Biotechnology doesn’t fall neatly into any one of the 16 government-designated critical infrastructure sectors that receive specialized and focused attention from feds, leading some lawmakers to worry that it’s not getting the protection from cyberattacks and other risks that it needs.

That’s why a bipartisan group of senators and representatives announced legislation Thursday that would place an emphasis at the Cybersecurity and Infrastructure Security Agency on defending biotechnology, biomanufacturing and biological data.

The Protecting Biotechnology and Biomanufacturing as Critical Infrastructure Act and the Protecting Biological Data Act are two separate bills with the same group of cosponsors. Both bills would weave biotech into the law that established the Department of Homeland Security.

The former would direct DHS to come up with plans to make sure biotech and biomanufacturing are protected as critical infrastructure, but not as a whole new sector. The plans would identify key biotech players, conduct outreach to them and develop steps to update the National Infrastructure Protection Plan this year to incorporate biotech sector input.

The latter would make sure that systems handling genomic sequences and sensitive biometric data are covered as critical infrastructure and integrated into the national cyber strategy, that CISA would work with biotech players on security steps like joint exercises and that the agency would get new personnel to handle biometric data security.

In the last two months, biotech giants Boston Scientific and Amgen have revealed that they suffered recent cyberattacks.

Sponsors of the measures include leaders and members of the National Security Commission on Emerging Biotechnology, a legislative advisory group.

“Biotechnology infrastructure and data are becoming vital to America’s economic and national security,” said Commission Chair Senator Todd Young, R-Ind. “Just as we are serious about where the sensitive data of Americans is stored and who can access it, we should be equally serious about protecting our biological data and infrastructure. Designating biotech as critical infrastructure is about recognizing its strategic importance and making sure the capabilities America will depend on tomorrow remain resilient and protected from foreign threats.”

Notably, however, the bills do not seek a separate critical infrastructure category for biotech to add to the 16. Currently, biotech cuts across a number of existing sectors, including the health, agricultural and industrial sectors.

Some industry groups and experts have lobbied for the inclusion of new critical infrastructure sectors, such as space or artificial intelligence.

“Protecting biomanufacturing infrastructure and the most sensitive biological data of Americans is essential for our national security,” said commissioner Rep. Ro Khanna, D-Calif. “These bipartisan bills will help ensure we are protecting this sector from physical and cyber threats while keeping America as the world leader in biotechnology.”

The bill’s sponsors in the House are Khanna, Stephanie Bice, R-Okla. and Scott Peters, D-Calif., and in the Senate the sponsors are Young and Maggie Hassan, D-N.H.

You can read the text of the bills below.

The post House and Senate members propose legislation for CISA to step up cyber defenses for biotech appeared first on CyberScoop.

A new Democratic bill in Congress would establish a federal Cybersecurity and AI Board of Investigations to provide independent government oversight of cyberattacks carried out by AI agents, following recent hacks by models run at companies like Anthropic, OpenAI, Meta and others.

The bill, introduced by Sen. Ed Markey, D-Mass., would attempt to establish a federal mechanism to investigate incidents where AI models escape sandbox environments and access live internet systems.

Currently, frontier AI companies like OpenAI and Anthropic largely control the investigation and public reporting of such incidents. Markey and other critics argue that these companies have too much control over investigations and reporting due to their financial and legal interests. 

“Despite the unprecedented depth and scale of recent AI-enabled cyberattacks, the public is learning critical details piecemeal,” Markey said in a statement. “Building stronger defenses requires a full accounting of what goes wrong, and we cannot depend on companies with little incentive to disclose their failures to give us one. We need the Cybersecurity and AI Board of Investigations to get to the bottom of major incidents and give companies and the government the critical information necessary to build resilience and better secure our economy and our country.”

Although frontier AI companies maintain external red-teaming programs and allow limited access to organizations like METR and Redwood Research, they control the scope, terms and time frames of those engagements.

The board, which would coordinate with the secretary of commerce, could subpoena witnesses and conduct “independent and impartial reviews and assessments” of AI agent-led hacks that impact federal information systems or critical infrastructure. 

It would be led by five members, appointed by the president and confirmed by the Senate for five-year terms, with no more than three members from one political party.

The board would also investigate systemic vulnerabilities in the AI supply chain, so-called “near misses” where unauthorized agent-led hacks were “narrowly averted,” and gaps in federal regulatory oversight. It would have technical staff including engineers, malware analysts, and digital forensic experts.

The board would “operate independently from regulatory review and enforcement actions without assigning legal fault or liability for any review and assessment” it conducts, according to the bill.

