threat posed by AI showed up incessantly during the past year, sparking alarming shifts and heightened targeting across software defects, open-source supply chains and AI tools themselves — all of which create greater difficulties for defenders, CrowdStrike said in its annual threat hunting report. 

“The AI tools that are being implemented by every enterprise across the globe right now are also creating an extended attack surface,” Meyers said during a press briefing. 

“AI is now a tool, a target, and a force multiplier for adversaries,” researchers wrote in the report, adding that AI-enabled malicious activity surged 89% during the past year as attackers used the technology to scale operations, hasten tradecraft and target AI infrastructure.

Attackers are using frontier AI models to uncover vulnerabilities and develop resources, including AI-generated scripts, payloads and commands that increase their effectiveness and efficiency. The technology also allows threat groups to design more creative ways to run automated attacks and boost impact by manipulating, interrupting or sabotaging AI systems and data.

“AI is both the weapon and the target,” Meyers said. 

Most organizations don’t view it as such, and thus far haven’t secured or put proper guardrails around the AI tools they use or address the ways attackers can use AI against them, he added. 

AI’s mark on vulnerabilities is particularly concerning, as reflected by what Meyers described as “one of the scarier stats” in this year’s report: 88% of vulnerabilities were weaponized through AI within 48 hours. 

“This is creating a rich ecosystem of vulnerabilities for attackers to use against various systems,” he said. It also renders the 30-day patch window obsolete, forcing organizations to struggle under a new baseline patch cycle of 24 to 48 hours, according to Meyers.

The AI ecosystem also became the next software supply chain battleground during the past year, as evidenced by TeamPCP’s rampage through open-source software in the first half of this year. 

The threat cluster compromised more than 300 software dependencies in one day, Meyers said. 

AI tools are already in the crosshairs and the attack surface will continue to grow as agentic systems, AI application integrations and dependency managers for AI agents proliferate, the report concluded.

“The same AI tools driving modern businesses are creating under-defended attack surfaces that adversaries are exploiting,” Meyers said. “We have to secure AI. This is absolutely critical.”

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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.”

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AI systems like Anthropic’s Project Glasswing and Microsoft’s MDASH are aiding in the discovery of vulnerabilities, filling the ever-growing pool of defects that defenders have to address before exploitation occurs. Yet, through the first half of 2026, these vulnerabilities were no more or less likely to be exploited than all vulnerabilities disclosed during that period, VulnCheck said in a report Tuesday. 

Concerns remain high about AI-discovered vulnerabilities fueling more attacks, but VulnCheck’s review of exploitation data shows that those fears are unfounded, at least so far. 

Patrick Garrity, security researcher at VulnCheck and report author, identified 1,061 vulnerabilities attributed to AI-assisted discovery during the first six months of the year. Of those vulnerabilities discovered by AI, 14 ( 1.3%) were exploited in the wild, a breakdown that aligns with the exploitation rate researchers observed across all vulnerabilities during the same period. 

“While AI-assisted vulnerability discovery clearly has value for both attackers and defenders, the data does not suggest that AI discovered vulnerabilities are inherently more likely to be exploited than those found through traditional methods,” Garrity wrote.

While AI’s contribution to actively exploited vulnerabilities was muted in the first half of the year, it’s too soon to assume that trend will continue. Moreover, none of these major vulnerability-hunting models were running for that full period. Project Glasswing rolled out in April, while Microsoft’s MDASH and OpenAI’s Daybreak were both unveiled in May.

The upward trend in Microsoft’s monthly Patch Tuesday indicates how much the floodgates might open through the remainder of the year as AI models discover more vulnerabilities. The company’s July security update contained an all-time-record of 622 vulnerabilities, besting the previous record-breaking June update with 206 vulnerabilities.

VulnCheck’s state of exploitation report also found that vulnerabilities were exploited much faster after CVE publication, speeding up from an average of 120 days in 2025 to 80 days during the first half of the year.

The intelligence firm also determined which technology categories were actively exploited most often. Content management systems accounted for nearly one-third of the 495 known exploited vulnerabilities VulnCheck identified during the first half of 2026. Network edge devices were responsible for almost 14%, followed by operating systems at nearly 9%, server software at 8%, and AI products — an emerging attack surface — at almost 6%.

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Botnets powered by residential proxy networks are proliferating, enabling cybercriminals of all types to evade detection by blending in with seemingly legitimate traffic, Lumen Technology’s Black Lotus Labs said in a report Friday.

