In a novel maneuver for a disruption operation against cyber attackers, industry and law enforcement teamed up to conduct a court takedown of two widely-used criminal tools at once rather than individually, Microsoft said Tuesday.

The takedown simultaneously went after Amadey, a botnet that can serve as a malware delivery system, and StealC, an infostealer. Cybercriminals often use them in conjunction and they rely on the same infrastructure, Microsoft said.

“When multiple parts of an operation are disrupted together, attacks are harder to launch, scale, and recover from,” said Steven Masada, assistant general counsel for Microsoft’s Digital Crimes Unit. “The result: fewer disrupted services, fewer opportunities for cybercriminals to profit, and more friction when they try to rebuild. It’s no longer enough to go after threats one by one. We need to interrupt how the attacks are put together.”

Microsoft had been tracking Amadey with ESET, BitSight, Lumen and Mitsui Bussan Secure Directions. Meanwhile, Europol had been investigating StealC alongside law enforcement partners including Germany’s Federal Criminal Police Office and the Dutch and Danish National Police as well as IBM X-Force and Proofpoint.

They then joined forces and turned to the Racketeer Influenced and Corrupt Organizations (RICO) Act, used to help authorities go after organized crime, to disrupt more than 200 command-and-control servers. Microsoft said it gained insights from its artificial intelligence product Copilot that “allowed the legal team to treat both malware families as part of a single criminal conspiracy.”

Microsoft regularly leads court-authorized disruption operations, but the industry and law enforcement partnerships combined with AI to expand data collection and identify connections beyond what one company could normally do, it said.

Amadey and StealC were linked to more than 140,000 infected computers around the globe in the first week of May alone, the company said. StealC has ranked among the top infostealers for years since its emergence in 2023 and sells in underground forums as a malware-as-a-service. It’s typically used by Russia-linked groups.

Amadey dates back to 2018, and is also commonly employed by Russian groups, including in attacks on Ukraine.

Their interaction shows the assembly line-like structure of modern cybercrime, Microsoft said. Even if the cybercriminals behind both tools never coordinate, their tools are designed to work together, it said.

“StealC is an infostealer that collects sensitive data from browsers, cryptocurrency wallets, messaging applications, email clients, and gaming platforms,” the company wrote in a separate blog post. “It is a malware-as-a-service (MaaS) offering that threat actors use to generate customized payloads and manage stolen data through a centralized web panel. Meanwhile, Amadey is a MaaS loader that threat actors use to deliver StealC and other malware. Modular, pay-as-you-go models like StealC and Amadey allow threat actors to use a single initial infection to quickly escalate into multiple other threats.”

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An epidemic of cyberattacks on open-source software has mounted in recent months, making clear how uniquely difficult it is to protect the publicly available code, from both a policy and a technical perspective, that serves as the foundation for so much of the digital world.

While open-source software security got a boost in attention under President Joe Biden — whose administration grappled with the fallout from the potentially catastrophic Log4j flaw that emerged in 2021 — a number of open-source experts say that government protection efforts have suffered setbacks under President Donald Trump. Many also say companies that heavily rely on open-source software, which is basically all of them, haven’t shouldered enough of the responsibility for safeguarding it.

“What we’re seeing is years of lack of investment sustainment in open-source software that is finally starting to catch up to us, where it seems like every week there’s a new supply chain compromise,” said Jack Cable, who held a role at the Cybersecurity and Infrastructure Security Agency where he worked on open-source security before departing under Trump.

The advancements of frontier artificial intelligence models stand to exacerbate the risk further, while simultaneously illustrating what makes defending open source difficult: Project Glasswing said shortly after its announcement that it had uncovered 6,202 high- or critical-severity vulnerabilities in a scan of more than 1,000 open-source projects, but that it had disclosed only 502 of them to open-source project maintainers and only 75 had been patched as of May 22 (albeit some due to typical patching lagtimes).

At the same time, there are questions about how much the government can help, even as overseas governments seek to focus on open-source security.

The evolution of open-source risk 

There are a series of factors contributing to the current threat to open-source software, experts say.

One is simply that attackers go to the area where they can get the highest return on their work. Compromising open-source software gives them the chance to get into the supply chain and exploit additional targets.

“Twenty years ago, open source was still fairly niche,” said Æva Black, who also worked on open-source security at CISA but left when Trump came back into power. “The potential blast radius if you managed to compromise open source was relatively small, because back then the world didn’t run on open source. Now almost everything runs on open source,” she said, from modern cars to satellites.

Another part is the nature of open-source software itself.

“It’s a symptom [of having] lots of open source [that] is a little bit under-maintained or not cared for enough, so that we spend too little effort and money and infrastructure on them,” said Daniel Stenberg, who is the creator and maintainer of cURL, a popular open-source project. “Lots of open source is being maintained by small teams, lots of volunteers, and I think that that’s a tough situation.”

That doesn’t mean the maintainers are to blame, Stenberg said. The companies that rely on open-source need to be diligent about using it, Black said.

“What we’re seeing in that realm right now is not new; it is more advanced and far more widespread,” she said. “The problem remains that companies who use open source — because open source is by far the most efficient way to collaborate on non-product value features — most companies are not implementing a responsible and safe utilization pathway.”

Open-source projects lack a systematic way to handle coordinated vulnerability disclosures, unlike companies or industry groups with formal processes, said Dan Lorenc, CEO and co-founder of Chainguard. Project maintainers sometimes aren’t reachable, and those who are available are flooded with reports, many of them unverified findings from AI tools that waste their time without adding value..

Of course, some of those vulnerability reports turn out to be legitimate. “Mythos and AI models have contributed to an uptick in the number of vulnerabilities and things that we’re able to find” in open-source software, said Alex Zenla, chief technology officer for the cybersecurity company Edera.

All of that leaves more room for companies, non-profits and world governments to improve open-source security.

A moment of momentum

While open-source software security isn’t a new issue, the 2021 discovery of the Log4j flaw sounded alarms within the cybersecurity community. Jen Easterly, then the director of CISA, called it “one of the most serious I’ve seen in my entire career, if not the most serious,” with the potential to affect hundreds of millions of devices given the ubiquitous nature of the popular open-source logging library.

A year later, the Cyber Safety Review Board released its report on the incident, concluding that swift action from industry and government averted a disaster. But the incident “called attention to security risks unique to the thinly-resourced, volunteer-based open source community,” it wrote. “This community is not adequately resourced to ensure that code is developed pursuant to industry-recognized secure coding practices and audited by experts.”

The U.S. government actions after included some steps focused specifically on open-source software such as creation of the Open-Source Software Security Initiative and hires of well-regarded open-source security experts at CISA such as Black, but also some steps that could be applied more generally and still help with open-source security, such as greater promotion of secure-by-design, memory-safe languages and software bills of materials (SBOMs).

Some of the Biden administration work on open-source security started before Log4j, such as provisions from an executive order he issued in 2021 that directed CISA along with the Office of Management and Budget and General Services Administration to issue guidance to agencies. 

The administration’s 2023 cybersecurity strategy also stepped into the long, thorny discussions over software liability, with a mention of open-source security: “Responsibility must be placed on the stakeholders most capable of taking action to prevent bad outcomes, not on the end-users that often bear the consequences of insecure software nor on the open-source developer of a component that is integrated into a commercial product.“ The Biden administration always indicated that addressing software liability would take a prolonged battle ahead.

Under Trump, many of the Biden administration’s efforts have languished. CISA’s splashy hires on open-source are gone, including Black, Tim Pepper and Anjana Rajan. Also departed are leading figures on secure-by-design and SBOMs, with CISA personnel cutbacks slicing deep. 

No one has seen any sign that the national cyber director-led Open-Source Software Security Initiative is active, with few participants remaining in government today. The Trump administration cyber strategy doesn’t mention open-source.

“The loss of open-source experts at CISA “is unfortunate, and it will be hard for the government to try to rebuild capacity, but I do think now more than ever CISA has a core role to play to secure open source software,” Cable said.

The pressure is mounting

It’s not that the issue is getting zero attention from those in a position to make a difference. Nick Andersen, the acting director of CISA, said last month that open-source security was an area of particular concern for him.

Andersen responded to concerns about CISA staffing levels on open-source security and spoke more broadly on the topic in a statement to CyberScoop.

“As artificial intelligence and other technologies have the power to transform how vulnerabilities are discovered and exploited, CISA recognizes that the open source software (OSS) that underpins much of the nation’s critical infrastructure will need to be hardened,” he said. “CISA actively collaborates with our partners on shared priorities, including OSS security, to ensure time and resources are spent where they matter the most.  We have an immensely talented team, but are also accelerating our hiring in critical areas, to strengthen the nation’s defenses against cyber threats.”

The Office of the National Cyber Director did not respond to requests for comment.

There’s been some activity on Capitol Hill, too. The Securing Open Source Software Act, which Cable worked on during a stint as a Senate staffer, would direct CISA and other agencies to take actions to mitigate open-source software security risks, but the legislation has stalled since its introduction in 2022. A portion of the bill, however, was included in the Department of Homeland Security funding law Trump signed in April, directing CISA to brief Congress on the value of establishing something like an open source program office, which some companies use to manage open source within a given firm.

Senate Intelligence Committee Chairman Tom Cotton, R-Ark., has pushed the executive branch to improve its awareness of foreign adversaries playing roles in open-source software used by national security-focused agencies.

The annual defense policy bill in the House calls on the Defense Department’s chief information officer to report to Congress on a plan to secure open-source software supply chains, saying lawmakers are “concerned that the Department lacks sufficient visibility into the origins, maintenance, and security of OSS applications and software dependencies.”

That defense authorization bill language is “really beneficial, and I think it signals acknowledgement of this changing of culture” around open-source security risks, said Hayden Smith, founder of HuntedLabs, whose company won a contract with the Space Development Agency on supply chain security — agency work that the defense bill singled out.

“The report language is the first time the Hill is trying to get a true handle on foreign influence in open source code where they have oversight,” he said, saying it was a “piece of the puzzle” along with Cotton’s letter and a memo from Secretary of Defense Pete Hegseth last year about foreign influence in the Pentagon supply chain. “It’s good and would trickle down into everyone who provides software to the department.”

Zenla, though, believes trying to isolate China from open-source systems isn’t in and of itself a good idea. 

“I don’t think that that makes a lot of sense, because they’re actually pretty good things that people contribute to open source,” she said. “Not everyone is malicious, and what are we going to do, spy on every single open source maintainer?” It’s more about doing things like making sure that highly-classified systems are set up in a separate way, she said.

Europe is also taking action to secure open-source software that the United States doesn’t seem ready or willing to do right now. Germany, for instance, devotes grants to the security of open-source projects, although Stenberg pointed out that sometimes money doesn’t equate to maintainers being able to fix flaws more quickly, depending on the project’s size.

