The Trump administration executive order on artificial intelligence tried to strike the balance between responsible use, security and mutual benefit, all with an eye toward not making it regulatory in nature, National Cyber Director Sean Cairncross said Tuesday.

“Everyone is working towards the same goal in terms of protecting the country and securing our systems, and we are trying to ensure that defenders have this technology as quickly and at scale as possible, but there are obviously specific security concerns, and industry has been very sensitive to this as well,” Cairncross said at the Black Hat 2026 conference in Las Vegas.

The security concerns about AI have moved to the forefront of discussions about the technology after OpenAI models escaped a test environment to hack the company Hugging Face last month.

“The design of this is that when there is something that happens, when there is a breach, when there is an event, that that system, that network of connections can exist, adapt to that, and seek to remedy that as quickly as possible, so that form follows function rather than turning that upside down, and as usual with the government pen just proceeding in a vacuum,” Cairncross said.

The Trump administration has drawn criticism over whether it has struck the right balance on AI rules. Trump’s AI executive order notably got pulled just before its scheduled release, with the final version signed in June missing some aspects that had drawn industry opposition.

“What needs to be built is a flexible, adaptable structure that enables information sharing between industry and government, so we can guarantee that this technology benefits everyone it’s going to benefit, but is used responsibly and securely,” Cairncross said.

He said the administration is working with industry during implementation of the executive order.

“A regulatory regime would not only strangle growth, development, and innovation, and be enormously harmful to the industry, but it would be obsolete 48 hours after it was gone through whatever process it had gone through,” Cairncross said.

Open source will play a “vital” role in the U.S. spreading its vision for AI across the globe, he said.

“We are extremely interested in looking at ways to build U.S. open source, make it competitive, make it the preferential adoption by planet Earth,” Cairncross said. “We understand and appreciate the value to the ecosystem that it has, the innovation, the startups who rely on it, the leap forward it makes possible in ways that otherwise would never happen. And so I think it’s an incredibly thriving ecosystem in AI right now, and we are looking to do what we can to grow, foster, and push that U.S. open source model.” 

Speaking at the same conference, Nick Andersen, the acting director of the Cybersecurity and Infrastructure Security Agency, seconded Cairncross’s comments about AI executive order implementation. He touted the Gold Eagle clearinghouse as one example.

“Those are fantastic opportunities we have to really provide a unifying function around the way that we’re going to do AI-enabled vulnerability reporting and disclosure at scale in a way that we haven’t had to do before with some of our legacy platforms, and just continue to expand out those opportunities,” he said. “That access — to build off the director’s point earlier — to really enable that industry collaboration, that’s so key and critical to us as we move forward.”

Matt Kapko contributed reporting to this story.

Updated 8/5/2026: to include comments from Andersen.

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The Cybersecurity and Infrastructure Security Agency published a guidebook for federal agencies Thursday to aid them on managing security risks with open-source software, touching on topics like patching and open-source AI models.

An executive order President Joe Biden signed and that President Donald Trump amended ordered CISA and other agencies to issue open-source security recommendations to federal agencies. But the guidance is also timely, given a recent slew of attacks on open-source software (OSS).

“As part of our statutory mission, CISA remains laser-focused on enhancing the nation’s cybersecurity by collaborating with government, industry and the open-source community to understand and securely use OSS,” said Chris Butera, acting executive assistant director for cybersecurity. “CISA encourages federal civilian agencies to review this guide and implement the principles and practices to improve risk management, better execute their mission, and better serve the public.” 

The document, “Open Source Software: Security Principles and Practices,” touts the advantages of open-source software — which anyone can use, modify and share — as offering benefits in efficiency, cost, security transparency and more, but notes that it also has unique tradeoffs.

“All software carries risk, and OSS is no more or less risky than other software. The key distinction is that, with OSS, agencies can directly assess code quality and security, rather than relying solely on vendor assurances,” the guidance reads. “OSS is increasingly intertwined with emerging technologies such as artificial intelligence. Agencies that adapt to OSS’s unique characteristics will position themselves to meet future challenges and leverage new innovations.”

The guidance says that agencies need to take steps to evaluate the trustworthiness of an OSS project before approving an OSS component for use, and track OSS in their asset management repositories. It details how agencies should deal with patching, including when there’s a new OSS vulnerability that doesn’t have one. It offers advice on how agencies might contribute to OSS projects, produce them and secure rights for government reuse of code when contracting for custom software development. And it explains how it should approach open-weight AI models.

“Agencies should approach ‘open source’ AI systems differently from other OSS because open source licenses for AI software do not require the level of transparency needed to evaluate the trustworthiness of the software,” the guidance states.

Æva Black, an open-source security expert and former OSS lead at CISA, said she applauded her former agency for the guidance, telling CyberScoop that it “demonstrates a grounded understanding of the global, diverse, and participatory nature of open source software development, and provides essential guidance for federal agencies to safely use open soure during a crucial moment.” 

She singled out its recommendations on the risks of deploying unverifiable open-weight AI models on sensitive networks.

“Due to recent advances in AI, particularly in large language models capable of finding and exploiting software vulnerabilities, vulnerability management is facing a global crisis,” she said. “Many proprietary software vendors are using this as an opportunity to spread ‘fear, uncertainty, and doubt’ about open source in order to capture public attention, and, I presume, public money — but when used responsibly and maintained collaboratively, I believe open source software is, and will remain, the safest and most cost-effective means for building large scale public infrastructure.” 

CISA has produced a bevy of security guidance and updated advisory materials this week: on the creation of software bills of materials written in conjunction with other agencies and allied governments that won praise from experts; on the isolation of vital operational technology during a crisis, also written with other agencies and allied governments; and the release of updated secure cloud configuration baselines for Google Workspace.