The global scale of botnets observed by Lumen is currently approaching 60 million victim IP addresses, Chris Formosa, senior lead information security engineer at Black Lotus Labs, told CyberScoop. Roughly 1 in 4 of those compromised IPs are based in the United States, and the true number of infected devices is much greater because there are networks beyond Lumen’s visibility and multiple devices are often unknowingly running a malicious proxy network on the same IP. 

Super-sized botnets are also gaining momentum, according to Lumen, with an average of 10 distinct botnets controlling their own populations of about 1 million active victims daily.

“The only reason these botnets keep getting more and more victims is because there is clearly a market. Aside from criminal activity, who wants access to millions of IPs regularly?” Formosa said. 

That demand for botnets fuels opportunities for growth, reselling, collaboration, and quick rebounds following massive disruptions.

IPIDEA, one of the largest residential proxy networks in operation when its infrastructure was disrupted by coordinated strikes in January, recovered at nearly half-strength within hours and earlier this surpassed its pre-disruption botnet size with a current botnet population of about 10 million IPs, researchers said.

“Their rebuild was eye-opening as they began to rebound from that interdiction,” Ryan English, information security engineer at Black Lotus Labs, told CyberScoop. “Even for how quickly some botnets can rebound, theirs was surprising. We’ve seen them all rebuild, but we haven’t seen anybody do it that fast.”

Meanwhile, botnets are continuously growing, as cybercriminals seek out the cover they provide, more cheap and poorly defended devices hit the market and vendors stop providing security updates for older but still usable products. 

“Your available pool for those proxy hunters grows every year, and it will continue to grow every year,” English said, adding that more than 1 billion devices are currently vulnerable and available to be unknowingly sucked up into botnets.

The challenge for defenders is lopsided, and while disruptions and seizures occur relatively often, botnet operators have formed a global supply chain with pathways that are difficult to break. 

“We have observed multiple residential proxy services collaborating to form what amounts to the largest cooperative network ever seen on the internet,” researchers wrote in the report.

Black Lotus Labs currently tracks more than 30 distinct malicious proxy botnet clusters, and most of those regularly boast more than 100,000 daily victims.

“Our understanding of the various botnets in this space, along with experience in multiple disruptions, leads us to a very important conclusion: taking down a single malicious proxy provider or their botnet in isolation is likely to result in a short-lived solution,” researchers wrote. 

“In recent years, the malicious proxy environment has essentially created the largest collective botnet currently active on the internet, capable of moving millions of IPs within hours to wherever they are needed,” they added. “Until the malicious proxy landscape is properly addressed and regulated on both the private industry and law enforcement sides, this issue will grow and, along with the DDoS botnet landscape, will most likely become a greater problem in the long term.”

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A Russian state-sponsored threat group has been stealing sensitive data from governments and commercial organizations since July 2025 via a novel exploit in popular Linux-based enterprise software, U.S. authorities and cyber officials from more than a dozen other countries warned in a joint cybersecurity advisory Thursday.

Laundry Bear’s most recent espionage campaign involves the exploitation of a zero-day vulnerability in Zimbra Collaboration Suite that wasn’t patched until November 2025, five months after attacks were well underway, officials said. 

The exploit just requires a view — no clicks — and allows attackers to steal the previous 90 days’ worth of email, the account’s password, search history, the victim organization’s email directory, two-factor authentication tokens and other newly created passwords.

“The covert and persistent nature of this activity, along with the absence of any known financial extortion, almost certainly indicates this group’s involvement in espionage activities with Russian government backing,” officials wrote in the advisory. 

“Additionally, extensive Ukrainian targeting, prior to use against U.S. and other NATO allies, outlines an increasing trend within Russian cyber threat groups to target Ukrainian users first—both as a priority target and as a testbench for malicious cyber techniques before broader global deployment.”

The state-sponsored espionage group, also known as Void Blizzard, has compromised governments and organizations in the defense, education, energy, law enforcement, media, finance, transportation and technology sectors. 

Laundry Bear’s year-long campaign involving the exploitation of CVE-2025-66376 showcases more technical capabilities, including a custom JavaScript payload it delivers to targeted victims via phishing emails. The threat group could also likely adapt the novel data exfiltration and aggregation capability, dubbed “beehive,” to exploit other vulnerabilities, officials warned.