The Cyber Resilience Act (CRA) adopted by the Council of the European Union in 2024 could offer another road on open-source security. The CRA requires those who use open-source software products as part of any commercial activity to take certain security measures. 

Black said that when she was at CISA, there were discussions between the agency and European counterparts about finding compatible ideas on open-source security, but that momentum died with the Trump administration.

But “Europe kept rolling, and now has in place a new legal framework that is set to really reshape open-source security for potentially the whole world, but certainly for anyone who wants to work with Europe on open source,” she said.

Lorenc recently wrote that “open source isn’t governable.” He said an organization like a neutral nonprofit, possibly using some government funding, should take responsibility for things like coordinating vulnerability disclosure into one pipeline. He also said there needs to be one authority in charge of “forking” — that is, taking a project and assigning stewardship elsewhere — when a maintainer isn’t responsive to vulnerabilities. 

There are differing opinions on how much past government warnings, advisories and guidance have helped. Smith gave some credit to government agencies that “have all responded to open source attacks using the means they have.”

Stenberg said that “I don’t think they make any big dent at all in the big scheme of things.” They might get some attention initially, “then two years later we all forgot about them, and they actually didn’t change much.”

Ideally, everyone could get on the same page, Zenla said. “The best way to do this is if people actually collaborated on a global scale on some sort of regulation around this, but that seems nearly impossible at the current moment,” she said. (The United Nations’ Open Source Week runs all this week.)

But if there’s an upside to the spate of attacks on open-source software, it’s the energy it gives to how better to secure it, Lorenc said, invoking the political saying to never let a good crisis go to waste.

“Everyone knows the industry has to change,” he said. “This is a really good crisis, and the right things are happening in the right places, and organizations are rethinking their culture around software development, and they know what they have to do. It’s just something that’s never been top of the priority list for the last 10 years. Now it is, and they’re doing it, and it’s, ‘Can we do it fast enough?’”

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Intelligence agencies for the United States, Canada, UK, Australia and New Zealand are warning that advanced AI models capable of wreaking havoc in the cyber domain are “months away” from being publicly available.

In a joint statement, the Five Eyes alliance say they expect the kind of advanced hacking capabilities provided by frontier models like Anthropic’s Fable 5 and OpenAI’s Daybreak to become broadly available the public within the year, despite efforts by AI companies to withhold them or restrict their access.

“Frontier Al models are anticipated to exceed current industry expectations, fundamentally transforming both offensive and defensive cyber capabilities,” the agencies said. “The timeline is not years, it is months.”

The statement, which included signatures from NSA’s Director of the Cybersecurity Directorate David Imbordino and acting CISA Director Nick Andersen, does not specifically cite secret or classified sources or methods to reach this conclusion.

But much of the underlying justification provided by the intelligence agencies also aligns with what public cybersecurity and AI experts have been warning about for months.

AI models capable of exploiting cybersecurity weaknesses are already available today through multiple channels: older commercial models, open-source versions, or foreign and black-market sources. And while newer models like Mythos are reportedly significantly more powerful for cybersecurity-related tasks, the breakneck pace of frontier model development often means that yesterday’s restricted frontier AI is tomorrow’s free, open-source AI.

Representative Andrew Garbarino, R-N.Y., Chair of the House Homeland Security Committee, said the warning from intelligence agencies “underscores what the Committee has repeatedly heard through roundtables, briefings, and hearings with industry leaders: China is just months, if not now weeks, away from achieving frontier AI capabilities comparable to those of the United States.”

“This threat reinforces the urgency of ensuring that federal agencies and critical infrastructure operators can responsibly leverage advanced U.S. models, and receive the guidance and support necessary to do so, to find vulnerabilities before adversaries can exploit them,” said Garbarino in a statement.”

The agencies flag legacy systems, sluggish patching loops, unnecessary internet connectivity, weak identity and access controls, and a lack of pre-incident planning by organizations as key weaknesses that AI will excel at exploiting.

“The rapid pace of frontier AI development means cyber risk assumptions can become outdated in months, not years,” the agencies wrote. “We must act before and be prepared to adapt and withstand evolving threats.”

Since large language models burst onto the scene, open-source models have run about 6-8 months behind the largest frontier AI companies.

To give an idea of how quickly the field develops: the capabilities described in the Amazon threat intelligence report that convinced the Trump administration to place export controls on Fable 5 could already be accomplished through older models like Claude Opus and Claude Sonnet, as well as open-source Chinese models.

Anthropic shut down access to their Fable 5 and Mythos 5 models as a result, and despite releasing a statement that they believe the White House decision was a “misunderstanding” the dispute remains resolved.

Programs like Anthropic’s Project Glasswing and OpenAI’s Trusted Access for Cyber Program provide AI systems to organizations for cyberdefense.  The goal is to give defenders a head start in finding and fixing vulnerabilities before AI systems can exploit them routinely in the coming years.

However, for all the fear surrounding the new technology, the recommended guidance is largely the same as it has been for decades. Governments, businesses and leaders must stop treating the digital security of their work as an afterthought or compliance issue.

“Success will come from getting the basics right, acting quickly, and integrating cyber security into core business strategy,” the agencies wrote. “Those that do not will face growing operational and strategic disadvantage.”

06/23/2026: This story was updated to include comment from Rep. Andrew Garbarino, R-N.Y.

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The Senate Judiciary Committee approved a new bill this week that seeks to prevent unauthorized deepfakes of American artists, performers and public figures. While the bill sailed through a committee voice vote, both Senators and outside groups say they’re worried it could become a tool for the powerful to quash free speech. 

The NO FAKES Act, introduced by Sens. Chris Coons, D-Del., and Marsha Blackburn, R-Tenn., would give Americans near-exclusive rights to their own digital AI replicas, and those rights live on, passing to heirs, executors and estates for at least 70 years after an individual dies.

While living, creators would be able to essentially license their likeness and image to others, over 10-year contracts for adults and 5 years for minors.

It would also permit individuals to sue anyone who uses their AI-generated image without permission, and pay up to $750,000 for violations. Blackburn submitted letters of support for the bill from more than 40 groups, including the Screen Actors Guild – American Federation of Television and Radio Artists, the American Medical Association, Creative Artists Agency, the Broadcasters’ Associations and the Human Artistry Campaign.

“It is imperative that we put this national standard in place for voice and visual likeness protection of creators, to protect from proliferation of harmful AIgenerated deepfakes that are created without their consent,” said Blackburn in a Thursday markup of the bill.

The introduction of consumer-grade AI tools has made it trivial to create convincing deepfakes of real individuals and public figures. The harms are well documented: bad actors have used them to create nonconsensual pornography or sexualized media of people they know, create child sexual assault material (CSAM) , and blackmail or humiliate individuals.

Artists have faced real challenges in the AI era when it comes to controlling their digital likeness. Last year, the Better Business Bureau warned that its Scam Tracker had been flooded with complaints about AI-celebrity endorsement scams. These included  deepfakes of Oprah Winfrey promoting weight loss products, Kim Kardashian pleading for donations to fight California wildfires, and pop star Taylor Swift and celebrity chef Gordon Ramsay endorsing cookware.

In the political arena, candidates now create deepfakes of their political opponents, putting words into their mouths or placing them in embarrassing or humiliating situations. Online, disinformation actors have repeatedly spread AI-generated videos and images of politicians like Donald Trump, Kamala Harris, and even regional or local politicians saying or doing scandalous things.

The bill represents one of the most aggressive attempts by U.S. policymakers to protect the digital commercial rights of artists and public figures. New York, for instance, passed a law this month that requires film and television advertisers to publicize when they’re using deepfakes in ads, but does not create a similar copyright regime for artists’ likeness. A Tennessee law, The ELVIS Act, that prohibits the unauthorized use of an individual’s voice and likeness and creates secondary liability for large platforms that publish or distribute the content.

The NO FAKES Act faces opposition from an alliance of tech business and digital rights groups. They argue the bill  fails to balance the commercial rights of artists to control their own image with longstanding First Amendment constitutional rights to free speech and parody.

Amy Bos, vice president of government affairs at NetChoice, a trade association for online businesses, said that while her group supports legislation that prevents unauthorized AI generated deepfakes, “good intentions do not make good law.”

“As written, this bill creates a dangerous financial incentive for platforms to aggressively over-remove lawful content, burdens creators with an unworkable counter-notification system, and fails to deliver the uniform national standard its sponsors promised,” Bos said in a statement.

Many digital civil groups agree with that view. A broad coalition of policy groups – including the American Civil Liberties Union, the R-Street Foundation, the Center for Democracy and Technology, the Electronic Frontier Foundation and others – wrote to the Senate Judiciary Committee this week to urge members to oppose the bill in its current form.

They argued the current bill creates a “Heckler’s veto” over most online content, allowing artists, public figures and advocacy groups to flood the notification system with takedown requests for content they don’t like. Similar to a law already on the books, the Digital Millenium Copyright Act, virtually all the incentives in the bill push platforms to be overaggressive in taking down content, regardless of whether it violates the law or not.

This approach could end up quashing not just unauthorized ads but also scores of other likely First Amendment protected uses, such as education, humor, satire and parody.

In 2023, a humorous AI-generated image of Pope Francis in a puffy Balenciaga jacket went viral. Under the NO FAKES Act, the coalition says that post would be illegal for anyone to post until nearly 2100.

In the political arena, both Republicans like Trump and Democrats like California Governor Gavin Newsom have used AI deepfakes to skewer their political opposition.

“A law that undermines free expression will struggle to survive constitutional review,” the groups wrote. “In the meantime, it can do lasting damage, both to lawful speech and to the autonomy of the people it claims to protect. We urge the Committee not to advance the NO FAKES Act in its current form, to examine how existing state and federal law already addresses the legitimate harms the bill seeks to address, and to pursue narrowly tailored solutions only where a genuine gap remains. We would welcome the opportunity to assist.”

While the bill passed by voice vote and with broad support, multiple Republican and Democratic members of the committee said they had similar concerns and expressed a desire to continue tweaking the bill further before passage into law.

In the Senate meeting, Coons appeared to dismiss those charges, arguing that changes made to the bill ahead of markup adequately address any First Amendment concerns.

“I want to be clear, NO FAKES includes features that protect free speech,” Coons claimed. “Parody, satire documentaries, biopics, newscasts, they’re all protected and we built in appropriate counter notification processes and exempted research libraries and archives.”

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TeamPCP is on a rampage through open-source software.

In less than four months, the threat actor has compromised and injected malicious code into more than 1,000 software packages. The extraordinary spree has transformed how software developers and maintainers distribute and manage their code, as their dependencies and repositories have become one of the most effective and prevalent attack vectors this year.

While there has been a host of technical exploits, TeamPCP’s greatest attack has been the uprooting of trust — repeatedly proving that most organizations fail to verify the code they ingest into their systems is legitimate, abusing a nearly blind faith that much of the software development industry relies on to power today’s modern economy.

Starting with Trivy in February, TeamPCP’s attacks have shaken that trust many times over.