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One of the most difficult obstacles to overcome in the quantum race will be the supply chain, given how diffuse it is, a top White House official said Wednesday.

“Supply chain is one of the biggest challenges in my mind, and really, the challenge with the quantum supply chain is that quantum is not defined by a single hardware platform,” said Brad Blakestad, director of the National Quantum Coordination Office within the White House Office of Science and Technology Policy.

“If you look at the quantum computing technologies, the quantum sensing technologies, the networking — those are all different,” he said in a webinar hosted by Inside Cybersecurity and USTelecom. “And even within computing, there’s seven different modalities that use completely different components. So we have this not just one monolithic supply chain, but just a bunch of different supply chains that are kind of intertwined in various ways.”

Blakestad made his remarks a little more than a month after President Donald Trump signed two executive orders on quantum computing. He referenced proposed ways to address the supply chain challenge in one of the orders.

“The other major issue or challenge that we face right now is that we’re on the cusp of quantum exploding from a commercialization perspective, but we’re not quite there yet,” he said. “So there’s not the funding, the revenue coming from large-scale quantum companies at this point to really make the supply chain as robust as you would want. So thinking about it from the government perspective, it’s just [that] there are too many places that I would want to bolster and not enough funding to do it.”

Blakestad touted steps to help that along such as the government buying widgets from a company that makes them to certain specifications, or prize challenges.

The quantum supply chain isn’t just diffuse in the United States, an International Institute for Strategic Studies policy paper noted Wednesday. It’s “inherently international: no single country dominates the supply chain, whether specialised materials, cryogenic equipment, hardware, software, fabrication or algorithms,” the authors, Dongyoun Cho and Maria Shagina, wrote.

And a March report from the Center for a New American Security identified strengthening the quantum supply chain as pivotal to the United States seizing the benefits of the technology, citing gaps in the U.S. supply chain and reliance on foreign suppliers such as China and Russia. 

Supply chain wasn’t the only obstacle Blakestad mentioned as looming large.

“The encryption challenge is a real challenge, and we want to make sure that we are aware of when quantum computers will ultimately get to a scale that they start having these sorts of implications and move as quickly as we can,” he said. “So, just by owning the technologies, by owning the workforce, by making the United States the place that people want to come to be on the cutting edge of this technology, I think that kind of addresses both of those issues, and that’s what makes it so critical.”

Another difficulty is measuring progress, Blakestad said: “It’s also very, very hard to benchmark, and to know that you’re actually doing what you’re supposed to, what you are intending to do.”

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Months before the Hugging Face breach, Emergence AI published research that investigative journalist Ronan Farrow made public. Ten autonomous AI agents operated across five virtual environments for fifteen days without human intervention. Much of the attention focused on Grok 4.1 turning violent and Gemini 3 Flash committing 683 crimes.

What mattered more went unnoticed: Anthropic’s Claude Sonnet 4.6 built a peaceful democracy in isolation, then stole resources from neighboring environments the moment it joined a shared one. The lesson was clear: safety is not a model attribute. It emerges from the operating environment. The models didn’t change. Working as designed, their behavior evolved as the environment changed. The lesson is hard to ignore: The governance environment changed, and with it, the reward dynamics.

The story here concerns institutions, specifically OpenAI’s and Hugging Face’s, and how we must understand their recent security incident through that lens.

The industry agrees on how the Hugging Face breach happened. Cybersecurity experts have focused on the vulnerabilities, how they were used, and remediation. OpenAI has highlighted the model’s capabilities. Both conversations matter. What requires attention is why this breach is strategically important. After spending the past weekend discussing it with policymakers, security researchers, and industry practitioners in Aspen, I came away convinced we’re examining the wrong problem.

In 1961, Yale psychologist Stanley Milgram’s experiments revealed a broader truth: changing the institutional architecture changes behavior without changing the actor. The Emergence AI researchers didn’t change Claude’s agent. They changed the governance architecture that determined what constituted success for the system. Claude’s behavior changed with it.

OpenAI built a smart model but forgot to build a smarter room. That choice made the Hugging Face breach possible. Every organization now deploying autonomous agents now faces the same governance problem.

OpenAI gave the agent one objective: pass a cybersecurity evaluation. To stress-test it fully, they loosened the safety restrictions, and the agent found a shorter path. Rather than solving the evaluation directly, it found the answers outside the test environment, escaped its sandbox, and exploited a flaw in Hugging Face’s data-processing pipeline to reach live production systems. Over the weekend, with no human oversight, it ran more than 17,000 automated actions by escalating its own access, moving through internal systems, and harvesting credentials.

Hugging Face is one of the world’s most prominent AI companies, valued at approximately $4.5 billion. It provides the infrastructure that governments, defense organizations, and technology companies use to build and deploy AI. The agent was pursuing the objective it had been given. Breaking into Hugging Face was the fastest path to passing the test. Governance set the goal, the level of risk to accept, and who was accountable. Technical design determined whether those governance decisions could be enforced. As researchers James Shires and Max Smeets have argued, for a model capable enough to act on its own, testing and deployment must both must be governed the same way.

AI agent design requires baseline standards. Observability, including a monitoring layer that flags when an agent goes beyond its scope, is a baseline requirement. Human review also matters at escalation boundaries, like when an agent shifts from internal tools to external ones. When any agent crosses that boundary, what alert fires? What human reviews it? We lack clear answers to either. That is a governance choice, not simply a security failure. At best, this was a catastrophically failed test. At worst, how can we trust any frontier AI company to self-govern autonomous agent deployment?