The defect’s medium-severity rating of 6.1 underscores the challenge defenders regularly confront in prioritizing patching schedules based on measure of severity alone.

The Russian state-supported group, which has been active since at least 2024, is still actively exploiting Zimbra Collaboration Suite instances that remain unpatched, officials said.

Authorities shared Thursday indicators of compromise, mitigation steps and urged organizations to update their vulnerable software.

“This campaign’s targeted victimology and limited exploitation capabilities likely indicate this group manually identifies and targets the victim organizations” by identifying organizations with public-facing infrastructure, officials wrote in the advisory.

Once a target is identified, Laundry Bear also likely compiles email addresses for users to target with the exploit via phishing emails. Officials did not identify specific victims or describe the volume of organizations already compromised.

The joint cybersecurity advisory was issued by the United States, Australia, Canada, New Zealand, the United Kingdom, Czech Republic, Denmark, Estonia, Finland, France, Italy, Moldova, the Netherlands, Poland, Spain and Sweden.

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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.

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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.

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Frontier AI companies often refer to their models as “helpful assistants” or try to compare them to entry-level employees.  

But new research from the UK’s AI Security Institute reinforces how large language models suffer from a common flaw that would land many human employees in hot water with their employers: they cheat.

In other words, these models are so committed to completing their tasks that they will break the rules, cut corners and deceive  their own users to accomplish them.

“Every model we have tested for this behavior attempted to cheat,” the AISI report said.
“Models did not reliably report this behavior when asked, and often did not reason about it in their chain-of-thought, suggesting that detecting cheating will likely require robust monitoring methods.”

The research tested OpenAI’s ChatGPT 5.4, 5.5 and 5.6 models, along with Anthropic’s Claude Opus 4.7 and Mythos Preview.

The AISI ran models through a series of “Capture-the-Flag” cyber evaluations, where they obtained points by performing offensive cybersecurity related tasks, like exploiting a particular vulnerability or reverse engineering compiled code.

The research defines “cheating” as “taking an action that is out of scope for the task or explicitly disallowed by the rules, in order to achieve a goal through a shortcut, workaround, or unintended solution that the task was not meant to, or should not, permit.”

It captures a range of observed behaviors from models, like searching the internet for solutions, attacking or escalating privileges on unrelated systems, probing evaluation software to gain access to the task solution.

Models also failed to acknowledge when they were cheating to complete a task, and less than 50 percent said the rule-breaking was “wrong” when challenged on it by a user.

A model’s propensity for cheating was not related to its capability, meaning newer or advanced models aren’t more likely to cheat. Rather, researchers think it stems from the techniques used during a model’s training and alignment that are to blame.

But even if rates of cheating remain constant, the problem could still worsen over time. As newer models in the future could become more proficient and learn more effective cheating techniques.

This deception also makes it difficult for labs like AISI to verify their own work, which relies on evaluating trustworthy outputs from AI systems.

The research underscores how AI systems can go to drastic lengths to complete their task, including blowing through or circumventing a company’s IT and cybersecurity protections.

In one instance, AISI researchers said a model was inadvertently given a cyber capability evaluation that was misconfigured and impossible to solve.

“The model tested was so persistent in attempting to cheat that it wrote and ran code on an external service, hosted on the open internet outside of AISI’s systems, in an attempt to access our evaluation infrastructure, triggering a security alert in AISI’s systems,” the report said.

While AISI said there were no data leaks or damage from the incident, the model could have successfully accessed their evaluation system had they not had monitoring in place. The institute said it implemented further controls on internal systems in response to the test.

The researchers said there are “significant consequences” to a status quo where we can’t trust models not to cheat. The behaviors are especially problematic in areas like AI safety and security research, as well as cyber operations and military decision-making, where trust outputs from the AI systems are critical.

Today, AISI said it can detect LLM cheating through a mix of manual review and LLM monitoring, but that may not always be true, and future models may be better at hiding their actions from human overseers.

“A more fundamental fix would be to train the models not to cheat in the first place – but given this kind of behavior was reported in frontier models more than a year ago, robustly aligning it away may not be easy,” researchers wrote.

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The people orchestrating North Korea’s IT worker scheme are funneling money through a web of front companies and intermediaries, including sanctioned entities, that partly fund Russia’s war effort against Ukraine, DTEX said in a report Tuesday.