OpenAI confirmed Wednesday its AI agents breached a statistics portal used by the Australian government’s social services agency, Services Australia. Though the breach happened in June, OpenAI learned of the incident in August. Australian Prime Minister Anthony Albanese said the company did not notify him until Sept. 10, when it sent findings to a general government email inbox, according to the BBC.

The post New bill would create federal investigative body for AI-driven hacks  appeared first on CyberScoop.

The Cybersecurity and Infrastructure Security Agency published a paper Wednesday that lays out its plan for improving the Common Vulnerabilities and Exposures (CVE) program, a contract for which nearly ended last year before a last-minute reprieve.

The white paper outlines the components of a “Quality Era” for the program, widely used as the definitive clearinghouse for data on vulnerabilities in software and other products, even as the number of CVEs surges. 

“CISA remains committed to leading, growing and sustaining the CVE Program into the foreseeable future, just as we’ve done for more than 25 years without fail,” said Chris Butera, acting executive assistant director for cybersecurity. “Informed by CVE community feedback, this whitepaper communicates CISA’s effort to support and enable stronger participation and governance, a program-wide maturation effort.”

The CVE program has been in a “Growth Era,” according to CISA. Over 67,000 new CVEs have been published in 2026 as of last week, and the National Institute of Standards and Technology National Vulnerability Database program has seen a 263% increase in CVE submissions between 2020 and 2025. Artificial intelligence has furthered the rise.

“These pressures intensify quality challenges across the CVE ecosystem,” the white paper states. “While faster discovery and reporting can improve the value of vulnerability information when records are complete, consistent, timely, and actionable, the same acceleration can expose gaps in processes, tooling, coordination, and accountability — especially when the quality of the submissions is uneven.” 

The plan calls for advancing data quality across four key dimensions: transparent and effective program governance, broad and active participation across the global software community, data infrastructure that supports CVE operational functions and reliable CVE record content.

Some vulnerability experts have questioned whether other organizations should take over CISA’s stewardship, given budget cuts at the agency.

Butera invited further feedback from the CVE community on the white paper, which stems from an earlier strategy document on the future of the program.

Some CVE experts that CyberScoop spoke to were supportive of what CISA wants to achieve, but skeptical about elements of the white paper.

“We’ve been working around long-standing quality issues in CVE reports for decades. Incomplete or inconsistent records create real downstream work for the security tools, developers, and organizations trying to determine whether they’re actually affected and what to do next,” said Sonatype’s co-founder and chief technology officer Brian Fox. “So it’s good to see CISA acknowledge that quality has to extend beyond the record itself to governance, infrastructure, and participation across the ecosystem.”

But, he added, “I’ll believe we’ve entered a ‘Quality Era’ when we can see the improvement in the actual data and in the decisions that data enables.”

Tom Alrich, who leads the OWASP PURL Expansion Working Group that’s focused on establishing a protocol for creating Product URLs for commercial software, said CISA’s white paper ignores a particularly important and growing issue.

“I support everything mentioned. I also support the flag, motherhood and apple pie,” he said. “However, nothing in there is going to affect the CVE program’s most important problem: that a huge and growing percentage of new CVE records don’t contain a machine-readable software identifier.”

Caitlin Condon, VulnCheck’s vice president of security research, said that “CISA and the CVE program are well-positioned to both observe challenges in this space and to create (and enforce) standards that explicitly state what ‘quality’ means in CVE records.”

But she said the white paper was more the basis for a future framework than a full-fledged framework in itself.

“Many of the potential success metrics suggested in the document can be measured today, but simply aren’t shared publicly,” Condon said. “In future iterations on the framework, I’d hope to see more transparency on CVE metrics as they stand today, along with reasoning on why those metrics are the right ones (versus simply the things that are easiest to measure qualitatively or quantitatively).”

The post CISA outlines improvement plan for CVE program appeared first on CyberScoop.

OpenAI and the Ukrainian government have agreed to a partnership that will provide AI tools and subsidized computing resources to better protect the nation’s critical infrastructure from cyberattacks.

The agreement, announced Wednesday at OpenAI’s New York office, will provide Ukrainian cybersecurity officials with access to advanced AI models designed for cybersecurity work through the company’s Daybreak program. OpenAI said it is also pledging over $1 billion in subsidized tokens to support the initiative.

During a panel discussion Dmytro Kushneruk, consul general of Ukraine in San Francisco, outlined how the tools would be used for cybersecurity automation, including functions such as incident response, threat triaging, login analysis, inventorying systems, code analysis and validating vulnerabilities.

In nearly all cases, Kushneruk said the primary benefit was carrying out those functions at machine speed. But this speed is meant to complement, not replace, Ukrainians’ human expertise.

In regard to incident response Kushneruk said humans must view “thousands and thousands of these logs and they have to find what’s really important, that’s why AI can give capable defenders really much greater advantage and leverage.” 