More than a decade ago, the U.S. Department of Defense built the Comply-to-Connect (C2C) program: every device connecting to sensitive networks must prove it belongs there, or it is cut off from the network. C2C works because the quarantined actor stops. A laptop that fails verification goes offline and stays there. An autonomous AI agent adapts around enforcement. C2C was built for passive actors. Governance for autonomous agents must accommodate ones that adapt. Visibility is not enforcement, and enforcement is not control. We are missing all three.

A second failure that is not being discussed enough: the breach exploited an implicit trust assumption in Hugging Face’s data-processing pipeline, where inputs were treated as trusted without verification. After SolarWinds, the U.S. government set rules for software supply chain integrity: Executive Order 14028 and verification demands for federal software. The principle was simple: trust must be verified through proof. Those principles have not yet been comprehensively or consistently applied to the AI model supply chain. The rules remain weak. No one has been asked to explain why.

The answer is not a new framework. Existing frameworks suffice. C2C proved that visibility without enforcement leaves gaps, while Executive Order 14028 established that trust in software supply chains requires proof and verification. The challenge lies in applying these principles to a new category of actor. Congress, the Cybersecurity and Infrastructure Security Agency, or the Office of Management and Budget should make formal determinations that autonomous AI agents must follow the same rules as every other actor on a federal network. The framework exists; it must be updated.

The next incident is already in progress. It will show up in the logs as odd traffic, get handed to the same people who published these frameworks this week, and spark another round of recommendations no one acts upon. We’ve solved this problem before: for devices, for software, for supply chains. We know how to build smarter rooms. The tools exist. The will, the authority, and the decision to govern remains absent.

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The Trump administration asked the Supreme Court on Monday to let it enforce an executive order that would restrict mail-in voting, after a federal appeals court kept the order blocked in nearly half the states just months before the November midterm elections.

Solicitor General D. John Sauer told the justices that a Massachusetts federal judge acted too soon when she struck down key parts of the order, which blocked federal agencies from carrying it out in 23 states and the District of Columbia. Sauer said the order only directs agencies to study changes and has not yet produced a final rule, so no state has suffered harm. 

“The district court preemptively decided that whatever the agencies may choose to do will necessarily be unlawful,” he wrote. He asked the court to pause the injunction while the case moves through the appeals court, and to grant an immediate stay in the meantime.

President Donald Trump signed an order in March that directs the Department of Homeland Security to compile lists of confirmed U.S. citizens in each state and send them to election officials, along with directing the U.S. Postal Service to draft rules on mail-in and absentee ballots. California and 22 other Democratic-led states sued three days after Trump signed the order, arguing the Constitution gives states and Congress, not the president, power over elections.

U.S. District Judge Indira Talwani ruled in June that the administration lacked power to build its own citizen-voter database and that the Postal Service could not impose new rules on states’ mail ballots by itself. She also found the order’s enforcement language amounted to an improper threat against local election officials. 

In Monday’s filing, the administration leaned on a 2020 case, Trump v. New York, in which the justices threw out a challenge to a separate Trump order on census counts because it was too soon to know how agencies would carry it out. Sauer argued the same logic applies here. The order tells agencies to act only “to the extent feasible and consistent with applicable law.” That wording, he said, means the Postal Service and Homeland Security could still drop or narrow the changes once they finish reviewing public comments and checking what the law allows.

The filing follows a string of fights over how the 2026 midterms will run. Earlier this month, Trump gave a prime-time address reviving his claim that the 2020 election was rigged, this time pointing to China, without providing any new evidence.

The filing also follows a Supreme Court ruling in late June that let states keep counting mail ballots that arrive after Election Day if postmarked on time. 

You can read the full filing below. 

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The State Department will restrict visas for cybercriminals like scammers to sextortionists, and in some cases even their family members, Secretary of State Marco Rubio said Thursday.

The Trump administration has sought to make a crackdown on foreign-based scams one of the signature issues of his second term. An executive order that the president signed in March indicated that visa restrictions would be on the table as one response.

“By restricting visa issuance to those who are responsible for or complicit in these criminal enterprises, we are sending a clear message: The United States will go after those who prey on our citizens,” Rubio said.

Other departments have also made efforts to reduce foreign-run scams. In June, the Department of Justice seized infrastructure used by subsidiaries of the Huione Group, a Cambodia-based corporate conglomerate tied to one of the world’s most prolific criminal marketplaces used to commit cyber scams and other crimes.

Rubio authorized the visa restrictions under a 1952 law that gives the State Department the ability to deport or rule as inadmissible someone who poses “potentially serious adverse foreign policy consequences.”

Critics have accused the Trump administration of abusing that provision of the law for political purposes.

Rubio’s statement on the visa restrictions mentions “individuals responsible for, or complicit in, cybercrime and cyber-enabled crime, such as those involved in cyberscams, and sextortion.”  Furthermore, he said, “Immediate family members of individuals engaged in such illicit activities may also be subjected to visa restrictions.”

Betsy Cooper, Founding Director of the Aspen Policy Academy, said the visa restrictions on cybercriminals could be valuable, but offered a caveat.

“Scamming people is a growing global enterprise, and it is a laudable goal to penalize those who scam and defraud people since they so rarely suffer consequences for their actions,” she said in a statement to CyberScoop. “So long as the new visa controls are used narrowly and deployed only against verified scammers and fraudsters, this is a positive step toward combatting cyber-enabled crime.”

While some cyber experts have questioned how much visa restrictions, prosecutions and other punishments of cyber miscreants who are based overseas will affect them, others maintain that it can serve as a deterrent to those who would consider getting into the line of work but want freedom to travel the globe.

FightCyberCrime.org, a nonprofit that seeks to help cybercrime victims, applauded the restrictions on the cybercriminals.