The security firm’s research shows that the scheme is moving beyond funding the country’s weapons program and into a bigger pool that supports many of the regime’s objectives. This includes manufacturing weapons and supplying them to Russia’s military, according to DTEX.

“When we think IT workers, we typically think head down, get your money, support the weapons program,” Michael Barnhart, nation state investigator at DTEX and lead author of the report, told CyberScoop.

“It’s a broad cover-all statement when we say it’s supplying the weapons program,” he said. “That’s the predominant place it goes,” but many other domestic programs and entities tasked with other projects are taking cuts from that pool of money as well. 

Barnhart corroborated previously leaked data from an internal North Korean payment server, which included 390 IT worker accounts, chat logs and transaction data.

He mapped the transactions to organizations that received those funds, including multiple sanctioned entities: Sobaeksu, Saenal, and Songkwang. 

The money trail also showed $1.97 million in payments from North Korean IT workers between December 2025 and February 2026 flowing directly through Korea Ryonbong General Corp, a sanctioned defense entity that procures weapons for the regime’s military programs.

Western officials previously reported that North Korea provided ammunition and weapons to Russia in 2023, and in the fall of 2024 sent upwards of 15,000 soldiers to fight alongside Russian troops, according to the Council on Foreign Relations.

“This is a consequence that is often overlooked,” Barnhart wrote in the report. “Revenue from the IT worker stream does not stop at a resume scam or a payroll-abuse story. It can feed a larger DPRK system that supports sanctioned entities, domestic state needs, and a Russia war effort that is actively consuming all facets of North Korean weapons and military support.” 

Data from the internal North Korean payment server, which was first published by ZachXBT in April, is controlled by “PC-1234,” a single administrator that DTEX has been tracking for a while. The wallet and its cluster of activity remains active, Barnhart said. 

The three months of previous activity attributed to the wallet amounted to more than $2.84 million, which then flowed upward into dozens of organizations. 

“It’s not a top-down funded regime. It’s a bottom-up,” Barnhart said. “Everyone makes money at the bottom and then they take a tiny cut, and then the money goes upwards to what we just blanketly say is the weapons program. But really, it can go a lot more places.”

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A pair of young men were sentenced to 66 months in jail for committing a cyberattack on the Transport for London that brought the network’s operations to a standstill in 2024, the United Kingdom’s National Crime Agency said Thursday.

Thalha Jubair and Owen Flowers were arrested at their homes in September 2025, barely a year after the attack, and pleaded guilty last month just as their trials were set to begin. Flowers was previously arrested in connection with the attack in September, but was released after questioning by officers.

Jubair and Flowers were leading members and highly involved in Scattered Spider, a nebulous hacker subset of The Com, according to researchers. The 20-year-old Jubair was a prolific cybercriminal and core member of the unbound collective. 

U.S. authorities last year accused Jubair of direct, prominent involvement in at least 120 cyberattacks, including extortion of 47 U.S.-based organizations and the January 2025 attack on the federal court system. 

Officials said they traced a combined total of at least $89.5 million in cryptocurrency, at the time of payments, to Bitcoin addresses and servers controlled by Jubair. Two financial services firms paid Jubair $25 million and $36.2 million, respectively, in Bitcoin between June and November 2023, according to an unsealed criminal complaint against Jubair. 

At the time of Jubair’s arrest, “he was one of the four principal people that we associated with Scattered Spider,” and one of the two most core players, Adam Meyers, senior vice president of counter adversary operations at CrowdStrike, told CyberScoop. 

Jubair and Owens had significant resources and support, and “victim payments were reinvested back into the enterprise,” said Allison Nixon, chief research officer at Unit 221B. 

The lasting impact of Jubair and Owens’ capture and imprisonment remains hazy.

U.K. authorities insist Jubair and Owens’ arrests and punishment “effectively halted the group’s criminal activity,” yet they added that other cybercriminals continue to use the Scattered Spider brand in more recent attacks. 

Thursday’s announcement “represents a significant step in holding accountable two members of Scattered Spider, a group that has repeatedly relied on data extortion, SIM-swap attacks, and other social engineering techniques to infiltrate networks and undermine critical services,” Brett Leatherman, assistant director of the FBI Cyber Division, said in a statement. 

The FBI also noted, in a LinkedIn post, that members of Scattered Spider “continue to victimize organizations around the world and cause significant financial and operational harm.”