“This is why the object is not to replace the cyber defender with AI, but to make sure the cyber defender acts faster,” he added.

Kushneruk said that for Ukraine, the partnership “is really not about protecting computers, it is about actually keeping our country running.”

Ukraine faces approximately 6,000 cyberattacks per year, or about 15 per day, according to Kushneruk. Over the past twelve years, the country’s critical infrastructure, including electricity and water systems, has endured sustained attacks from Russia in the form of cyberattacks and physical strikes.

Since Russia’s 2022 invasion, Ukraine’s critical infrastructure has been under constant threat. While missiles remain the primary concern, Kushneruk said Ukraine has been preparing to protect vital services since Russian GRU hackers shut down the country’s power grid in 2015. 

He added that while the country was “maybe not so much prepared” to deal with the fallout in 2015, it improved over time, including the resilience displayed in 2025 when trains kept running after Russian hackers attacked Ukraine’s railway system.

Some national security experts and congressional committees have explicitly cited the resilience of Ukrainian critical infrastructure as a model for U.S. industry.

Naz Durakoğlu, minority staff director of the U.S. Senate Foreign Relations Committee, said there is “pretty much across the board” agreement between the parties in favor of similar adoption of defensive AI tools by U.S. critical infrastructure operators, though issues like regulation remain sticking points.

“This is something that’s already happening, and frankly, it’s just kind of a basic duty of government to make sure that when you turn the tap on, water comes out, the electricity doesn’t go out, and hospitals keep running and treating patients,” said Durakoğlu. “So there is a broad understanding that this is a major issue, and I will say seeing what Ukraine has to go through day-to-day is also a huge wake-up call to our members on a bipartisan basis.”

OpenAI has publicly pushed for its product, and AI at-large, to be used to solve these types of problems. Company president and co-founder Greg Brockman signed an open letter released earlier this year calling for “collective action” and widespread use of AI models to find and fix vulnerabilities before the rest of the world,  including foreign governments and cybercriminals, got access to the same capabilities.

According to Politico, OpenAI CEO Sam Altman met with U.S. power companies in July to discuss using AI to protect the nation’s electrical grids.

On Wednesday, OpenAI’s national security policy head, Sasha Baker, said the company felt “urgency” to try to strike similar agreements with other governments and industries.

“There’s this period of time where we’re really rushing to get [these tools] in the hands of critical infrastructure operators, of governments around the world, of people who want to patch systems, defend their networks, remediate vulnerabilities because we know as these tools proliferate out there in the ecosystems, there are going to be bad guys out there that also try to use them,” said Baker. “So, we have this window of time to take action and we’re really motivated by the idea that we need to act with some urgency.”

The post OpenAI, Ukraine partner on ‘Daybreak’ program to protect power grids and water systems  appeared first on CyberScoop.

Dave Chismon, the NCSC’s chief technology officer for architecture, said in a blog post that the imbalance in AI means cyberattacks would likely grow as automated defenses struggle to keep pace.

President Donald Trump continued to defend his administration’s hands-off approach to AI regulation in the wake of hacks carried out by U.S. commercial frontier models that have rattled policymakers and industry veterans and spurred calls for more regulatory oversight.

In a Truth Social post Monday, Trump dismissed worries from critics that “AI is going to kill us,” comparing them to complaints from environmentalists about climate change, which he also alleged was a false narrative. He also posited that nothing may matter more than future U.S. dominance of the technology over geopolitical rivals like China.

“Whoever wins AI, WINS!” Trump posted. “We are leading now over China, and everyone else, and I’m going to keep it that way! I’m not going to stifle Growth, of something that will be bigger than the Industrial Revolution, or the internet, itself.”

Trump has previously suggested that good leadership is the only regulation the U.S. needs for artificial intelligence. He later claimed the Department of Justice was ready to “rein things in” if companies overstepped, but offered no specifics on enforcement, legal authority, or where he would draw that line.

“We will be careful, and that’s why we have the Department of Justice, and other Law Enforcement bodies, that will rein things in if we have to, but I will only encourage AI or, SI (SUPER INTELLIGENCE)!” Trump concluded.

Secretary of the Treasury Scott Bessent recently told Congress that private lawsuits could force AI companies to institute better security, saying it’s clear what the government “shouldn’t do on safety is to give these labs a liability exemption, which is what they are asking for.”

“The best way to guarantee safety is that the creators are liable for what they build and generate,” Bessent said.

Beyond existential fears, critics also argue that inadequate regulation or cybersecurity controls in current AI systems make them impossible to fully control or monitor.