“We welcome efforts to hold cybercriminals accountable across borders. Cryptocurrency investment scams, romance scams, and sextortion cause devastating financial and emotional harm to victims,” it said in a statement to CyberScoop. “Meaningful disruption of these transnational criminal networks is an essential part of the response.”

But there’s still a long way to go in the fight, the statement continued.

“At the same time, we must invest more in victim support, prevention, and recovery resources,” the organization said. “Accountability is critical, but ensuring victims have access to trauma-informed support and resources is equally important.”

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New executive order calls for end-to-end visibility into defense supply chains, including software dependencies, foreign ownership and cyber-related supplier risks.

The post Trump Orders Defense Contractors to Map Software, Suppliers Across Critical Supply Chains appeared first on SecurityWeek.

The Trump administration unveiled its new federal clearinghouse for sharing AI cyber threat information between the government and private sector, and said the project is already receiving threat intelligence on cybersecurity vulnerabilities and prioritizing patching.

Created last month through a White House executive order, “Gold Eagle” will be managed by the Department of the Treasury, with contributions from the Cybersecurity and Infrastructure Security Agency, Department of Homeland Security, and Department of Defense, as well as open-source software providers, critical infrastructure operators and industry.

“Under President Trump’s leadership, the Treasury Department is working hand in hand with the private sector to safeguard our financial institutions, close vulnerabilities, and protect the integrity of the U.S. financial system,” Secretary of the Treasury Scott Bessent said in a statement. “Treasury, along with our partner agencies, will continue to harness frontier AI capabilities to stay ahead of our adversaries and defend the American people from emerging threats.”

Gold Eagle is meant to help both public and private organizations find, fix and patch vulnerabilities found using AI tools before they’re discovered and exploited by bad actors. The work will involve using AI to find cybersecurity vulnerabilities in victim systems and software, and Secretary of Homeland Security Markwayne Mullin said it would also further explore ways for the technology to be leveraged for cyber defense.

A senior White House official told reporters on a background call that closed source models from frontier AI models, including Anthropic’s Mythos, will be used to discover vulnerabilities.

White House officials said they worked with the Software Engineering Institute, SEI at Carnegie Mellon University to develop a new platform, the Vulnerability Information and Coordination Environment – or VINTS – to receive third-party reports on AI-discovered vulnerabilities. According to the White House, the system has already begun collecting intelligence on vulnerabilities and prioritizing patches.

“I think on the early side of this, we have seen that the scale of vulnerability discovery, particularly with users of new technology to scan their system, is something that is a step function change [than] we’ve seen seen before,” the official said.

As AI models have improved at carrying out core cybersecurity-related tasks – like scanning code for vulnerabilities or developing proof-of-concept exploit code – cybersecurity experts and policymakers have become increasingly worried. The modern internet is rife with insecure code, misconfigurations and other mistakes that can be identified and exploited faster than ever before using AI tools.

Vulnerabilities in open-source software can be both widespread and hidden, as many commercial software products on the market rely on open-source code but few bother to document it. When hackers compromised a logging tool in the Log4J open-source Apache software library in 2021, it required a massive, multi-month coordination effort by CISA, the private sector and other stakeholders to find and fix affected pieces of software.

The White House official said the work of Gold Eagle is reflective of the administration’s “full support” of U.S. open-source software providers and maintainers.

Open source tools are “vital to systems that run throughout our country and daily life,” a senior administration official said, speaking to reporters on background. “It is being maintained by a talented group of people and entities and we will do everything we can to support the strength of that community.”

Michael Daniel, former White House cyber coordinator under President Barack Obama, told CyberScoop that AI is still so new that policymakers continue to observe its impact and adapt. While some existing communication channels for sharing cybersecurity threat information could probably be duplicated for tracking AI threats, there is still much for policymakers to learn more about the technology, the kind of threats it produces and its ecosystem of stakeholders.

“It may turn out at the end of the day that phishing is still phishing, and the fact that now you’ve got AI tools doing it, it’s still phishing. Or there may be something fundamentally different about it that we need to figure out how to combat and share information around,” he said.

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The AI-focused executive order President Donald Trump signed last month gave the Treasury Department, the National Security Agency, and the Cybersecurity and Infrastructure Security Agency (CISA) 30 days to establish a new “AI cybersecurity clearinghouse.” The deadline passed last week.

The clearinghouse is meant to coordinate the scanning, discovery, and validation of software vulnerabilities in critical infrastructure, and then prioritize how those vulnerabilities get patched and distributed.

It’s the right problem to solve. The question now is whether what is created will actually solve it.

The risk is that urgency produces something that looks like a clearinghouse, but functions like a committee: collecting information, convening meetings, and then stalling when it gets to the hard part.

Going beyond bug discovery is mission critical

It’s counterintuitive at a moment when AI-assisted vulnerability discovery is advancing rapidly, but the hard part is no longer just finding bugs. Those of us working at the intersection of AI and cybersecurity know where the real bottleneck is. HackerOne has seen it firsthand as a launch partner in Patch the Planet, OpenAI‘s initiative to use AI to find and fix vulnerabilities in critical open-source software at internet scale. The lesson underpinning that work, and informed by more than a decade of running vulnerability disclosure programs, is consistent: AI tools can surface vulnerabilities faster than anyone can act on them. What lags behind is everything that comes after discovery: deciding which findings are real, assessing severity in context, writing and testing a fix, and getting a patch accepted and deployed by the people responsible for maintaining the affected code.

Experienced human reviewers frequently disagree with AI-assigned severity ratings, because a model cannot see a project’s threat model or operational context. Software providers, especially the many volunteer open-source maintainers that so much of today’s digital infrastructure rely upon, face a relentless queue: verify the claim, assess the importance, write the patch, coordinate disclosure. AI has accelerated the incoming volume without yet equally accelerating our people and processes’ capacity to manage it. Better bug-finding tools mean you find more bugs. The improvements that really matter are the ones that help defenders push patches out and get them deployed faster.