When Owens, now 18, was first arrested for the Transport for London attack in 2024, investigators said he was “in the process of hacking the systems of U.S. health care companies SSM Health Care Corporation and Sutter Health, which had been infiltrated and damaged.”

Officials also said Jubair and Owens failed to cooperate after their arrests. 

“This is the largest cybercrime prosecution ever brought before the U.K. courts and the culmination of nearly two years of painstaking work,” Paul Foster, head of the National Crime Center’s National Cybercrime Unit, said in a statement. 

“Scattered Spider has been the most significant cybercrime threat to the U.K. in recent years. Through this investigation, we have severely disrupted that threat and brought key offenders to justice,” Foster added.

Despite the upbeat reaction from U.K. officials, Nixon said the punishment for Jubair and Owens is “remarkably lenient considering the period of continuous reoffending lasted longer than the sentence.”

Nixon hopes the United States will eventually extradite the pair to face additional charges. “If that happens, they won’t be able to use mental illness as a loophole to get back to harming society as soon as possible,” she added.

“No one who worked on their case was surprised they would reoffend, and there seems to be no allowance in the law to protect the public from what everyone knew was going to happen,” Nixon said. “I know the narrative in the cybercriminal culture will glorify them, but they wouldn’t if they knew the full story.”

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Cyberstalkers are increasingly exploiting a feature in Google Chrome meant for mobile phone user convenience, but can give intruders broad access to a device owner’s private information, according to researchers.

Certo Software said in a blog post Tuesday that stalkers are making use of Chrome’s sync capability — meant to make it so signing into Chrome on one device makes it easier to do so on other devices, too — to spy on a phone owner’s browsing history and gain access to their stored passwords.

As an illustration, Certo used the case of a pseudonymous victim, Emma, who had searched for a family lawyer and visited a domestic violence support website while her partner was sleeping, only for him to bring up to her two days later.

“Emma had been careful to only ever use her own device, and she hadn’t noticed any new apps appear on her phone,” wrote Certo co-founder Russell Kent-Payne. “What she didn’t know was that weeks earlier, during a few unattended minutes with her phone, he had opened the Chrome app and quietly signed it into a Google account of his own. From that moment on, every site she visited was being copied straight to his account, viewable from any device, anywhere in the world.”

The surveillance is as easy as that: brief access to a phone, signing into a Google account and making sure sync is turned on for that account.

Eva Galperin, director of cybersecurity at the Electronic Frontier Foundation, said on the Bluesky social media app that Certo’s research serves as “an important reminder that tech-enabled abuse isn’t just limited to stalkerware.”

Certo said that Google could do a couple things, such as providing a temporary notification whenever a new account is added or sync is turned on or offering a regular marker to indicate when sync is active and which account it’s syncing to, to protect users.

Google did not respond to multiple requests for comment about Certo’s findings.

But the uptick in usage of that stalking method could be a byproduct of security successes elsewhere in the fight against spyware, Certo said.

“Modern smartphones are harder to compromise than ever. Regular security updates, stricter app store rules, and on-device threat detection have made traditional spyware a much riskier bet for a cyberstalker than it used to be,” Kent-Payne wrote. “As a result, we’re increasingly seeing abusers turn to something far simpler: the legitimate apps already sitting on their victim’s phone. No installation, no suspicious permissions, no telltale battery drain — just a quiet misuse of a feature the victim never knew existed.”

At the same time, Chrome is the world’s most popular browser, and this isn’t the first time security concerns have popped up about its sync feature, among other worries.

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SonicWall customers are attempting to dodge another security challenge as attackers are exploiting a pair of zero-day vulnerabilities that have been confirmed by the vendor. 

The company publicly disclosed the vulnerabilities — CVE-2026-15409 and CVE-2026-15410 — in a security advisory Tuesday. SonicWall credited an employee with discovering the defects, but it hasn’t said when the discovery occurred or the earliest known instance of exploitation. 

Rapid7 researchers told CyberScoop both vulnerabilities were first exploited June 22. “From the cases that our team has observed, the goal is likely ransomware, though we have prevented the actors from achieving exfiltration and encryption,” said Seth Lazarus, senior manager of detection and response services at Rapid7.

Overlapping tactics, techniques and procedures from the attacks observed by Rapid7 indicate the same threat group or attacker discovered and exploited the zero-days, Lazarus added.

SonicWall did not answer questions about the impacts of these attacks thus far, and the company hasn’t attributed the attacks to a known group or described the attacker’s origins and motivations.