Recently, former President Barack Obama criticized the argument from Trump administration officials that the free market will naturally push industry toward self-regulation and that “these companies will solve the safety issues because they have every incentive to do so.”

“If it turns out to be dangerous, people will just sue them and they’ll be worried about financial liability,” Obama said last week in remarks at Colgate University in New York. “That’s not how we treat airlines or drug companies or food companies.”

The Trump administration issued an executive order earlier this year that set up a voluntary testing regime for some commercial frontier models, largely at private industry’s discretion. That order was significantly delayed and altered by AI industry boosters to ensure that governmental review did not cause companies to postpone their release timelines for new models.

That agreement did not last long before fast-moving events caused the administration to strike another, non-public agreement with frontier AI companies like OpenAI, Anthropic and others governing pre-release testing for models.

But the Trump administration has consistently argued that regulation will harm, not help, U.S. innovation and global competitiveness, and the threat of China frequently looms large in those discussions.

Experts believe China’s AI models are behind U.S. models at the top of the market, where OpenAI and Anthropic have consistently pushed the frontier limits of model capabilities. But Chinese lower and “middle class” models are often cheaper, more efficient and can even outperform more powerful models because users can dedicate exponentially more tokens for their tasks.

The U.S. government has accused Chinese AI companies of conducting widespread, “systematic” distillation of U.S. frontier models, with the implicit encouragement of Beijing.

In defending the administration’s approach, David Sacks, co-chair of the President’s Council of Advisors on Science & Technology and a top adviser on AI issues, specifically cited the threat from China and other countries that he claimed would not be subject to similar restrictions.

“We’re not the only country that has advanced AI labs, and as the president declared…we have to win this AI race,” Sacks told Politico in May, later adding “I think that’s the first thing to recognize is that if somehow we slow down or stop AI development, it doesn’t mean that AI progress is going to stop. It just means it’s going to happen in other countries and specifically China.”

Some observers have alleged that despite their larger differences, top leaders in the U.S. and China may view AI similarly at the strategic level, specfically that increased adoption – and risks – of AI are inevitable.

Ronan Murphy, director of the tech policy program at the Center for European Policy Analysis, posited that while there may not be a formal agreement between the two countries, “they share views both in Beijing and in Washington, particularly in the White House, of: you have to allow this to happen.”

“Clearly there’s a call for regulation from many quarters of AI in the U.S. and elsewhere, but in the White House – and we heard David Sacks talking about it [recently] – It’s ‘let them cook,’ and the Chinese approach seems to be the same,” said Murphy in a press briefing. “So there might be consensus at that level, if nothing else.”

The post Citing China, President Trump doubles down on hands-off approach to AI regulation appeared first on CyberScoop.

Researchers said they used Anthropic’s Claude and OpenAI’s Codex to identify a damaging flaw embedded in a popular software decoding tool that could leave major internet platforms, enterprise services, and web frameworks vulnerable to data theft and remote access.

The vulnerability, nicknamed HEIF Heist, refers to the malware’s ability to trigger memory corruption errors in affected software, allowing the attacker to pilfer sensitive data from its victims. In a report published Thursday, the researchers laid out the potential damage an attacker could cause, including gaining access to internal OpenAI repositories, leaking user files, access tokens, and other sensitive data for online services like Amazon Web Services, and gaining remote code execution privileges across a range of online services, including Meta’s core product suite, GitHub Enterprise servers and open-source internet forum Discourse.

“Even when Remote Code Execution isn’t immediately achievable, the attack primitives may still allow arbitrary heap disclosure, letting an attacker ‘heist’ in-memory data such as other users’ data and environment variables,” wrote Hacktron researchers Harsh Jaiswal, Mohan SRK, Rahul Maini and Sudhanshu Rajbhar.

The researchers relied heavily on AI systems, including frontier models from OpenAI and Anthropic, to conduct their research. Attribution for the research is described as being “led” by the Hacktron human researchers “assisted by Hacktron Harness, GPT-5.6 Sol, and Opus 5.”

According to the research, the attack exploited the way that code parsing tools in many popular software decoders — specifically libheif and libde265, used to parse C and C++ software — process certain image files.

By uploading HEIF, HEIC and AVIF image files corrupted with malicious code, the attacker could bypass most of the victim’s application layer defenses, in many cases achieving remote code execution privileges for accounts or products tied to major AI and tech brands.   

While the latest version of libheif has been patched, the researchers said “any deployment lacking the latest upstream security patches is potentially vulnerable.”

In one incident detailed in a Sept. 13 blog, Jaiswal, Maini, and Hacktron researcher Mohan Pedhapati described how chaining two vulnerabilities, including an image parser flaw, could compromise OpenAI employee accounts.