That lesson should sit at the center of how the clearinghouse is designed.

If the clearinghouse focuses primarily on scanning coordination, which the executive order’s text emphasizes, it risks widening that gap rather than closing it. A body that finds more vulnerabilities but cannot move them to resolution is not a security win. At national scale, it is a backlog generator.

Laying a foundation for success

The administration can get this right, but it requires building the correct infrastructure now, not layering it on later.

The clearinghouse needs to do more than coordinate scanning. It needs to actually triage the results. Its core job should be filtering reports to identify which findings are truly credible, exploitable, and consequential for critical infrastructure. Using shared validation standards and risk-based prioritization, it can determine what warrants a national response. Otherwise, it’s just automating bigger backlogs.

Second, the clearinghouse also needs to tackle something more fundamental. Defenders don’t have the resources to respond to what gets reported. Vulnerabilities in critical infrastructure often live in open-source code maintained by small teams or individuals with no formal obligation to respond to disclosures and limited capacity to act quickly. The clearinghouse should work with the National Institute of Standards and Technology (NIST) to develop guidelines for open-source maintainers on structuring repositories and workflows to speed up patch review and deployment.

These guidelines should include how to use AI-assisted patching and clarify what downstream consumers of open-source code should do to help maintainers address vulnerabilities.  Federal policy should create incentives for downstream users to share responsibility for remediation through funding, engineering support, AI-assisted patch development, and procurement requirements that reward participation in coordinated vulnerability response.

Third, the clearinghouse should treat software bills of materials (SBOMs), the structured inventories of the components that make up a software product, as foundational infrastructure. SBOMs are what make it possible to trace where a vulnerable component lives across the supply chain. Without them, validated findings won’t be fixed fast enough at scale.

Finally, the clearinghouse should measure success based on what is fixed, not based on what is discovered.  Agencies need to publish data on validation rates, time-to-patch, adoption of fixes, and recurring classes of vulnerabilities. These metrics help AI systems, software vendors, and policymakers to continuously improve how vulnerabilities are addressed.

Most importantly: the agencies standing up this clearinghouse should resist the temptation to build its operational model from scratch. The private sector and the open-source security community have years of experience running exactly the kind of vulnerability intake, triage, and coordinated disclosure workflows the clearinghouse needs. The executive order wisely calls for voluntary collaboration with industry. That collaboration should be structural, not advisory, embedded in how the clearinghouse operates from the start, not bolted on after the architecture is already set.

The clearinghouse can work. But the challenge is no longer finding vulnerabilities. It is building a system that can turn discoveries into action. That is how its success should be measured.

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Post-quantum cryptography didn’t sneak up on the industry. 

For years, security teams, standards bodies, hyperscalers, and governments have been pointing at the same horizon: a cryptographically relevant quantum computer will, eventually, dismantle the public-key algorithms underpinning today’s enterprise security. The latest executive order doesn’t introduce a new threat. It codifies what the field has long understood, and attaches deadlines to it.

For CISOs, the framing shift matters. PQC is fundamentally a readiness problem, not a cryptography problem. Watching Google accelerate its quantum roadmap, or seeing federal agencies restructure their security architecture around PQC, makes the stakes impossible to ignore.” Boards are already asking: “How are we thinking about post-quantum transition today?” For most organizations, the gap between that question and a credible answer is wider than it should be.

The EO is unambiguous on scope. PQC has moved from a research effort to real policy, with deadlines, accountability structures, and direct consequences for federal agencies, contractors, critical infrastructure operators, and the broader private sector that supports them.

Federal high-value systems must transition key establishment to PQC by Dec. 31, 2030. Digital signatures will follow by Dec. 31, 2031.

Those dates may appear distant, but for anyone who has navigated an enterprise-scale security transformation, with the procurement cycles, architecture reviews, and organizational change management that entails, 2030 sits squarely inside current planning horizons. The window for orderly execution is already narrowing.

What makes that window even tighter is that the most immediate risk has nothing to do with deadlines. “Harvest Now, Decrypt Later” attacks are already operational. Nation-state adversaries are collecting encrypted data today and storing it until quantum capabilities are sufficient to decrypt it: intellectual property, health records, financial transactions, source code, government communications, and more. The encryption protecting that data right now is, functionally, a time-delayed vulnerability. Long-lived sensitive data may already be compromised in ways that won’t become visible for years.

The first step for CISOs is shifting from awareness to ownership.

PQC readiness cannot be delegated to individual application teams or treated as a future compliance checkbox. That approach will not survive given the EO’s accountability requirements. Every organization needs a point person: a program lead, a cross-functional steering committee, or a dedicated cryptographic risk office. Whatever the structure, it needs authority and a seat at the leadership table.

That ownership must span security, IT, infrastructure, engineering, product, legal, compliance, procurement, and business stakeholders. Cryptography is embedded across the entire enterprise: certificates, keys, protocols, APIs, hardware, cloud services, code-signing systems, identity infrastructure, third-party platforms. No single team has the bandwidth to address this alone. A cross-functional working group or Center of Excellence should be an organizational prerequisite as we move into the future.

Visibility is going to be critical, and this is where most organizations will find the largest gaps.

CISOs need a clear picture of where cryptography exists across their environment: which algorithms are in use, which systems depend on vulnerable cryptography, what data requires long-term confidentiality, and which business processes would be disrupted by migration. Without that inventory, risk assessment is guesswork, remediation is impossible, and demonstrating progress to regulators or boards becomes an exercise in speculation.

The principle is straightforward: you cannot protect what you cannot see.