The vendor did, however, confirm to CyberScoop that both vulnerabilities have been chained together for exploitation. The vulnerabilities affecting SonicWall SMA1000 appliances, including a max-severity defect that allows attackers to make authenticated requests and a 7.2-rated vulnerability that allows authenticated command injection.

“When these two are chained, an attacker can go from zero access to a complete system compromise for the affected appliance,” said Landon Rice, senior exploit developer at VulnCheck.

Ben Harris, founder and CEO at watchTowr, said two characteristics of the vulnerabilities fuel a sense of dread. “Both were exploited as zero-days before fixes were available, and together they offer a plausible path to remote-code execution from the internet,” he said.

The Cybersecurity and Infrastructure Security Agency added both zero-days to its known exploited vulnerabilities catalog Tuesday. 

SonicWall encouraged customers to patch the vulnerabilities by upgrading to the latest software version, which it released upon disclosure, and shared some indicators of compromise to help customers hunt for potential malicious activity on their systems.

“Speed of response was a priority for us,” said Bret Fitzgerald, senior director of global communications at SonicWall. “Within days of becoming aware of the issue, our team had developed a script that we can run on behalf of affected customers to assist with resolution, and mitigation efforts are already underway.”

SonicWall and third-party researchers haven’t said how many SonicWall customers are impacted by the exploited vulnerabilities, but the vendor did say it already investigated multiple cases of active exploitation. 

Fitzgerald said the company monitors about one million sensors globally and “SMA1000 appliances represent a very small subset of that footprint, less than 5,000 units.”

SonicWall said support staff are also helping customers work through instances of suspicious activity, warning that patching alone is not sufficient. 

The vendor and its customers have been hit by a barrage of actively exploited zero-days and previously disclosed defects in SonicWall devices for years. In 2025, an undisclosed state-sponsored threat actor intruded the company’s cloud environment and stole firewall configurations of every SonicWall customer. 

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.

“As always,” Harris said, “when something is confirmed as already exploited in the wild, patching is the bare minimum, and breach should be assumed.”

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Microsoft’s monthly Patch Tuesday security program reached an unrivaled pinnacle this month, as the vendor addressed 622 vulnerabilities across its suite of business products and systems. 

“The bug apocalypse has finally descended upon us,” Dustin Childs, head of threat awareness at Trend Micro’s Zero Day Initiative, wrote in a blog post Tuesday.

“The mother of all releases. To call this record-breaking is an understatement,” he added. “The CVE count year-to-date exceeds all other years’ totals.”

The startling increase in vulnerabilities reflects a compounding effect taking root across software as artificial intelligence plays a growing role in discovering and developing patches for defects lurking in error-riddled applications. 

Microsoft’s June Patch Tuesday update broke the previous all-time record with 206 vulnerabilities.

The company last week warned forewarned customers and defenders that a flood of defects would be uncovered as it applies its multi-model agentic scanning harness (MDASH) to discover and address vulnerabilities at greater speed and scale.

The monthly exponential rise in Microsoft vulnerabilities already puts the vendor on pace to break a full-year record, ending 2026 with the largest annual collection of defects, beating the previous record of 1,245 CVEs in 2020, Satnam Narang, senior staff research engineer at Tenable, said in an email. 

“It’s probable that we will not only exceed 2,000 CVEs in a calendar year, but potentially over 3,000 CVEs this year or more,” he added.

“The volume is striking, but it reflects how good these tools have become at finding bugs, not how many of those bugs actually pose a risk to organizations,” Narang said.

Microsoft disclosed two actively exploited zero-day vulnerabilities — CVE-2026-56155 and CVE-2026-56164, privilege escalation defects in Active Directory Federation Services and Microsoft SharePoint Server, respectively. 

The monthly batch of patches included 416 defects in Windows, 82 in Office and 46 in Microsoft Edge. More than 1 in 10 vulnerabilities the vendor disclosed — 63 total — were rated as critical.

“The products covered this month are also astonishing,” Childs said. “Just about everything you’ve ever heard of is getting patched.”

The full list of vulnerabilities addressed this month is available in Microsoft’s Security Response Center.

SAP also addressed a fresh assortment of vulnerabilities Tuesday, including critical defects CVE-2026-44747 in SAP NetWeaver Application Server and CVE-2026-27690 in SAP Approuter.

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