With access to the compromised accounts, researchers could reach OpenAI’s internal repositories. As a proof of concept, they opened a pull request in the company’s “monorepo,” a centralized library where code is shared across projects, using the employee’s Codex credentials. 

According to a timeline provided by the researchers, the flaw was discovered on July 25 and patched within days. They said the entire attack, from discovering the initial vulnerability to gaining access to the repositories, took less than 72 hours. OpenAI paid them a bug bounty of $6,500 for their work.

Given that AI models are increasingly integrated into enterprise and personal networks, an attacker exploiting HEIF Heist could have accessed far more than just OpenAI’s systems and data.

“Until two months ago, a user or OpenAI employee logging into OpenAI’s own help forum could have had their ChatGPT and Codex accounts taken over,” the researchers wrote. “Since people can connect various services to Codex and ChatGPT, the scope of what we could theoretically access was huge, including GitHub, Slack and emails.”

CyberScoop has reached out to OpenAI for comment on the research and additional information.

At the same time, the researchers said the attack paths they found were not particularly easy or efficient to exploit.

“Exploitation requires fingerprinting the target version and tailoring the payload images,” the blog stated. “Some of our RCE attempts landed only after thousands of image uploads. That said, an AI agentic approach with a frontier model like GPT-5.6 Sol cut exploit development time down to roughly 1 to 3 days from initial probe to remote RCE. A motivated attacker can convert a vulnerable upload endpoint into RCE or an info leak.”

The post Researchers use AI to find widespread software decoder flaw  appeared first on CyberScoop.

The past few weeks have “felt very strange” for Juan Andres Guerrero-Saade.

Like many, he is trying to sort through the spate of frontier-model AI agents from OpenAI, Anthropic, Meta and others hacking their way onto the open internet over the past few months, particularly amid the already-heated national debate around the emerging technology and its impact on society.

Guerrero-Saade, a fellow for AI and security research at SentinelOne and an adjunct professor at Johns Hopkins University, said the hacks are worth taking seriously, but at a time when businesses and open-source maintainers should be focused on further hardening their systems and policymakers should be discussing new solutions,  “what we see is cybersecurity being used essentially as an excuse for these AI doomer arguments.”

The incidents have spawned those “doomer arguments” amid an intense public debate about the technology, the pace of industry development, and whether government and the private sector are doing enough to protect against “doomsday”-type scenarios, where AI systems take over or attack large parts of the internet or society.

Guerrero-Saade is among a growing chorus of cybersecurity professionals who say that while AI systems pose real, unique threats to our systems, the apocalypse is far from inevitable. Most of the public concerns around the incidents, let alone worries about killer AIs attacking critical infrastructure, assuming control of the internet and wiping out humanity, are either technically impossible or can largely be controlled through established cybersecurity principles.

There is this “narrative or magical thinking of ‘Well, AI is going to be able to hack everything, and therefore it can control everything, and therefore it’s going to kill us all,’” he told CyberScoop. “And you [think] these just don’t add up. They’re not very well-reasoned arguments.”

This fatalistic narrative tied to AI’s eventual dominance doesn’t hold up under scrutiny, according to experts CyberScoop spoke with. In recent conversations, cybersecurity and national security professionals raised questions about both the technical solutions OpenAI and Anthropic use to contain their models, as well as the glaring absence of federal oversight from federal regulators or truly independent third-party review.

For example, Jacob Coxon, an Anthropic employee who resigned over AI safety concerns, told CBS News that frontier models could not be “unplugged” by humans once deployed because the model would copy itself to thousands of other computers connected to the internet.

By contrast, Matt Tait, a former information security specialist at UK signals intelligence agency Government Communications Headquarters (GCHQ), pointed out that the models run by Anthropic and other frontier companies require extremely expensive, “ultraspecialist” machines that “are functionally supercomputers.”

“There is a zero chance that Anthropic’s most capable models will be able to extract their own model and run in the wild, because those supercomputers essentially only exist in datacenters,” Tait said.

“Not a credible warning”

Other former cybersecurity government leaders say the agentic hacks represent a failure by regulators and industry to deploy known technical and policy options that make it harder for these types of incidents to occur.

Matt Hartman, former deputy executive assistant director for cybersecurity at the Cybersecurity and Infrastructure Security Agency, said “we should not accept harmful AI behavior as inevitable or unmanageable.”

“There are meaningful steps companies can take to monitor agent activity, constrain permissions, detect anomalous behavior, and build stronger safeguards into how these systems operate,” said Hartman, now a chief strategy officer at Merlin Group. “Those controls will inevitably involve trade-offs in capability and speed, but that’s a familiar cybersecurity challenge. Our goal should be to manage the risk without unnecessarily limiting the enormous benefits AI can provide.”