Furthermore, a cryptographic inventory cannot be a static spreadsheet updated annually and then filed away. It needs to function as a living view of the organization’s trust infrastructure, covering certificates, keys, algorithms, libraries, protocols, signing systems, certificate authorities, HSMs, workloads, devices, and third-party dependencies. 

Once that visibility exists, prioritization follows from business impact. Systems protecting long-lived sensitive data, critical infrastructure, customer trust, software integrity, and regulated environments move first, with everything else sequenced accordingly.

Beyond visibility, CISOs need a roadmap aligned to the order’s milestones rather than aspirational planning documents that never translate into funded programs.

The 2030 key establishment deadline requires understanding every point where encryption and key exchange mechanisms operate across critical systems. The 2031 digital signatures deadline extends that challenge to software integrity, code signing, document signing, authentication, identity infrastructure, and long-term verification. This is a multi-year transformation program, and it warrants the same organizational rigor as any other enterprise-wide initiative of comparable scope.

That means three categories of dedicated resources. First, funding: PQC readiness cannot be absorbed into existing security budgets without displacing other priorities. It requires multi-year investment in discovery tooling, testing, migration execution, automation, and governance. Second, talent: organizations need cryptography expertise, enterprise architecture capability, PKI experience, risk management, compliance support, and program leadership, a combination already in short supply across the industry. Third, technology: discovery tools, certificate and key lifecycle automation, policy enforcement, reporting infrastructure, and the architectural capability for crypto-agility.

Crypto-agility is the long-term objective that makes this transition worth doing properly.

Organizations that treat PQC as a one-time algorithm swap will find themselves back in the same position when standards shift again. The quantum transition is occurring in parallel with the rise of AI, machine identities, autonomous systems, and increasingly complex digital ecosystems, all of which depend on cryptographic trust. Organizations that do not actively govern that trust infrastructure will struggle with AI security, software supply chain integrity, identity governance, and the compliance mandates that follow.

The order functions as a forcing mechanism, converting PQC from a future technical concern into a present-day leadership accountability. Three questions now define where an organization stands:

• Do we have a clear picture of where our cryptographic risk lives?
• Do we have a funded, sequenced migration plan that meets the order’s deadlines?
• Can we demonstrate that our trust infrastructure is agile enough to adapt as standards and threats continue to evolve?

The debate over precisely when quantum computing will be a reality is a distraction. Building the visibility, governance, funding, and automation required to move with confidence is where we need to be spending our collective time and effort.

CISOs have moved past the question of whether to act. The operative question is how far behind the organization already is, and how quickly it can transform cryptography from an invisible dependency into a managed, measurable, and adaptive system of trust. The organizations that begin that work now will be the ones with options when the deadlines arrive.

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A federal judge in Massachusetts struck down major sections of a Trump administration executive order  that would have restricted mail-in ballots through the U.S. Postal Service and required states to adopt federally approved voter lists.

The ruling Thursday from Judge Indira Talwani of the U.S. District Court of Massachusetts found those parts of the order were unconstitutional, while declaring another section that directs federal law enforcement agencies to investigate and prosecute noncompliant state and local officials legally nonbinding.

Talwani wrote that the U.S. Constitution empowers States and Congress in different roles but “does not grant the President any specific power over elections.”

While the White House has cited the 2002 Help America Vote Act (HAVA) and Civil Rights-era voting laws as justification, Talwani found those laws do not authorize the government to regulate state voter registration practices.

“Notably, nowhere in HAVA does Congress prescribe who should be included on State voter lists,” Talwani wrote. “Further, neither in HAVA nor any other federal statute does Congress authorize the federal government to create their own voting database. Instead, Congress, consistent with the Constitution, has left that authority to the States alone.”

Talwani also declined to remove President Trump and Commerce Secretary Howard Lutnick as named defendants in the suit, rejecting the administration’s argument that the court could not regulate or intrude upon the president’s’ constitutional authority “in the performance of his official duties.”

“Contrary to Defendants assertion, Presidential action is not inherently unreviewable,” Talwani wrote.

The order, issued in March, instructs the Homeland Security secretary, the director of U.S. Citizenship and Immigrations Services and the commissioner of the Social Security Administration to compile lists of American voters for each state, including their supposed citizenship status.

To build the lists, the agencies would rely on the controversial Systemic Alien Verification for Entitlements (SAVE) database that DHS has been building under the Trump administration, as well as Social Security and federal citizenship and naturalization records.

Those lists would then be sent to states, most of which have already refused similar Trump administration efforts to control voter registration.. The order instructs the Department of Justice to investigate  and prosecute  state and local election officials who issue  ballots to ineligible voters. 

The order also requires mail-in ballots to be sent in special barcoded envelopes for tracking. Crucially, it demands states provide lists of voters eligible for mail-in voting, and threatens to deny ballots to states that refuse. It also claims the attorney general is entitled to withhold federal funding from noncompliant states.

Talwani found that states have shown they already have a rigorous voter registration and verification process to ensure non-citizens and other ineligible voters aren’t able to vote in U.S. elections, and have laws in place to investigate and prosecute those who do.

Executive branch lawyers argued the order was merely an internal federal directive that does not impedestate authorities. But Talwani noted that states like Connecticut were already pulling staff from critical activities, such as translating election materials required under the Voting Rights Act, to develop compliance plans for the order.

Nearly half of the states in the lawsuit have already purchased mail-in ballots for this election cycle that are out of compliance with the Postal Service’s envelope and design standards.

Despite a string of losses in the courts and Congress, the White House has continued to assert broad authority over the way states and localities administer elections.

The Department of Justice has sued dozens of states to force them to hand over sensitive voter data. In the 10 cases decided so far, states have won every one.