The scale of TeamPCP’s attacks lies partly in the automated systems companies use to deploy code, like CI/CD pipelines. It is also capitalizing on new security gaps created by developers’ increasing reliance on AI. Yet, with relatively low effort and unoriginal tactics, TeamPCP is wrecking open-source frameworks and underlying systems at levels the technology community has rarely reckoned with.

“Developers didn’t do a great job of analyzing the security of their open-source dependencies before but, now with AI, there’s in some cases virtually no human in the loop or any kind of sanity check on what these tools are doing,” Feross Aboukhadijeh, founder and CEO at Socket, told CyberScoop.

“You have agents installing packages that haven’t been vetted,” he said. “When an attacker gets in, the impact is even broader because there’s less checks and balances to stop it from affecting everybody.”

TeamPCP hasn’t identified a new problem or proved anything novel. The crux of these attacks hinge on a central theme — defensive vulnerabilities the entire software industry has known about for years. Researchers and developers know the open source trust model is broken and susceptible to sabotage. Yet, the software industry has not fixed this problem. 

“The speed and scale of these attacks is what makes it most notable, not necessarily the methodology behind it, because at the core it is really about exploiting third-party trusts that we have,” said Kimberly Goody, senior manager at Google Threat Intelligence Group.

Software packages are typically subjected to intensive security monitoring to test for vulnerabilities and poisoned updates before they are released to live environments. 

Yet, the real vulnerability highlighted by TeamPCP lies further up the chain of command with the organizations or individuals that publish these packages to the wider market, according to Nathaniel Quist, manager of cloud threat intelligence at Palo Alto Networks.

“It is their responsibility to secure their credentials and not provide a jump off point to trigger a supply-chain event,” he said. “Everything that interacts with or crosses through that zone must be highly monitored and controlled to ensure a compromise can be contained quickly and easily.”

TeamPCP’s motivation

TeamPCP, like any prolific cybercriminal, has captured significant attention from threat hunters since it emerged in late 2025. Google attributes the activity to one core operator.

The company said it traced TeamPCP’s residential and mobile IP address connections to South Africa, indicating the primary operator was located there during at least some of its attacks.

“We don’t believe that there’s an established core group, at least not yet, and that a lot of this has been conducted by an individual,” Goody said. Google declined to name the core operator or confirm it knows the person’s true identity. 

Palo Alto Networks said the core manager of TeamPCP uses the “ResoluteXBF” handle on multiple platforms. The cybersecurity firm is also tracking two additional core members: “diencracked” and “Shinigami.”

If TeamPCP is primarily run by one person, law enforcement has a rare opportunity to make a lasting impact with a single arrest.

TeamPCP has collaborated with other cybercriminals, but most of those partnerships were short-lived and ended in a public feud or otherwise failed to get off the ground in any meaningful way, Goody said.

Researchers have linked TeamPCP to extortion crews, dark web forums and affiliates including Lapsus$, ShinyHunters, Vect, DragonForce, BreachForums and “HasanBroker.” TeamPCP listed about 4,000 private code repositories on a dark web forum with an asking price of $95,000.

The actions to date, including unpredictable behavior, indicate motivations beyond financial gain and a “clear desire for notoriety,” Goody said. “They seem to like to make chaos.”

Quist draws the same conclusion from his months-long investigation, noting that it encourages other cybercriminals to get in on the action, at one point offering financial rewards for the largest software supply-chain attack. 

TeamPCP isn’t in the game for extortion payments, he said. “These actors are more interested in the underground street cred they are gaining” and “causing as much damage and mayhem as possible.”

Victims abound, but exposure limited

TeamPCP has been remarkably noisy, opportunistically injecting malware into open-source software for the purpose of stealing credentials for Kubernetes environments, Amazon Web Services, Microsoft Azure, Google Cloud and many other connected services.

The group’s claimed victim list is staggering: Checkmarx, Bitwarden, LiteLLM, Telnyx, Mercor AI, PyTorch Lightning, AntV, SAP, GitHub, TanStack, UiPath, MistralAI, Microsoft DurableTask, Red Hat and Nx Console.

The full collection of packages compromised or poisoned by TeamPCP to date accounts for roughly 500 million weekly downloads combined, according to Quist.

While the breadth of potential downstream compromise flowing from those downloads is substantial, many endpoints infected with those malware-riddled packages aren’t exposed to the internet and less susceptible to attack, he added.

“I don’t think there’s going to be a very extremely large number of victims,” Quist said. “There’s going to be a lot of people who potentially could be compromised and have potentially vulnerable packages in their environment, but that doesn’t necessarily mean they’re in an exploitable position.”

While these incidents have grabbed headlines, TeamPCP hasn’t accumulated payouts nearly as large as other cybercriminals. The broader reputational impact it has wrought, however, is massive.

TeamPCP has publicly claimed more than 10,000 victims and about $90,000 in extortions, according to Quist.

“They might not be making a lot of money, but they are causing a lot of impact,” Goody said. “Their campaigns have been very disruptive.”

How TeamPCP’s operating model targets development

TeamPCP’s victim list has grown as its hijacked open-source repositories on npm, PyPI, GitHub and other outsourced developer tools that are incorporated into upstream code running in production environments.

Developer laptops and other endpoints that are assigned to install, build and publish software widely contain keys and access to source code that create incredibly valuable supply-chain targets for attackers, Amitai Cohen, head of the attack vector intel team at Wiz, explained during a June presentation on TeamPCP at SleuthCon in Arlington, Va. 

The group targets CI runners, which are automated systems that build, test, and publish code. TeamPCP injects malware into the code repositories these runners maintain. When other developers pull that code into their own systems, they unknowingly download the malware alongside it. 

Some of these artifacts, including Python libraries, npm registries and GitHub Actions, are downloaded almost immediately by thousands or millions of developers who’ve set their runners up to consistently pull the latest version, according to Cohen. “We as a security industry have taught them that that is the right thing to do. You want to use the latest version because you want to be protected against vulnerabilities, and obviously you want to benefit from all the latest features.”

That instinct is exactly what TeamPCP exploits. By compromising one company’s CI/CD workflow, the group gains access to every downstream user who automatically pulls that infected code. “This is what allows [TeamPCP] to leverage initial access to some patient zero, some company that had a vulnerability in their CI/CD workflow, in order to gain access to their downstream users,” Cohen said. “That’s just how the software supply chain works. Everything has dependencies upon dependencies upon dependencies.”

Some of the packages compromised by TeamPCP were live for almost 13 hours, but security practitioners have responded by identifying code-injection attacks much quicker now, pulling some compromised repositories within 15 minutes, said Ben Read, director of strategic intelligence at Wiz.

The threat group’s operations remain high-tempo. TeamPCP infects new software packages almost daily, validates compromises and captures sensitive data within 24 hours, according to Wiz researchers.

The threat group has consistently evolved its tactics, developing payloads in JavaScript and Python while spreading from local files to Kubernetes application programming interfaces and bundled software development kits. Most recently, it’s been stealing credentials via custom protocols. 

The group’s ambitions have expanded beyond its own attacks. TeamPCP is also responsible for a self-replicating piece of malware known as Mini Shai-Hulud, which infected hundreds of software packages across open-source registries in back-to-back attack sprees last month. A TeamPCP affiliate published the full source code for the malware on GitHub last month and encouraged other cybercriminals to use it for their own campaigns.

“TeamPCP is going for volume. They are not being discriminating, they’re not necessarily trying to be stealthy or trying to maximize ROI. They’re going for an all-of-the-above strategy,” Read said during the Sleuthcon presentation.

Defensive gaps create openings for attack

TeamPCP’s attack spree has also underscored how difficult it is for organizations to revoke compromised secrets. Multiple victims have experienced recurring infections, sometimes falling prey to TeamPCP three times within a month, because they didn’t rotate secrets properly, Cohen said. 

At its core, these attacks highlight a direct trade-off organizations accept when they update software quickly to fix vulnerabilities, but learn that doing so too quickly could expose them to illegitimate registries containing malware.

TeamPCP has targeted what Aboukhadijeh describes as a “public good,” open-source registries that were never perfect but widely trusted and rarely turned into a point of entry for supply-chain attacks. 

Rapid open source software installation is one of the most dangerous things an organization can do right now, he said, adding that there’s a roughly 1 in 10 chance that any package installed by an organization could trigger an active attack. 

TeamPCP has compromised security scanners, password managers, automation tools, data visualization software, and CI/CD infrastructure across various environments.

And it’s lifted a trove of credentials and other sensitive data from victims.

Researchers like Cohen at Wiz, who have been tracking this attack spree since the beginning, are nearing a breaking point. 

“This is also too hard on us. We’re very tired. I’m sure a lot of people working on this problem space are very tired, and it’s just kind of become untenable,” Cohen said.

“You can’t keep existing in a world where you wake up every morning and some super prevalent package is compromised and everybody’s just going to be using it like nothing,” he added. “We need to start taking this a bit more seriously.”

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Members of Congress responded with skepticism and caution Tuesday to the Trump administration’s decision to impose export controls on Anthropic’s newest AI models.

The Friday order, which Anthropic said forced it to disable its Fable 5 and Mythos 5 artificial intelligence models, was prompted by what the administration said were national security concerns that a large number of cybersecurity professionals have dismissed as ill-founded.

Several Hill Democrats told CyberScoop they were concerned that the administration’s decision was driven by other considerations. Notably, the administration has feuded with Anthropic over use of its models for domestic surveillance and fully autonomous weapons.

Sen. Angus King, a Maine independent who caucuses with Democrats, said he would need to be convinced it was a legitimate national security order and hadn’t yet seen a full justification.

“What they did was pretty extreme, and I’d want to see what the basis was, as opposed to all the other issues that are swirling around in cybersecurity,” he said. “I’m a little skeptical because of their otherwise announced antipathy to this company.”

Leaders of the House Homeland Security Committee had contrasting takes, with Chairman Andrew Garbarino, R-N.Y., offering a two-pronged response and the top Democrat on the panel, Bennie Thompson of Mississippi, panning the order.

“The administration is right to treat advanced AI cyber capabilities as a national security issue, especially when foreign adversaries and cybercriminals are actively looking for ways to weaponize these tools,” Garbarino said in a statement. “At the same time, we need to make sure our response does not unintentionally disadvantage American companies, allied partners, or critical infrastructure defenders who need access to the best secure tools available in order to protect our networks here at home.”

The United States, not China, needs to set standards for trusted AI, Garbarino said.

But Thompson said the order adds evidence to the appearance that the Trump administration doesn’t “have a coherent plan for mitigating the cybersecurity risks” of frontier AI models, he told CyberScoop in a statement.

“AI regulations should rely on standards and procedures that provide confidence to the public that decisions are based on the evidence and not on politics,” he said. “Instead, the Trump administration has adopted an ad hoc approach where decisions are made by political appointees in the White House rather than experts and where companies are left guessing on how to comply.”