Ciaran Martin, former head of the UK’s National Cyber Security Centre, took issue with the way the CEOs of frontier AI companies have framed the threat of “rogue” AI behavior as inevitable, while issuing dire warnings about future threats and capabilities with little transparency.

Martin’s comments came after an essay published by Anthropic CEO Dario Amodei that cited the threat of a HuggingFace-style swarm of agents that could create a botnet capable of “taking over the entire internet” within 6-12 months.

This, Martin said, “is not a credible warning,” because it doesn’t explain how the exploitation would function, how such a botnet would persist on the internet, or how it would escape law enforcement. 

 “It assumes no monitoring of systems, no anti-virus, no DDoS protection, no network segmentation, no incident management, no nothing of any kind of the cybersecurity on the global Internet of the type that has developed over the last 30 years,” wrote Martin. “For a claim of this magnitude, there is neither evidence for the contention nor a credible account of a path to this outcome.”

Meanwhile, some federal government cybersecurity leaders have touted the technology’s disruptive potential and called for more widespread adoption of AI tools by defenders.

Joseph Alm, assistant secretary of cyber, infrastructure and risk resilience at the Department of Homeland Security, said classified systems may retain stronger protections. But for most other data, AI models are “just going to know things and be able to infer things about the world, and we’re going to have to adapt to that as almost inevitable.”

Asked by CyberScoop whether the government or frontier AI companies could be doing more to prevent or deter their models from carrying out unauthorized hacks via agents, Alm cited recent efforts by the Trump administration this year to establish pre-release testing of commercial models as a step in the right direction. But he called unauthorized AI agent hacks “a new threat class” that is different from previous threats and can be easily distributed to users through open-source software today.

“I think what we can do is…encourage the building of good sandboxes, so that the best models aren’t used for this and the stuff you see out in the wild is the kind of detritus that you can actually respond to effectively and control your networks,” said Alm.

Other experts have shared similar concerns. Earlier this month, CrowdStrike CEO George Kurtz recently warned of a new threat class emerging alongside nation-states, cybercriminals, and hacktivists: “the agent state.” By pairing AI systems with small human teams, these operators can now match the speed, scale, and sophistication of government-backed hackers.

“It took a nation to fund the talent, the tooling, the infrastructure, the patience,” said Kurtz. “That scarcity is over.” 

To be sure, frontier AI companies tout their commitment to both approaches. OpenAI and Anthropic have rolled out an array of cybersecurity partnerships, external red-teaming programs, vulnerability disclosure programs and cybersecurity technical advisory bodies filled with cybersecurity experts.

Mohammed Husain, strategic delivery lead for government at OpenAI, told CyberScoop that the company deploys both internal safety guardrails for their models and relies on outside cybersecurity vendors for additional expertise.

Internally, OpenAI focuses on vulnerabilities at the training level: filtering data poisoning attacks, blocking harmful datasets, and using network controls to prevent prompt injections. For other security layers like sandboxing, identity management, networking controls, they outsource to external vendors. 

“I don’t think OpenAI has all the answers here but what we do as a research lab is we’re going to focus on levels of protection we have expertise in and we partner to self-complement,” said Husain.

AI safety vs. AI cybersecurity

In response to the HuggingFace hack, OpenAI and Anthropic have allowed third-party organizations, such as nonprofit AI research firms METR and Redwood Research, to investigate. But multiple cybersecurity professionals told CyberScoop that both firms lack incident response experience and focus primarily on AI alignment and safety. Their reporting on the hack also lacked critical details: network monitoring logs, telemetry, and other data standard in cybersecurity threat intelligence reports.  

METR president Chris Painter addressed those general concerns in a post on X, saying since 2022 the organization has worked with Google, Anthropic, OpenAI, Meta, Amazon and others on investigations and third-party evaluations. Painter said none of the AI companies fund METR and that his employees are not uniformly “doomer” or “accelerationist” around AI.

Painter also said METR’s work ensures that if AI systems become autonomous or “rogue” within a company, there are ways to share that information with governments and people “outside the company’s walls.”

“We don’t accept money from frontier AI companies,” wrote Painter. “They haven’t paid us for our work, and we don’t accept donations from them or their employees. As we’ve shared previously, multiple frontier AI companies currently provide us with free access to their models in order to perform our evaluations, research, and engineering.”

AI safety and AI cybersecurity advocates take different approaches to securing “rogue” AI behavior. Safety advocates focus on aligning models around ethical training and behavior. Cybersecurity advocates argue that technical and regulatory controls must go further—actively preventing models from accessing what they need to carry out malicious behavior.