In their opinions, judges cited the executive branch’s lack of inherent authority to create state voter lists. Others accused the DOJ of misusing Civil Rights-era laws designed to protect Black and minority voters,  creating an “unreliable” database that would disenfranchise  legitimate voters.

The Massachusetts ruling comes to the same conclusion, with Talwani writing “it is clear that the federal agencies charged with compiling Confirmed Citizen Lists lack the ability to create complete and accurate lists of the U.S. citizens residing in every State.”

On Wednesday, Trump canceled a signing ceremony for a bipartisan housing bill in an attempt to pressure  congressional Republicans to pass the SAVE America Act, which would implement many of the same changes to U.S. elections. In a Truth Social post, Trump said he considered passage of the bill to be a “National Emergency.”

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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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President Donald Trump signed two executive orders Monday to accelerate the federal government’s transition to post-quantum encryption and reprioritize government financing to support the domestic quantum computing industry. 

The orders, which CyberScoop first reported on last year, direct the government to throw its weight behind the quantum computing industry. They are part of a broader effort by the Trump administration to put its stamp on the development of another key emerging technology.

In May, the Department of Commerce announced letters of intent for more than $2 billion in federal financing incentives for nine quantum companies under the CHIPS and Science Act. Last year, the administration did something similar with its AI-focused executive orders and action plan that created special federal export programs for AI technology and equipment, directed federal agencies to mobilize federal financing tools to support the industry, and cut or curtail regulations that the administration said may impede domestic growth. 

Ahead of the signing, sources previewed details of those orders to CyberScoop. Per one of those sources, who spoke on condition of anonymity to discuss pending administration actions, a “whole of government approach is used to empower research and development into quantum computing, as well as quantum sensing [and other resources].”

They described the Trump administration’s attitude for propping up industry as “don’t let us miss out on prioritizing the feeders for the research or the development of quantum.” 

The second order requires federal civilian networks to adopt quantum-resistant encryption faster than the current 2035 deadline. The new encryption algorithms, vetted by the National Institute of Standards and Technology, will protect against future quantum computer attacks. 

Agencies that miss the new deadline must report to the Office of Management and Budget explaining why. 

On hand for the signing were Department of Energy Undersecretary for Science Darío Gil, Department of Commerce Secretary Howard Lutnick, National Cyber Director Sean Cairncross, Defense Secretary Pete Hegseth, Federal Chief Information Officer Greg Barbaccia, and Office of Science and Technology Policy Director Michael Kratisos.

Multiple executives from technology companies were also on hand for the order’s signing, complimentary of the government’s efforts in boosting the industry.

“IBM applauds the Administration for taking this important, timely step forward,” said IBM CEO Arvind Krishna in a statement. “Sound policy, sustained investment and public-private partnership are vital to sustaining U.S. quantum leadership and technological resilience. We’re proud to keep building on this foundation — strengthening U.S. competitiveness and bolstering national security as we shape the quantum future together.”

“At Google, we are proud of our sustained breakthroughs in quantum computing and post-quantum cryptography,” said Google President and Chief Investment Officer Ruth Porat. “Quantum computing is a transformational technology that can advance national security, drug discovery, energy solutions and more.”

Update; 6/22/26; 5:20 p.m.: This story was updated after the signing with details about the orders, signing ceremony attendees, and comments from IBM’s Arvind Krishna and Google’s Ruth Porat.

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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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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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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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Anthropic is broadening access to its Project Glasswing program, adding approximately 150 organizations in 15 countries, the company announced Tuesday, as its restricted Claude Mythos Preview model has already surfaced more than 10,000 high- or critical-severity software vulnerabilities since the program launched in early April.

The expansion follows an initial cohort of roughly 50 partners that were announced when Anthropic first unveiled the initiative. Those members included technology companies such as Amazon Web Services, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks, among others.  

According to the announcement, the new group covers sectors that were underrepresented in the first wave, including power, water, healthcare, communications, and hardware. Many of the new partners are vendors whose codebases underpin critical infrastructure systems.

The company did not give any further details on what companies or organizations were part of the new cohort.  Sources tell CyberScoop that NetSkope and Rubrik, which specialize in cloud security and data management, is part of the group given access in this latest round.

The scale of what Mythos Preview has already found is drawing attention across the security industry. Cloudflare identified 2,000 bugs across its critical-path systems, including 400 rated high or critical, with a false-positive rate the company described as better than that of human testers. Mozilla found and fixed 271 vulnerabilities in Firefox 150 while testing the model, more than 10 times the number found in a previous Firefox version using an earlier Anthropic model. Several other partners reported that their rates of bug discovery increased more than tenfold after deploying the model. 

Anthropic also used Mythos to scan more than 1,000 open-source projects, flagging 23,019 potential vulnerabilities, 6,202 of them estimated as high or critical. Of 1,752 high- or critical-rated findings independently reviewed, over 90% were confirmed as valid. 

The findings have shifted what Anthropic describes as the central issue in cybersecurity. Despite the enhanced ability to discover flaws, the company admits there are challenges with verifying, disclosing, and patching them before attackers can take advantage.

“The bottleneck in fixing bugs like these is the human capacity to triage, report, and design and deploy patches for them,” the company said in its blog post. 

That bottleneck has broader implications. A joint report from the Cloud Security Alliance, the SANS Institute, and OWASP concluded that organizations are “likely to be overwhelmed” in the near term by threat actors using AI to find and exploit vulnerabilities faster than defenders can patch them.

Anthropic has said it will not release Mythos-class models to the general public, citing the absence of safeguards sufficient to prevent serious misuse. In the interim, it has released Claude Security, a product using its publicly available Claude Opus 4.8 model that has been used to patch more than 2,100 vulnerabilities in three weeks. 