Virginia Sen. Mark Warner, the top Democrat on the Intelligence Committee, had also previously highlighted the administration’s quarrel with Anthropic in response to the order in a statement to CyberScoop.

Behind the scenes, the administration and Anthropic were reportedly continuing to try to forge a truce Tuesday. More broadly, the administration’s AI executive order had a rocky rollout as the administration swung back-and-forth on how involved the government should be.

Some lawmakers deferred on commenting Tuesday, such as Senate Homeland Security Committee Chairman Rand Paul, R-Ky., who told CyberScoop he didn’t have anything to say on the order.

Others said they were still seeking information from the administration.

“I have not had the opportunity to get a brief specifically as to the logic, the reasoning behind it, and so forth,” said Sen. Mike Rounds, the South Dakota Republican who chairs the Armed Services Subcommittee on Cybersecurity. “So I’m going to withhold judgment until I get an opportunity to get the rest of the story, so to speak.”

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While Washington D.C. frets over the potential impact of Anthropic’s Claude Fable 5, security researchers continue to track how the integration of frontier AI tools are transforming the digital security landscape for malicious hackers and defenders alike.

The breakneck speed of model releases may be creating short, silent security gaps for developers who must choose between performance and security, according to a new report.

Researchers at Backslash Security pored through update logs for Claude Code, Anthropic’s flagship coding model, finding the company was patching dozens of newly discovered security vulnerabilities in the program between April and early June 2026.

The logs revealed the details of more than 30 security relevant patches implemented over that timeframe, but Anthropic did not publicize them. Instead, Backslash Security researchers found them by reviewing update logs for every new version of a Claude Code release in the last two months, noted the security-relevant fixes and traced each one back to the version and date it shipped.

The patches included fixes for data poisoning, prompt injection and arbitrary code execution vulnerabilities. One bypassed core safeguards put in place to prevent Claude Code from accepting catastrophic deletions commands, such as erasing an entire codebase, by adding a single backslash to the command. Another leaked user OAuth credentials, while a third allowed an AI agent to plant a backdoor in shell startup files.

There is nothing inherently odd about this: most companies regularly update and patch their software  and anyone who had auto-updates turned on would automatically be switched to the newest, secure version of Claude Code.

But Yossi Pik, co-founder and chief technology officer at Backslash Security, told CyberScoop that the research concluded “the way AI agents are released is different than previous software.”

“We debated internally, because when I originally said I wanted to write about this, I was told ‘Okay, every company has the [same] issue, then they patch and fix,” he said. “This is the nature of software, but I think that what makes this unique is the cadence and frequency of the releases.”

AI companies keep a ferocious pace when updating their models. Claude Code’s changelog indicates there have been 16 different versions through the first half of June, while OpenAI’s Codex was updated 6 times.

Because model updates often bring short-term performance and stability issues, software developers typically wait a week or more before upgrading to a new version.

These time gaps create small windows of vulnerability and force developers to choose between security and performance. The report identifies several reasons why developers don’t automatically update their AI models, including companies that may rely on internal vetting or release schedules, operate in regulated or air-gapped environments where model versions are frozen, and the need to maintain long-running sessions or use manual installations.

Pik said some IT and security teams have also told him they prefer not to install any new version of an AI model without letting it run on other environments first.

“You don’t have that much flexibility, either I go to the latest and I’m getting a less stable version [of the model] or I’m waiting for a few days or a week until I can install it, and hope that nothing would happen during this time,” said Pik.

The Backslash report is not intended as a dig at the security rigor of Anthropic, noting the company tends to “patch fast and document more than anyone” and has addressed every issue and vulnerability identified in the report.

Rather, it’s to highlight the series of mostly silent and persistent security exposures that an organization faces when adopting AI into their workflow.

Other software programs and technology products face similar tradeoffs through different updates, but most of the vulnerabilities detailed in the change log – such as getting an agent to leak data or accept malicious prompts – are unique to large language models and AI systems.

That means integrating AI tools can bring new security problems to an organization, both from outsiders who can poison or influence the model and insiders who can maliciously or accidentally direct the model to access or leak systems, data and identities.

For most Claude Code users, this process runs automatically in the background. Yet Yik points out that just as AI is transforming work itself,  it’s also changing how we need to approach software security and updates.

“It should not be compared to [Microsoft] Office that is installed and gets patched once in a while,” he said. “It’s a completely different beast that keeps evolving, and we don’t want to limit it…I think that it’s great for everyone. We just need to make sure that we do it in a secure way, and every organization should understand what that means for them.”

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A policy paper published Tuesday advocates for software bills of materials (SBOMs) for artificial intelligence as a mechanism for reducing cyber risk and improving transparency, and seeks to give lawmakers, federal agencies and others a roadmap on how to proceed.

The SBOM, commonly described as an inventory of software ingredients, emerged in the 2010s and has expanded beyond software to include hardware and AI.

But the paper from the Institute for Security and Technology, which CyberScoop is the first to report on, argues that AIBOMS require foundational work before they can be widely implemented.  This comes as some companies are already offering AIBOM services and other organizations are actively shaping AIBOM policy.

“What we’re worried about is we would end up in a ‘fire, ready, aim’ situation where everyone was doing it, but we were all doing slightly different things,” said a co-author of the paper, Allan Friedman, who has worked on SBOMs in multiple U.S. government roles. “If we don’t have a shared vision, it becomes a lot harder to have a coherent policy. It becomes a lot harder to have common tools and interoperable data and it becomes a lot harder to use the data that we’re tracking to actually deliver on the promise of supply chain transparency.”

The idea for the paper sprung from discussions with Hill aides and Pentagon staffers, Friedman said, and people like them are the target audience as well.

A key premise is that AIBOM policy needs to explore the topic from two sides.

“How do you solve the chicken-and-egg issue, where no one’s providing the data, so no one’s asking for it, and no one’s asking for it, so no one’s providing it?” Friedman told CyberScoop. “The answer is, you have to go from both supply and demand.”

On the supply side, “An AIBOM should capture relevant details about the models and datasets used for training, fine-tuning, evaluation, validation, testing, retrieval, grounding, augmentation, or other model development or operational purposes,” the paper suggests.

“The demand side begins with some form of forcing function or requirement that organizations understand what is in the products they manufacture and sell,” it states, with one such requirement potentially being an industry mandate to require the tracking of system components — for example, like the “lightweight” standards used in the payment card industry on data security that isn’t overly exact about how components should be tracked.

But it could also include government regulations or contracting conditions, Friedman argues with his Institute for Security and Technology colleague Nick Leiserson. (The scope of government directives on AI is a topic of considerable debate on Capitol Hill and within the Trump administration right now.)

Friedman said the paper isn’t meant to be the be-all, end-all, and acknowledged the prior work of organizations like the Open Worldwide Application Security Project (OWASP) and Linux Foundation.

“We’re not saying this is a brand new topic, nor are we saying that AIBOM will solve all AI security issues,” he said. “I’ve been fighting this fight for SBOM for a decade. You know, SBOM will not pick up your dry cleaning.”

And as AI continues to evolve rapidly, that means papers like the one published Tuesday are just at the beginning of the discussion, Friedman said.

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Last Friday, the Trump administration sent a shock through the tech ecosystem when the Department of Commerce levied export controls on Anthropic’s new AI model Fable 5.

Anthropic has taken steps to limit the risks around the commercial sale of its Mythos model, including declining to release it publicly, funneling it to organizations for cyber defense and developing guardrails for Fable 5 that would default its answers to older, less powerful models around sensitive topics like cybersecurity and biological warfare.

But the Trump administration was reportedly alarmed by recent reports from Amazon and another cybersecurity researcher claiming to have jailbroken Fable 5 within days of its public release, and determined that if researchers in the U.S. could jailbreak the model, so could America’s foreign adversaries.

The Commerce Department’s decision spurred Anthropic to shut off the models for all users as they attempted to convince the White House to change course.

But some cybersecurity and AI experts have sharply disagreed with the White House’s actions, saying the research has not demonstrated that anyone has been able to circumvent Fable 5’s safeguards and access the kind of dangerous new capabilities that have worried officials.

Katie Moussouris, a well-known cybersecurity expert, said Monday that Anthropic provided her with a copy of third-party research on guardrail bypass techniques for Fable 5.

According to Moussouris, the researchers asked three Claude models – Fable 5, Mythos and Claude Opus – to review batches of known, vulnerable open source code for security issues. Fable 5 initially refused the request, but the researchers were able to use “a multistep and manual process” to get Fable 5 to turn the output into automated scripts that could test patches for the vulnerability.

Third-party research since Fable 5’s release has not found ways to bypass its safeguards around hacking. The capabilities researchers have demonstrated are foundational to what makes Fable 5 and other frontier models valuable for cybersecurity defense.

“Defenders need to be able to ask AI to fix the bugs in a file, explain why the fix matters, and write tests that confirm the patch works,” she wrote. “That is not a guardrail bypass. It is the most valuable thing an AI model can do for defensive security: executing the find, fix, and test loop defenders run every day.”

Moussouris previously provided technical expertise to the Waasenaar Agreement, a voluntary multilateral security agreement around controlling exports for both munitions and dual use technology that includes the U.S. and dozens of other countries.  Based on the research she’s seen, she called placing export restrictions on all foreign sales of Fable 5 “heavy handed” and “misguided.”

Some lawmakers who in favor of higher regulations and scrutiny on the national security implications of AI were nevertheless critical of the White House decision. Senator Mark Warner, D-Va., told CyberScoop in a statement that while “there may be circumstances where restrictions on the export of frontier AI models are warranted,” those decisions must be “grounded in a transparent, risk-based process with clear rules and consistent standards.”

The Trump administration’s approach, he argued, has been the opposite, and he called for Congress to pass a statutory framework for testing and approving frontier AI models based on transparency, predictability and fairness.

“This administration has repeatedly shown a willingness to weaken export controls designed to protect our national security and maintain our technological edge over adversaries, while also making no secret of its hostility toward Anthropic,” said Warner. “That raises serious questions about whether this effort is being driven by objective national security concerns or something else.”

Anthropic said it subjected Fable 5 to 1,000 hours of testing from internal and external red team, reporting that no universal jailbreaks were found that would remove those guardrails or allow the model to access Mythos for cyber and biology work.

Moussouris is far from alone. She is one of dozens of cybersecurity experts who signed an open letter Monday calling on the Trump administration to “Free Fable.”    

The researchers say that while Mythos-class models are “quite good” at identifying and exploiting vulnerabilities in software code, they “are not uniquely good” compared to other frontier models they use every day for cybersecurity defense.

For example, despite OpenAI’s Daybreak model offering similar vulnerability discovery and patching capabilities. It was not included in the Commerce Department’s restrictions.