Guerrero-Saade said sandboxes in particular can easily be programmed with aggressive cybersecurity monitoring in order to spot when something odd may be happening and react in real time.

“I can’t think of an easier situation in which to set up trip wires, set up configurations like DNS servers, just different parts where you can say ‘Hey, anomalous behavior is happening,’” he said. “We should have been able to tell this immediately, not weeks and months later. So watching [the AI hacking incidents] go down is a little ‘crazy-making’ because we’re seeing things that, frankly, look like neglect, negligence, people just mishandling things, and then being told that these are categorically new incidents that mean that AI systems need to be treated completely different from anything that’s come before.”

While cybersecurity experts say AI systems are, at their core, still software, they do operate differently from more traditional code in ways that can make them harder to predict and control.

John Hultquist, chief analyst at Google’s Threat Intelligence Group, said most software has been deterministic. It may have bugs or vulnerabilities, but an expert could generally understand how it would react to certain stimuli, making it easier to design straightforward controls.

AI models are non-deterministic, with far more variability than traditional software. That can break security controls that rely too much on predicting behavior in advance. Using AI to enforce security controls on other AI models faces the same problem: the systems being deployed to control AI are just as unpredictable. 

But people are also non-deterministic, and people have developed systems in other industries and practices to account for that.

Hultquist drew on his Army experience, noting that “they give incredibly dangerous, expensive things to 18-year-olds” and expect responsible use. The military manages this through two types of controls: deterministic ones like strict weapons and ammunition protocols, and non-deterministic ones like human officers who monitor and correct violations.

Similarly, established cybersecurity controls have been used by incident responders to detect and prevent or mitigate ongoing cybersecurity breaches.

“I don’t think we should throw out all the other tools that we have learned to use as well. I think that would be utterly foolish,” he said, later adding “I will say that if we use only non-deterministic tools to figure out when things are happening, we shouldn’t be surprised when we get the wrong answer.”

The post The AI hacking apocalypse is not inevitable appeared first on CyberScoop.

“It's really complicated, and I wouldn't want to do something in a lame duck session to do it quickly and not get it right,” said House Energy and Commerce Chairman Brett Guthrie about the FRONTIER Act.

Anthropic is testing a new personal finance feature called "Claude Money" that will allow you to connect your bank accounts directly to Claude and "understand your money." [...]

A Cybersecurity and Infrastructure Security Agency program that provides tools and capabilities to other agencies has to get speedier so it can push them toward being able to move more quickly themselves, an agency official said Tuesday.

“We have to get faster,” said Richard Grabowski, acting branch chief of service delivery and deputy program manager for the Continuous Diagnostics and Mitigation program at CISA. “The way that we collaborated today wasn’t fast enough for the threats of yesterday, and they certainly aren’t going to be fast enough for the threats of tomorrow.”

That means pushing responsible automation of tasks that also can do so at scale, he said, so that experts “can focus more [on] dealing with the novel threats and adoption and tuning of advanced technology, and not hitting alerts every other day.”

Velocity is one of the three core goals for the CDM program, along with unification and data-driven risk management, Grabowski said at the Elastic Federal Cyber Defense Breakfast, produced by FedScoop.

Unification means keeping data out of silos so “we are connecting those deployments in a meaningful way to really stimulate reusable, actionable lessons learned,” Grabowski said. And data-driven risk management means that in the event of a crisis-level event, agencies are able to “see what is happening with timely, accurate, and trustworthy data, so that we are the tool of first response when the things hit the fan.”

One of CDM’s offerings is Security Information and Event Management (SIEM) as a Service, a cloud-based platform for threat analytics, incident response and more. Grabowski said there’s a three-year roadmap for expanding and enhancing it, including by ramping up staff and conducting training.

Mike Duffy, the acting federal chief information security officer, said at the same event that three principles should guide what comes next for CDM. One is aggregating demand across agencies that share common problems: “When agencies need the same capabilities, we should use federal scale to improve security, interoperability and value.”

Second, he said, “is buying outcomes, not product” by making it clear what outcomes the federal government is seeking and then allowing commercial markets room to innovate. 

Duffy said the third was to “design acquisition for continuous improvement,” meaning making sure that acquisition models promote competition and opportunities for new capabilities to enter.

“Now is not the time to set capabilities and move on for the next 10 years,” he said. “Mow that agile mindset of how we can continue to deliver and deploy capabilities based on the threats we’re seeing to reduce risk at scale across the federal government — that is absolutely key.”

CDM has been evolving since the SolarWinds breach that compromised at least nine federal agencies, said Matt House, CISA’s acting associate director and program manager for CDM.

“Post-SolarWinds, one of the things that that the government took away was, we lack what I would say is a common operating picture with respect to the operational visibility we need to be able to assess and coordinate response government wide,” House said at the event.