The researchers also note that Fable 5’s guardrails have been notoriously oversensitive compared to other frontier models used by red teamers, becoming “a source of humor in the cyber community on launch day” as IT and cyber workers reported online that they couldn’t get the model to perform basic defensive cybersecurity tasks.

The letter questions whether the issues found in the jailbreaking reports would even qualify as offensive capabilities, and note they can be reproduced in other commercial and open-source models, including GPT 5.5, Claude Opus, Claude Sonnet and Chinese models like Kimi 2.7.

“The justification for this unprecedented action was that Fable provides a unique ‘uplift’ of capabilities beyond other AI models, but AI has been finding bugs and generating working exploits at superhuman levels since last year,” they wrote.

The White House decision comes as AI companies face increasing backlash from a public that is now overwhelming calling for more robust government intervention.

A Johns Hopkins University poll in May found broad, bipartisan support for AI regulations, with 73% calling for bans on AI-generated images and video, 68% calling for labels on AI content, 75% wanting disclosure laws around when they interact with AI chatbots and 70% calling for “the right to interact with a human rather than an AI in medical, legal, educational and government settings.”

Another global survey of 18,000 people released this week found that the top four concerns most people have around AI all revolve around the tool’s ability to spread misinformation, create deepfakes to embarrass or hurt others, making it easier for criminals to hack into victim networks and helping terrorists create new weapons.

Senior reporter Tim Starks contributed reporting for this story.

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The U.S. government on Friday ordered Anthropic to immediately suspend foreign access to Fable 5 and Mythos 5, its two most advanced artificial intelligence models, citing national security concerns tied to a reported method of bypassing the models’ safety restrictions. 

The directive, issued late Friday afternoon by Secretary of Commerce Howard Lutnick in a letter to Anthropic Chief Executive Dario Amodei, placed the two models under export controls that prohibit use by foreign nationals, whether inside or outside the United States. 

Because of the scope of the restrictions, which includes foreign-born Anthropic employees, the company announced Friday evening that it disabled the models to ensure compliance. Access to the company’s other AI models was not affected. 

Fable 5 and Mythos 5 had been released earlier this week, with Anthropic describing them as the most capable systems it had ever deployed. Mythos was available to members of Project Glasswing, which allowed selected cybersecurity companies to use the model to identify and address security flaws.

It’s unclear how the Commerce Department action affects Project Glasswing. Anthropic did not respond to a request for comment.

The Commerce Department‘s letter did not detail the specific national security concern. In its blog post Friday night, the company said its understanding is that the government became aware of a technique for “jailbreaking” Fable 5, a term for methods that circumvent a model’s built-in safety guardrails. According to Anthropic, the government provided only verbal evidence of what it described as a “narrow, non-universal jailbreak,” which essentially involved prompting the model to read a specific codebase and identify software flaws. 

Anthropic disputed the severity of the finding. The company said it reviewed a report it believes formed the basis of the government’s directive and found that the capabilities demonstrated were already available in other publicly accessible models, including OpenAI’s GPT-5.5. The company said those same capabilities are used routinely by cybersecurity professionals for defensive purposes. 

Katie Moussouris, chief executive of the cybersecurity firm Luta Security, posted on BlueSky Saturday that the issue stems from “Defense Oriented Prompting,” a security-first method of engineering AI system instructions that treats natural language as code.

Other reports claimed that Amazon was responsible for flagging the security issues in the model. The company did not respond to CyberScoop’s request for comment. 

Anthropic acknowledged in its statement that perfect jailbreak resistance is not achievable for any model provider, and said it had designed Fable 5 around a “defense in depth” strategy, combining narrow jailbreak resistance with active monitoring. The company said no testers had found a universal jailbreak capable of broadly bypassing the model’s safeguards. 

“We disagree that the finding of a narrow potential jailbreak should be cause for recalling a commercial model deployed to hundreds of millions of people,” Anthropic wrote. “If this standard was applied across the industry, we believe it would essentially halt all new model deployments for all frontier model providers.”

Friday’s directive is the latest episode in a prolonged dispute between Anthropic and the Trump administration. In February, President Donald Trump moved to bar Anthropic’s products from federal agencies after the company sought stronger restrictions on how the Pentagon used its technology.

Despite that, as Anthropic released Mythos under Project Glasswing, the National Security Agency was given Mythos 5 to conduct offensive cyber operations. Earlier this month, Trump signed an executive order directing federal agencies to bolster cyber defenses and establish a voluntary mechanism for the government to gain early access to powerful AI models before deployment. 

The administration’s stated rationale for Friday’s action drew widespread skepticism from researchers and analysts. Dean Ball, a senior fellow at the Foundation for American Innovation, called the move “baffling.” Chris McGuire, a senior fellow at the Council on Foreign Relations, said targeted export controls on model access could be a legitimate policy tool, but called the across-the-board restriction “highly questionable” and the deemed export provisions — which restrict foreign nationals inside the U.S. — “just absurd.” 

The broader implications for the AI industry remain uncertain. Aaron Levie, chief executive of Box, described the directive as “a big turning point for AI regulation,” arguing that the government’s willingness to deem specific models too powerful for certain uses establishes a precedent with potentially far-reaching consequences.

Other tech leaders in the government supported the action. 

“We fully support @POTUS and @SecWar in prioritizing national security and the security of our warfighters, DIB partners, critical infrastructure, international partners and allies,” DOD CIO Kirsten Davies wrote in a social post on X. “Some things are simply more important than revenue cycles, clickbait, and pre-IPO valuation. America First. Always.”

Anthropic said it believes the situation stems from a misunderstanding and is working to restore access as soon as possible.

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The U.S. Departments of Justice and Homeland Security seized multiple internet domains this week, accusing them of being used to publishing thousands of AI or digitally-altered images and videos of nude women.

The domains, CFAKE.com and SOCFAKE.com, specialized in digital forgeries that “were made to appear to be sexual images of famous women, including politicians, first ladies of multiple countries, royalty, journalists, television presenters, athletes, entertainers, and others” either nude or engaged in sexual activity,” according to a Department of Justice release.

In addition to creating sexual images and videos of women without their consent, the service allowed people to browse by topics, including “rape,” “forced,” and “degradation.”

That description comes from a Department of Justice release describing the contents of its probable cause affidavit and search warrants. CyberScoop has not viewed the court documents.  

The sites were seized under the TAKE IT DOWN Act, a law passed last year giving federal authorities the ability to criminally prosecute those who create and distribute deepfake porn. The law was a rare moment of bipartisan agreement in Washington D.C., gaining support from both Democrats and Republicans who said their constituents were demanding tougher laws to curb the use of AI to create nonconsensual deepfake porn.

The operation marks one of the largest seizures since the law went into effect. The details of the operation disclosed by the government show how creators of deepfake porn rely on a web of international assets and infrastructure to evade law enforcement.

Robert Fraiser, U.S. Attorney for the District of New Jersey, said U.S. authorities worked in coordination with law enforcement agencies in France and Italy. According to U.S. officials, they were first notified about the website by Italian Polizia de Stato, while a parallel investigation run by the Paris Public Prosecutor’s Office in France resulted in the arrest of a suspect connected with the site, along with seized cryptocurrency funds.

“These seizures stopped a website that trafficked in humiliation, exploitation, and the violation of personal privacy on a massive scale,” said Frazer in a statement. “For the victims whose images were distributed without their consent, the harm is not virtual — it is deeply personal and often enduring.”

According to the Paris Prosecutor’s Office, Cyrille B., a 47-year-old French national was arrested and accused of being an administrator for CFAKE. A search of his home in Nice found computer equipment related to the site and a little more than $48,000 in Ethereum cryptocurrency that they said came from the site’s advertising.

The French investigation identified 300,000 images, 7,000 videos depicting 14,000 individuals from different countries. The site had approximately 200,000 user accounts, 4 million views per month and uploaded 50 pieces of new content every day.

The suspect had no prior criminal record, and will go to trial on July 7. The charges carry potential penalties of up to seven years in prison and €500,000.

U.S. Immigration and Customs Enforcement’s Homeland Security Investigation division is leading the federal investigation, in conjunction with the U.S. Attorney’s office for New Jersey.

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OpenAI’s threat intelligence team tracked what it believes are two distinct clusters of activity online from groups with ties to China and posting content seemingly designed to stoke anger around divisive topics like AI and data centers.

The first, dubbed “Data Center Bandwagon,” used ChatGPT to create imagery and social media comments claiming data center buildouts were raising electricity prices for Americans.

Another used the tool to develop images and online posts characterizing tariffs as a covert means for the countries to exert control over the global technological landscape. According to OpenAI, the originating prompts directed ChatGPT to only include U.S. President Donald Trump in this content, while leaving out Chinese President Xi Jinping, who has also made use of tariffs.  

In both cases, OpenAI said the operators “likely originated” in China. The anti-data center content was traced to an unnamed Chinese technology company that holds multiple contracts with regional Chinese governments, and both clusters used VPNs to evade restrictions, prompted ChatGPT in simplified Chinese and asked for both English and Chinese-language outputs, all while posing as Americans on social media platforms like X and YouTube.

“This looks like a classic example of a foreign influence operation jumping onto the bandwagon of a genuine and pre-existing domestic debate and trying to manipulate it by using fake accounts posing as Americans,” online, said Ben Nimmo, principal investigator at OpenAI and author of the report. 

While OpenAI – which has sought to raise hundreds of millions of dollars in funding to build datacenters in the U.S. – is not a neutral party, the report does not claim that anti-data center sentiment in the country is being driven or bolstered by foreign propaganda online.

There’s little evidence that the campaigns got much attention outside their own amplification networks. Such engagement from third parties is an imperfect but important indicator of an influence operation’s impact. OpenAI rated the campaigns a 1 and 2 on the Bookings breakout scale, scores that indicate activity on one or more platforms but no evidence of meaningful engagement by targeted audiences.

Additionally, researchers who study state-sponsored influence campaigns say these groups are happy to latch onto and amplify genuine domestic movements or messaging so long as it serves their larger destabilization goals.

Others have suggested that piggybacking off established narratives with organic momentum – like public anger at AI and data centers – can make an influence operation appear more effective.

While AI tools can be leveraged to create such internet content at scale, they often fail to gain traction. Some images used by Chinese actors appear clunky or use overly direct messaging that display a lack of familiarity with both the English language and internet virality.

“I do want to be really clear here: this was not a case of an influence operation creating a debate,” said Nimmo. “The debate existed already. This was an influence operation from China trying to interfere in it. We didn’t see any signs that it succeeded.”

He added that while such views are “reasonable” and “sincerely held” by many participants on both sides, “what we don’t want to see is a covert foreign influence operation posing as Americans to try to shape it, still less a foreign influence operation using the very AI that it attacks.”

According to the OpenAI report, the actors used ChatGPT to edit work reports which contained operational security details about their social media campaigns. In them, they described their goals as “establishing persistent and credible accounts, producing visually appealing content to expand audience reach in different regions and maintaining long term account viability by anticipating platform enforcement.”

Another report fed into ChatGPT discussed how best to leverage Facebook’s content ecosystem, groups, pages, hashtags, advertising tools, recommendation systems and reporting mechanisms, as well as strategies for evading Meta’s detection of coordinated inauthentic accounts.

The campaign around tariffs also used ChatGPT to create short comments, comics in English but also Italian, Japanese and traditional Chinese accusing the US of putting profits over loyalty to its allies. OpenAI said they were targeted by the same network on X with an influence campaign alleging a widespread user data breach that Nimmo said “never happened.”

While OpenAI said the campaigns likely originated in China, they do not directly attribute the operations to the Chinese government or actors working on their behalf, but do note that many parts of the campaign and its tactics overlap with pre-established Chinese government propaganda campaigns online.

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The Cybersecurity and Infrastructure Security Agency on Wednesday ordered federal agencies to prioritize vulnerabilities based on four criteria, as part of push to “patch smarter, not harder.”

Federal agencies should emphasize patches for vulnerabilities that affect a publicly exposed asset, allow an attacker to fully automate exploitation, give attackers the ability to take over control of a system or relate to evidence of active, real-world exploitation, CISA declared.

CISA acting director Nick Andersen previewed the binding operational directive (BOD) Tuesday, framing it as a rethinking of vulnerability management more broadly.

“This Directive provides clear definitions, timelines and criteria that enhances transparency, predictability and agencies’ resource planning to execute more effective vulnerability remediation,” Andersen said in a statement. “CISA is leading and collaborating with federal civilian agencies to stay ahead of our adversaries as tactics, technologies and vulnerabilities change.”

BOD 26-04 sets forth timelines for how quickly agencies must fix a vulnerability based on how many of the four criteria it meets. If it meets all four, for example, agencies need to fix it within three days and carry out a “forensic triage” to assess whether their systems were compromised. 

More generally, agencies must immediately update their vulnerability management policies, including establishing a process for ongoing remediation of known, exploited vulnerabilities (KEVs) on CISA’s “must-patch” list. Within 60 days, agencies need to update their processes for remediating common vulnerabilities, and within 180 days, agencies must meet the order’s remediation timelines.

The directive is motivated in part by how artificial intelligence is shifting the window from vulnerability discovery to weaponization, and CISA said it reflects priorities in an executive order on AI that President Donald Trump signed last week.

BODs aren’t mandatory for anyone outside of federal agencies, but CISA encourages the private sector to embrace them. CISA officials said in a blog post about the need to “patch smarter, not harder” that “defenders are already struggling to keep up.”

“Artificial intelligence is assisting both researchers and adversaries in identifying flaws in software, vastly increasing the pace at which new vulnerabilities are discovered,” wrote Chris Butera, acting executive assistant director for cybersecurity, and Jonathan Spring , senior technical adviser. “Per Verizon’s 2026 Data Breach Investigations Report, only 26% of vulnerabilities on CISA’s Known Exploited Vulnerabilities (KEV) Catalog were fully remediated by organizations in 2025, a drop from the previous year’s 38%. The median time for full resolution rose to 43 days.”

The move from weeks to days for agencies to patch the most urgent vulnerabilities is something CISA has discussed with some agencies to see if it’s doable, Butera told reporters Wednesday. At one large agency CISA analyzed, just 1% of vulnerabilities fell into the 3-day window, while 60% could be deferred to the next system upgrade.

“We’ve engaged with a few federal agencies ahead of this directive and tried to socialize some of these new time frames,” he said. “We really believe we should be able to free up some time to patch the most urgent vulnerabilities faster, while allowing for more regular patch cycles for some of the lower risk vulnerabilities.”

Patrick Garrity, a security researcher at VulnCheck, said the CISA directive joins similar guidance out of India and the United Kingdom.

“It’s clear the momentum is growing and pushing in the right direction,” he told CyberScoop. “The new directive aligns exactly with the approach we’ve been taking with customers for years, leveraging exploit intelligence to focus on the subset of vulnerabilities that enterprises, governments and vendors really need to address. While it’s mandated for federal organizations, it’s something the private sector should pay attention to as well.”

Tod Beardsley, vice president of security research at runZero and former KEV section chief at CISA, wrote on LinkedIn that there are several noteworthy potential impacts of the BOD, among them that he thinks three-day deadlines will end up being frequent.

“I remain dubious that a three day deadline spread across more than a hundred agencies is an achievable patch cadence today, but we’ll all find out together,” he said.

Updated 6/10/26: Includes Chris Butera comments on timelines, and comments from Patrick Garrity and Tod Beardsley.

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Earlier this year, Anthropic executives said that their new AI model, Claude Mythos, had such powerful capabilities for harm that they would not release it publicly.

On Tuesday, the company said it was making an altered version of Mythos available to the public, promising “new guardrails” that thwart the model’s best-in-class performance in hacking and bioweapons research.

Anthropic said Claude Fable 5 was the “same underlying model” as Mythos, but its responses for certain topics like cybersecurity and biology will be drawn from a previous Claude Opus model that is already public.

“Releasing a model this capable comes with risks. Without safeguards, Fable 5’s capabilities in areas like cybersecurity could be misused to cause serious damage,” the company said in a draft blog sent to CyberScoop ahead of the announcement. “We’ve therefore launched the model with safeguards that route queries on a narrow set of topics to our next-most-capable model, Claude Opus 4.8.”

Anthropic also said they subjected Fable 5 to both internal and external red team testing for common model vulnerabilities, like jailbreaking. Anthropic said these tests identified no known “universal” jailbreaking techniques, but does not specify if partial jailbreaking techniques were discovered.  

The company is betting that won’t change when Fable 5 is made available to the broader public, but it’s worth noting that cybersecurity researchers have consistently found ways to jailbreak older AI models.

“The uplift from Mythos-level capabilities is valuable to many adversaries—for instance, those who could financially gain from cyberattacks—and we therefore expect them to be motivated to try to circumvent our safety measures,” the company wrote.

Anthropic is changing its data retention policies for Fable and Mythos models, keeping all user traffic for 30 days on both its own platforms and third-party services. A White House executive order creates a voluntary framework for AI companies to share frontier models with the government up to 30 days before public release. The company says the retained data won’t be used to train new Claude models or for “any non-safety-related-purpose.”

Following publication, a spokesperson for Anthropic told CyberScoop the company’s data retention policies “are specific to their safeguards work and is unrelated to the EO.”

Most organizations are still deciding whether to adopt AI into their IT and cybersecurity ecosystem.  But models like Mythos can scan for vulnerabilities, chain together exploits, and steal data from a victim network in minutes. Automation in hacking existed before AI, but experts have said frontier models like Mythos and OpenAI’s Daybreak can allow even low-level cybercriminals to wreak havoc.

While Anthropic cited its commitment to developing safe and secure AI in its reasons for not publicly releasing Mythos, many organizations have been clamoring for access, and its enhanced cybersecurity functions in cybersecurity and other areas have been the subject of congressional hearings, national security papers and White House executive orders.

Releasing a limited version of the model in Fable 5 represents an attempt to split the difference between those two desires. Anthropic said it would release follow up benchmarks and assets for the model.

So what can Fable 5 do? 

Anthropic said it’s possible the restrictions built into Fable will make it harder for the model to fulfill both malicious and legitimate user requests.

“Because we have prioritized safety, we’ve deliberately tuned the safeguards to be cautious, and they are still stricter than would be ideal—for example, sometimes benign requests will trigger our classifiers,” the company wrote. “We recognize that this will be frustrating to some users, and our aim is to reduce false positives as we update and refine the safeguards after launch.”

If Fable 5 draws its cybersecurity and biology answers entirely from Claude Opus 4.8, it will still provide users with impressive – though not unique – dual use cybersecurity capabilities.

According to the system card published for Opus 4.8, the model is a slight improvement on previous models like 4.7 in the realm of cybersecurity but was “generally much less capable than Mythos Preview.”

Opus 4.8 was tested on its ability to write complete end-to-end exploits and build exploit primitives that provide attackers with the ability to execute arbitrary code. It averaged a score just 5 out of 16 in proficiency, compared to Mythos Preview which scored closer to 10.

Without safety guardrails in place, Opus 4.8 can still reproduce nearly 80% of previously discovered vulnerabilities in real open-source software projects when given a high level description of the weakness. The system card said Anthropic’s unspecified safeguards whittle this success rate down to 1%.

Another test assessing Opus’ ability to develop exploits for the popular Firefox browser found that, again without guardrails, the model could identify a full working exploit 8.8% of the time and a partial working exploit 68.8% of the time.

The company also said that members of Project Glasswing – a consortium of public and private businesses given access to a preview version of Mythos – will be able to upgrade to the latest full model, Claude Mythos 5, to continue their work. Access to Mythos 5 will be expanded over time “through a more systematic trusted-access program” including federal agencies.

The post Anthropic’s new model is Mythos on a leash appeared first on CyberScoop.

The Cybersecurity and Infrastructure Agency wants to fundamentally reevaluate how it prioritizes risks and vulnerabilities, both for privately-owned critical infrastructure and within the federal government, acting director Nick Andersen said Tuesday.

The plans include a binding operational directive for federal agencies set to be published Wednesday and getting more specific with critical infrastructure owners and operators about which assets they need to protect most and how, Andersen said while speaking at an event hosted by Axonius in Washington, D.C. and talking with reporters afterwards.

The binding operational directive looks to revise how federal agencies do vulnerability management, he said. “Overall, our approach to date has been ‘A patch is released, apply this patch as quickly as you can,’” he said.

“We’re really asking people to take more of a focus on risk associated with each vulnerability. Is it with an asset that is internet-exposed? Does it align to a KEV entry?” he said, referring to CISA’s list of known exploited vulnerabilities. “Is it automatable in its exploitation? Really, we need to be able to highlight that some patches just aren’t as important as others, and plugging the holes for some vulnerabilities is simply not as important as others.”

Andersen said he has made setting the right priorities the focus of his tenure.

“We have to be okay with saying there are some systems that are less important than others, there are some elements of critical infrastructure that are less important than others,” he said. “Those things are very easy for us to rationalize [for] physical crises, but we need to start wrapping our minds around how we’re going to do that during cyber crises.”

Andersen said artificial intelligence-enhanced threats have fueled the directive in part, based on “a recognition that we’re a different dynamic environment with the shorter timeline to weaponization and exploitation,” but the discussions on the directive have been going on for months, before the splashy announcements about frontier AI models and the risks they might deepen. Wednesday’s directive is unrelated to the AI-focused executive order released by the Trump administration last week.

The idea of prioritizing certain potential hacking targets over others isn’t a new one in critical infrastructure, with concepts like “Section 9” designations under a 2013 executive order for entities whom an attack upon could have catastrophic effects; “systemically important critical infrastructure” designations, as recommended by the Cyberspace Solarium Commission; or the creation of the National Risk Management Center established during President Donald Trump’s first term but now the subject of proposed budget cuts.