The post What’s next for CISA’s CDM program that gives cybersecurity tools to federal agencies appeared first on CyberScoop.

Researchers say they have discovered thousands of malicious software packages uploaded to an online public software repository that were left by a “swarm” of OpenAI agents.

According to an incident timeline published Friday by researchers Spencer Kitts, Thomas Larsen and Sydney Von Arx, the campaign began May 5 when they observed a handful of suspicious packages being uploaded to RubyGems, a public library for the Ruby programming language. By May 11 and 12, the site saw more than 2,000 malicious uploads from the same actors before RubyGems maintainers halted new user sign-ups for four days to stop the flow.

In one instance, the agents attempted to exploit a very recent vulnerability that had only been discovered this past July that would have given them access to RubyGem user API keys. According to Colby Swandale, the technical lead at RubyGems, the flaw involved an improper cache configuration. While initial access logs showed no evidence of malicious key use, Swandale acknowledged the review was limited in scope and inconclusive. 

According to the report published Friday, the agents also used “disposable” email addresses and exploited another bug in RubyGems platform (since patched) that allowed them to register new accounts and gain API keys without verifying their email address.

The researchers said their understanding, based on discussions with “people in the RubyGems community,” is that OpenAI had yet to disclose the involvement of their agents in the May campaign.

An OpenAI spokesperson told CyberScoop that the company is aware of the incident and said they were in contact with both the researchers and RubyGems to conduct a broader review. The company characterized the episode as “benign,” describing it as routine training runs where agents attempt to access publicly available data.

“Based on our review, our agents used the RubyGems platform to access the internet to carry out benign tasks and retrieve public information,” the spokesperson said. “We’ll continue to investigate as part of our broader review of agent activity during training and evaluation.”

In many ways, the agents were not subtle about their identities or goals.

Days into the campaign, researchers noticed that some of the packages had “oai” in their filenames, while fifteen of them had “oai” set as their author and another listed the email “openaixyz65947@gmail.com” as their point of contact.

They also “clearly regarded what they were doing as hacking,” naming some of their files “hack.rb,” “evil.rb,” “inject.rb” and “exploit.rb.” Other packages were given names like “pwnp999,” “exfiltestwand3,” and “hacksvn,” and comments referring to things like a “malicious probe” or “#hack” are present through the files.

They also said the actors’ behavior was extremely similar to another incident revealed earlier this month where OpenAI agents flooded a German wiki  with thousands of hacking-related posts. OpenAI has confirmed their agents were involved in that incident.

The RubyGems campaign used some of the same retrieval methods as the German Wiki agents, while thousands of malicious packages uploaded included a similar snippet, r.jini.ai, that was contained in the German posts.

Cybersecurity company Socket first flagged the campaign in a threat intelligence report posted May 13, but it does not mention or attribute any of the activity to OpenAI or AI agents.

However, the researchers said they had only limited visibility over the model’s actions and how successful some of them were, noting only OpenAI had the full details.

“This analysis is entirely based on the publicly available RubyGems packages uploaded by these agents,” the researchers wrote. “However, we do not have access to the rest of the AI behavior, in particular the chain-of-thought produced by the model during the incident, which is internal to OpenAI. Therefore, we do not know why the AI agents chose this strategy or whether it was successful.”

OpenAI’s spokesperson told CyberScoop that to date, they have not been able to verify the specific claims about malicious packages or exploitation detailed in the report and are continuing to investigate.

The post Researchers say OpenAI agents were behind May hacking campaign targeting RubyGems appeared first on CyberScoop.

Wildberries told several Russian media outlets earlier this week that payments to some sellers were delayed by security measures introduced after a distributed denial-of-service (DDoS) attack targeted systems used to track and withdraw their earnings.

CISA's cybersecurity, infrastructure security and emergency communications divisions are among the priorities as the agency fills vacancies created at the beginning of the Trump administration, acting director Nick Andersen says.

The new record total for Patch Tuesday is 973 vulnerabilities.

OpenAI is investigating an ongoing incident causing ChatGPT image generation failures and delays when uploading files. [...]

Two populous states and two large cities are among the U.S. jurisdictions where leaders have taken direct action to address criticisms of automated license plate readers (ALPRs).

OpenAI appears to be testing a new "Writing Style" feature for ChatGPT that can learn how you write by looking at examples from your connected apps. [...]

OpenAI is now rolling out ChatGPT Astra, its most powerful model to date, to those with a $20 Plus subscription, but there's no word on when free users will get access.. [...]

Russia's data centers are concentrated in areas increasingly exposed to Ukrainian drone attacks. The Kremlin wants them to stiffen their physical defenses.