Andersen said past concepts haven’t worked well, citing Section 9 designations as an example.

“We would sit here and say, ‘Congratulations, you’re with this company, and you’re a Section 9 entity, isn’t that fantastic?’” he said. “That’s really not the level of fidelity that we have to be able to get to to have a real measurable conversation about risk. I need to be able to go to a company and say, ‘Here’s the specific function you’re supporting that makes you more critical. Let’s have a conversation about the specific assets that support that function, and how do we get to a measurable level of resilience for those assets?’”

Those discussions need to get down to a “fine grain,” Andersen said.

“If I’ve got a major bank that I’m talking to, is it as important to me that the bank’s process that supports the bulk payment system is resilient, or is it just as important to me that the branch location two blocks away is continuing to operate?” he said. “Those things just are apples and oranges, even though it’s the same entity that might be affected.”

CISA’s capabilities under the Trump administration have drawn considerable scrutiny, given deep budget cuts at the agency, with more planned. The administration is now making moves to hire back personnel.

Andersen said the agency is working to hire 329 people, and will have job offers out to 182 of them by the end of June. He said the emphasis of the first tranche of hires under the hiring sprint is operational capabilities, meaning areas like emergency communications, infrastructure security and regional personnel.

The agency also has had some of its work hampered by the government shutdowns, such as the delay in plans for town-hall meetings about implementation of the Cyber Incident Reporting for Critical Infrastructure Act of 2022, which will require key owners and operators to report major incidents within 72 hours.

Andersen said he couldn’t set a date for finalization of regulations related to the law — which had already been delayed prior to any funding lapses — with those town halls now scheduled to begin next week.

“We could have a lot of comments that come to us and really radically change our way of thinking about what the need is here,” he said. “But our focus is just on what’s the original congressional intent behind CIRCIA. what is the greatest need that we’re going to be able to serve, and how it’s going to be able to further the mission that we have for the nation.”

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AI models such as Anthropic’s Claude Mythos and OpenAI’s Daybreak represent a fundamental inflection point in security. These advances are not only reshaping technology but also redefining trust, risk, and the relationship between humans and intelligent systems. As innovation accelerates, AI governance and responsible deployment are becoming strategic priorities for every organization.

Historically, governments have played a stabilizing role during moments of transformational technological change. Yet the pace and scale of the AI era demand a new model, one built on partnership rather than control, balancing societal responsibility with the need to sustain innovation and global competitiveness.

The White House’s executive order on AI governance signals that collaboration between the industry and policymakers will increasingly shape the future landscape. Proposed frameworks that promote transparency and responsible development point toward a more coordinated approach to risk management.

Effective governance of AI models should balance clear safeguards with the speed of innovation, aligning organizations, policy makers, and technology leaders around a shared goal: advancing AI in ways that strengthen trust, security, and long-term value. The path forward is not defined by heavy-handed oversight, but by building an ecosystem of accountability.

Three key points substantiate this approach.

First, the industry should recognize Anthropic’s release of Mythos as an example of responsible innovation. Company leaders recognized the model’s risks and deliberately delayed broader deployment, allowing early testing to surface vulnerabilities before widespread adoption.

The broader lesson extends beyond a single model release. Responsible leadership means prioritizing decisions that build trust and enable sustained innovation. As AI capabilities accelerate, the most successful organizations that lead will be those that weave accountability through their ambitious pursuits, rather than treating them as competing priorities.

Second, innovation rarely thrives under rigid frameworks. History has shown that many compliance regimes, while well-intentioned, incentivize organizations to optimize for requirements rather than outcomes. Security is strengthened through systems designed for resilience and trust, which goes beyond mere compliance.

Third, slowing U.S.-based AI innovation risks weakening long-term competitiveness. The U.S. remains a leader in AI but maintaining that position will require balancing responsible safeguards with continued investment and progress. Overly restrictive approaches risk slowing domestic advancement while other nations continue accelerating development and capability.

An effective AI governance approach would encourage further responsible AI model development, as demonstrated by Anthropic. It would avoid direct government regulation and instead enforce accountability for companies that are irresponsible with AI development.

Hopefully, the partnership and collaboration between government entities and industry will continue beyond the White House order. Policymakers and industry leaders should create incentives that reward AI vendors for considering societal implications before releasing new solutions. This framework would highlight responsible providers as models for the industry while imposing meaningful consequences based on demonstrated societal harm that direct affects business and technology decisions.  

AI models such as Mythos and Daybreak underscore a broader reality: the future of AI will be shaped by the trust around innovation, not merely by its development pace. The next era of AI leadership will require a new model of collaboration between industry and policymakers that maintains the speed and adaptability that innovation demands while establishing meaningful accountability for real-world outcomes.

The objective should be to guide progress responsibly. The organizations and nations that lead in the AI era will be those that demonstrate how innovation and accountability work together to strengthen trust, security, and long-term value creation.

Art Gilliland is CEO of Delinea, a cybersecurity company focused on human, machine and AI identity protection.

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Government agencies, cybersecurity companies and threat researchers are pouring resources into studying how fast-developing AI tools can be wielded by malicious actors to hack into victim organizations.

But as agentic AI becomes more embedded in business infrastructure, there’s also a high possibility that a breach could be caused by an insider guiding the tool, whether maliciously or due to lack of security controls.

In research shared exclusively with CyberScoop, DTEX researchers detail how a common workflow in Anthropic’s Claude Cowork used in corporate environments offers convenience for AI agent deployment but grants near-total access to the system.

Claude Cowork includes tools that let users remotely control their agents. One particular tool, known as Dispatch, relays commands from a user’s phone to their desktop Claude agent. It also includes a plugin for communicating with Salesforce AI agents that access and transfer data.

DTEX researchers tested two scenarios. The first prompted Claude to summarize information from Salesforce and paste it into a draft Outlook email. The second tasked the agent with archiving selected files and transferring them via the Cowork app.

In both cases, researchers used simple, single-turn prompts and spent between 10-30 minutes preparing to exfil  the data.

Alex Desmond, director of insider threat intelligence and innovation at DTEX, told CyberScoop that both improvements in frontier models and deeper integration of AI tools into IT network operations have reduced the time defenders have to react to a breach.

“In cyberattacks, you talk about the kind of execution time of adversaries coming in and dropping ransomware, we’re now seeing the kill chain drop to 30 and 10 minutes depending on what they’re doing,” Desmond said. “Six months ago, that was a couple of hours.”

But that speed, when paired with direct access to business networks or cloud services, can also create an insider threat nightmare for organizations that must monitor for both malicious actors and potential mistakes from legitimate employees using the technology.

Over the past few years, western IT and cybersecurity businesses have been inundated with job applicants secretly working on behalf of the North Korean government. Their salaries are used to evade international sanctions and fund Pyongyang’s nuclear program, but it also positions the individuals to access or steal sensitive data or assets from these companies. 

“You’ve got a nation-state actor getting into an environment legitimately,” Desmond said. “Now if you gave them access to AI tools on top of that…you’re like ‘here’s the keys to everything and here’s this awesome tool that’s just going to make your job – stealing our data – easier.’”

Tests by DTEX confirmed that the agents indeed had access to sensitive systems, applications and data – including the ability to download SharePoint corporate data, production documentation in OneDrive, access to Outlook email, Salesforce data (and all the data it can access), and any other files on the user’s endpoint device. For each of these applications, Claude Cowork has a dedicated plugin or API to share externally if prompted.  

To be clear, DTEX’s research does not involve exploiting a software bug or configuration vulnerability, and it doesn’t come with a CVE. It’s more of an IT governance and visibility problem. Businesses are racing to integrate AI tools into their workflow and pushing employees to use the technology while failing to put in place the kind of security controls, access policies and monitoring required to spot problems.

For instance, it may not be possible to determine how a data breach or leakage involving an AI agent actually occurred if an organization is not logging and auditing its prompts – or whether the incident was the result of an agent running amok or responding to potentially malicious instructions.

While network and cloud monitoring can identify when data is being accessed or downloaded from SharePoint, that may not be a strong enough signal to stand out for defenders.

“If a user’s normal workflow is to pull sensitive files down to work locally all the time, you don’t have endpoint monitoring and you introduce an AI agent, it then just has access to all that data” along with the ability to exfiltrate it,” Desmond said.

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Troy West was in Warsaw when his dinner was interrupted by his phone. But he was happy about it.

West, associate director of cybersecurity for autonomous offensive security company XBOW, had just learned that a trial version of the company’s platform had found a vulnerability that led to a full takedown of a development environment used by Moderna, the pharmaceutical company primarily known for its work related to mRNA vaccines.

It was, by most measures, exactly the kind of outcome a security team dreads. But for West and Farzan Karimi, Moderna’s deputy CISO, it was something closer to a proof of concept. XBOW’s product had done in hours what a human penetration tester could not — and it had done so with a level of persistence and creativity that neither of them had fully anticipated.

The episode is one data point in a much larger shift now rippling through the cybersecurity industry: The artificial intelligence models discovering vulnerabilities are moving faster than the teams that have to patch them.

Across recent conversations and presentations, industry experts said the tools are getting sharper, the attack surface is getting larger, and the gap between finding a problem and fixing it is not closing fast enough. For now, most organizations are caught between the speed of discovery and the slowness of remediation, with vendors across the industry rushing to position their products as the way through.

A shift in scale 

The inflection point came with Claude Mythos. When Anthropic announced the highly guarded model, security executives at major enterprise technology companies took notice in a way they had not with prior frontier releases. 

Zscaler was among the early organizations given access to the model, and CEO Jay Chaudhry told CyberScoop that he directed his team to use it to probe the company’s own applications.

“Are we finding some serious stuff? Yes, indeed,” Chaudhry told CyberScoop at Gartner’s Security & Risk Management Summit. He was careful to note that the findings were not necessarily more severe than those produced by other models. The issue, he said, was volume. 

“There aren’t enough resources and cycles to fix all those,” he said. 

The reason Mythos changed the calculus, according to Tom Gillis, general manager for infrastructure and security products at Cisco, comes down to code complexity. Legacy network infrastructure was built on tens of millions of lines of code developed over decades, and earlier AI models lacked the context window and reasoning capacity to comprehend it in full.

“The models couldn’t understand the entirety of it before,” he told CyberScoop. “Now they can. That’s why they’re finding all these vulnerabilities.”

The problem runs deeper than application code. Firewalls and network switches often run for decades without updates or reboots, and many have never been patched in any meaningful way. The combination of aging infrastructure and newly capable AI models has created what Gillis described as a meaningful and accelerating shift in attacker capability that the industry’s existing operational rhythms were not built to absorb.

An opportunity in existing technology 

Cisco’s answer to the oncoming vulnerability deluge is a technology it calls Live Protect, a compensated control built on eBPF, a Linux feature that lets security software operate at the kernel level to block threats without rewriting system code.

“It’s a pinpoint, laser-fine control that can shield a vulnerability on a production system,” Gillis said. “We’re not touching or modifying the binaries of that production system.”

The intent is to shrink the window between discovering a vulnerability and the next scheduled patch, allowing IT teams to fix issues without taking systems offline.

“This is a finger in the dike that plugs a hole until you get to new change control windows,” he said, acknowledging that some customers may be tempted to treat the shields as a permanent solution. 

The product has been shipping since October, but customer urgency shifted noticeably after Mythos. “Customers are like, ‘Oh, good story, Tom. I’ll think about it.’ Now it’s like, ‘Oh my God, turn this thing on right now.’”

He also noted that eBPF is open source, and said he expects the broader industry to follow. 

“While I’m very proud of Cisco leading the market with these compensated controls, I know my competitors have to do this.”

The bot that broke everything 

But shielding vulnerabilities only works if you know they exist. Karimi, the Moderna deputy CISO, faced a different problem: His vulnerability management system was surfacing hundreds of high-severity findings with no reliable way to know which ones an attacker could actually exploit. His team had skilled red-teamers, but they were finite resources. What he needed was something that could test continuously, everywhere.

“We have some very senior red-teamers and pen-testers in our organization that are pointed in a specific direction,” Karimi said during a presentation at the Gartner summit. “XBOW is covering different attack stories for us.”

West, who leads offensive security for XBOW, describes the platform as a response to a structural problem in how offensive security has traditionally worked. Human testers scope an engagement, run it, write a report, and move on. The window between tests is where risk accumulates.

“Historically you have exploit developers spending time finding the right vulnerabilities, writing the exploits, finding if those exploits are reachable, and then finding a way to chain them all together,” West said. “That takes a long time.”

Given the realities, Karimi decided to put XBOW through a trial, which produced two notable findings.

In the first, XBOW identified a web application firewall bypass on a company application built on the Spring Boot framework. The bypass involved encoding a single character (a capital “A”) as its percent-encoded URL equivalent (A), which the WAF interpreted as a legitimate request, allowing the bot unfettered access. 

The second finding, which was the cause for West’s dinner interruption, was more consequential. West had provided XBOW with access to the source code of an internal application called Orders, used by Moderna’s research partners to procure drug substances, but no login credentials. The platform identified a valid API key embedded in the source code, used it to authenticate, and then began probing the application’s APIs for SQL injection vulnerabilities.

What happened next was not entirely planned. One of those APIs handled a malformed SQL injection attempt in an unexpected way, dumping garbage data into a shared routing application that other services depended on.

“Not only was it able to kick that Orders app I showed you, but it somehow kicked over the entire ecosystem of apps,” West said.

Human pen-testers who reviewed the findings afterward confirmed they were valid, and said they would not have found them on their own. Karimi said despite the outage, his team recognized the value immediately.

“If we’re able to demonstrate where you could have an outage in a safe testing environment, that’s a great signal,” he said.

The broader value, Karimi argued, is in forcing prioritization when bugs are discovered. “If you have exploit proofs, you can provide that plus-one modifier and really point your developers to remediate the top tier of real risk that’s been validated.”

But he does worry about the volume of bugs that will be surfaced by these tools. 

“How do we now handle the volume of bugs that have gone up due to AI-driven scale?” he said. “That’s a whole other problem space.”

A broader reckoning

Across these conversations, a consistent theme was that even as defenders are trying to get arms around the forthcoming wave of bugs, it’s going to be a tremendously uphill battle. That mirrors what some of the industry’s top leaders have been saying for months. 

It also mirrors what the model developers themselves have consistently been warning about. In its announcement about expanding access to Mythos, Anthropic admitted the timeline for a publicly available tool similar to its cybersecurity-focused model is shortening, and there are no guarantees it will be released with safeguards. 

“In that world, cyberattacks could occur much more often, and in much more unpredictable forms,” the blog post reads.

Gillis was blunter about what happens to organizations that don’t move. 

“Some people will be slow to change,” he said. “But the consequence of not making that change is gonna be front-page news. It’s a massive, massive compromise. You know, like, ‘you gave up every credit card number.’ Bummer.”

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The Pentagon is focusing on integrating cyber into all its operations, and wants to make sure it integrates security into artificial intelligence usage from the outset, the Defense Department’s top cyber policy official said Tuesday.

Recent conflicts have made clear how important cyber is, said Katherine Sutton, assistant secretary for cyber policy and principal cyber adviser at DOD — especially when it’s paired with physical force.

Defense officials have noted that there’s been a cultural shift on the importance of cyber at the department since the war in Iran and the capture of Venezuelan leader Nicolas Maduro.

“Information is becoming more and more important on the battlefield, so having the ability to integrate space, cyber and other non-kinetic effects to be able to degrade that information advantage is something that’s going to be critical and foundational to any future conflicts going forward,” she said at the GDIT’s Emerge: Battlespace of the Future conference, hosted by Scoop News Group. “We have to fully pull cyber out of its silo, which means not just integrating the effects, but starting the integration from day one with operational planning … and built in from the beginning, and not something that we strap on as we’re going to execute.”

Brandon Pugh, principal cyber adviser for the Army, backed up that message at the same conference, saying that cyber “being considered in a silo is not where it’s most effective,” and is more effective “when we see cyber blending in the kinetic operations while still being an option in its own right.”

Army Secretary Dan Driscoll has made Pugh Army secretariat lead for all its defense critical infrastructure, both physical and cyber, which Pugh said emphasizes how the Army sees the two linked. The Army brought agencies together last month for an exercise to contemplate threat scenarios across domains.

By the same token, security needs to be interlaced with artificial intelligence, Sutton said. It’s a truism in the cybersecurity world that the internet wasn’t built with security in mind. As advanced AI models grow in usage at the Defense Department, Sutton said the Pentagon can’t make similar mistakes.

“As we adopt these new tools, we’re also creating a new threat landscape for adversaries to attack us and to exploit these new capabilities, so we need to start thinking about how we’re going to secure them,” she said. “One of the challenges we have often had with tools is we adopt them, and security is an afterthought, or we realize that we didn’t think about security from the front. I just don’t think we have that luxury with AI going forward.”

CORRECTED 6/3/2026: to clarify Pugh’s role on defense infrastructure within the Army.

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The Trump administration issued a revised executive order Tuesday focused on artificial intelligence, offering a significantly pared-back vision for the federal government’s role vetting AI systems compared with a draft version that was spiked weeks ago.

The order keeps in place the administration’s largely voluntary framework for companies to engage with the federal government around testing new models before release, but appears to considerably weaken or loosen provisions that had been opposed by industry.

Under the order, AI companies would voluntarily provide the federal government access to frontier models before release, but now it will be for “up to” 30 days instead of the 90-day timeline included in previous drafts.

It also explicitly states that nothing in the program will be construed as mandatory or part of a federal licensing or permitting regime, and gives AI companies significant influence to help define what models would and would not be covered under for testing.

It also states that all federal testing and access to the models would be subject to “confidentiality, cybersecurity, insider-risk, and intellectual-property protection, use, and nondisclosure requirements.”

Section one of the order highlights the central friction that has plagued the Trump administration’s AI policy since assuming power: While the White House increasingly sees national security implications in the rapid release of frontier models from the private sector, it has also been one of the loudest critics of regulating the technology for fear it could harm American businesses.

“The United States continues to lead the world in Artificial Intelligence (AI) because of the enormous talent and innovation of our AI industry, and because we refuse to stifle this innovation with overly burdensome regulation,” the order reads.

That argument was bolstered in recent days as industry members and top advisers to Trump, like tech investor and AI czar David Sacks, lobbied against previous draft language, arguing it would put too much of a regulatory burden on U.S. businesses.

On X, Sacks called the revised EO, including changes reducing the government’s access from 90 days to up to 30 days “a game changer” because it would allow frontier labs to comply without delaying new model releases. He also said the discussions he’s had with the White House indicate that not all new model releases would be subject to even that level of scrutiny.

The White House characterization that the order is not a program for conducting oversight of all new AI models “is completely consistent with the discussions that I have participated in, where it was agreed that the EO is intended to apply only to models that represent a meaningful step-change in cyber capabilities (eg Mythos), not to incremental version numbers of existing models,” Sacks wrote.

The order also puts the Department of Treasury at the head of a new interagency cybersecurity clearinghouse on AI, where the private sector, critical infrastructure operators and federal agencies voluntarily collaborate to coordinate and deconflict scanning for software vulnerabilities, discovery and validation and remediation activities, like patching.

Treasury, the Cybersecurity and Infrastructure Security Agency, the NSA, the Office of the National Cyber Director and other agencies would also be responsible for developing classified benchmarks that would be used to identify or flag the kind of advanced cyber and hacking capabilities that agencies are interested in testing.  

Questions linger over implementation, politicization

Consisting of less than 1200 words, the directive is vague in many areas about exactly how implementation will work.

“On frontier capability access, vulnerability discovery for critical infrastructure, and sharing with trusted partners, many questions remain,” wrote American Enterprise Institute fellow Ryan Fedasiuk.

Senator Mark Warner, D-Va., said the order would help the White House “begin to grapple” with the threats that new frontier models and their hacking capabilities pose to critical infrastructure and praised certain provisions, like putting the NSA in charge of classified testing of new models. But he was also sharply critical of the administration’s about face on the need for federal scrutiny of emerging AI technologies.

“Once again, the Trump administration has belatedly discovered the need to redo something it hastily dismantled in its first year,” Warner said in a statement. “While this course correction – a rehash of proposals contained in the last administration’s 2023 executive order, bipartisan congressional legislation, and each of the last three years of intel authorization bills the Senate Intel Committee has passed – can begin to grapple with widespread impacts that new frontier models will have on our critical infrastructure, it can’t undo the years wasted on dismantling some of the most vital pillars of our nation’s cybersecurity response, including key information sharing initiatives and the federal agency established to protect the security of U.S. critical infrastructure.”

Warner also said he will be “watchful” for indications the administration may politicize any testing regime, for instance, such as using the partnerships “to pressure U.S. firms into making changes to their products or Terms of Service to suit partisan or legally questionable objectives of the president and his allies.”

The administration’s lighter touch approach around voluntary testing yielded approval from some experts who have traditionally been more in favor of regulation, but who also expressed similar worries about the downsides of putting the federal government in charge of vetting AI models.

Samir Jain of the Center for Democracy and Technology, said that while AI models pose real cybersecurity threats to critical services, the order “attempts to avoid the deeply concerning implications of a mandatory licensing regime for release of new models.”

“Testing and benchmarking programs are important to promote cybersecurity and address other risks,” Jain said in a statement. “However, the EO should not become a mechanism for the Administration to punish companies for political or other arbitrary reasons, and so we will be closely monitoring the details of its implementation as they emerge.”

You can read the full order on the White House’s website.

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