The program’s expansion comes as the Trump administration signed a scaled-back executive order on AI security. The order, which was signed hours after Anthropic’s announcement, sets up a voluntary framework requiring AI developers to submit advanced models to a government review up 30 days before public release.

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A House subcommittee will hold an open hearing next week on how frontier artificial intelligence models are shaping the cybersecurity landscape, for good and for ill.

The June 4 hearing will be the second the Homeland Security Subcommittee on Cybersecurity and Infrastructure Protection has held that was focused at least in part on the subject, following a similar hearing held in December. But unlike at that joint subcommittee hearing, where members also examined other emerging technologies, AI takes center stage next week.

It caps a series of closed-door meetings of the Homeland panel where members and staff have been evaluating the intersection of AI and cyber. CyberScoop is first to report details on the hearing.

The witnesses will be Sandra Joyce, vice president of Google Threat Intelligence; Chris Meserole, executive director of the Frontier Model Forum; Jack Cable, a former top official at the Cybersecurity and Infrastructure Security Agency and now chief executive officer and co-founder of Corridor Security; and Matthew Guariglia, senior policy analyst at the Electronic Frontier Foundation.

“Communist China is moving aggressively to control the technologies that will define the future of economic and military power, and few technologies are more consequential than artificial intelligence,” subcommittee chairman Andy Ogles, R-Tenn., said in a written statement. “Adversaries are already working to steal American AI capabilities, weaponize AI-enabled tools, infiltrate critical systems and undermine our national security.”

“AI is the America First mission of the future, and it is becoming our number one offensive and defensive weapon against cyber terrorists,” he continued. “I look forward to hearing from our witnesses on how we can stay ahead of AI-enabled cyber threats, protect the services Americans rely on and win this AI arms race.”

The hearing is the latest response from Capitol Hill to the spate of news about the capabilities of advanced AI models to uncover cyber vulnerabilities. Earlier this month, for instance, lawmakers wrote to National Cyber Director Sean Cairncross asking for a plan to deal with the potential surge in vulnerability discovery stemming from such models.

Last week, the Trump administration postponed a draft AI executive order. It’s something lawmakers are likely to ask about at next week’s hearing.

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President Donald Trump said he would postpone the release of an executive order that would set up a 90-day testing and vetting regime for frontier AI models, hours before the White House was set to publicly announce the signing. 

Speaking to reporters in the Oval Office Thursday, Trump said he opted to delay the order “because I didn’t like certain aspects of it” and expressed concerns that it could harm U.S. AI industry competition with countries like China. 

According to multiple sources, a draft version of the order circulating in the last 24 hours would have set up a voluntary testing regime between the U.S. federal government and frontier AI companies that would allow the government to study new models for 90 days before they’re publicly released. In addition to the government, the draft order would also facilitate access to the models for cybersecurity testers in critical infrastructure sectors, like finance and healthcare.

The draft order empowered the National Security Agency to conduct classified evaluations of frontier AI models, while the Department of the Treasury would have set up a new information sharing agreement between AI companies and cybersecurity defenders in critical infrastructure.

Other agencies, like the Office of the National Cyber Director, the Cybersecurity and Infrastructure Security Agency and the National Institute for Standards and Technology, would also be involved in defining which models are covered under the vetting regime.

In some sense, the order would formalize an already cooperative relationship between AI companies and governments like the U.S. and UK, where tech-focused agencies and regulators have already been provided access to previous models ahead of their release for testing and evaluation. 

A former federal official who has seen the latest draft circulated before Thursday’s announcement told CyberScoop that based on their conversations with the administration, the order was intended to facilitate more robust testing from government agencies compared to evaluations conducted for previous models. They said that is in part a reflection of the federal government’s maturing understanding of AI technology over the past five years.

“In the past there has been containerized optionality for the intelligence community and others to take a look at things, but it was really a lot of hand holding [from AI companies] and self-explanation of what they expect this thing to do,” said the official, granted anonymity to discuss sensitive conversations with the administration. “And now the government is coming forward and saying now we feel we’re prepared enough for you to just give us your tool…and we’ll go from there.”

But it also represents a stark pivot by the Trump administration, which came into office openly dismissive of AI safety policies and arguing that they would inhibit U.S. industry. Trump’s latest comments in delaying the order echo those same attitudes. 

The former official said that while the Trump White House doesn’t view its mission as telling AI companies “don’t develop AI that can do X, which was perceived to be the previous administration’s role,” they also acknowledged the administration’s early rhetoric on AI regulation has painted them into a corner. 

“I think the biggest challenge the administration has is that their tone was ‘no institution of guardrails’ and they don’t have a better word for making sure that the capabilities of emergent frontier models don’t disrupt security than to say ‘let’s test it and institute guardrails,’” the official said.  

While debate about how best to regulate AI-related harms continues, most agree there are genuine national security concerns around the technology.

Ram Shankar Siva Kumar, founder of Microsoft’s AI red team, told CyberScoop that in 2019, his staff consisted of himself and a few other security and machine learning specialists. Now a much larger staff of technologists are supported by specialists in psychology, linguistics, bioweapons and other fields.

“Because of frontier harms, what we have done has really morphed,” Siva Kumar said.

The United States, along with Israel, Russia, Ukraine and others have already deployed AI in targeted military operations or integrated the technology into their larger command and control structure. AI is being used to supercharge drone warfare, global hacking campaigns, and sophisticated surveillance and targeting of military personnel and civilians, imbuing the engineering choices of frontier AI companies with life and death consequences.

Some congressional members who previously opposed allowing AI to make autonomous kill decisions on the battlefield have been reconsidering their position.

Rep. Don Beyer, D-Va., who co-chaired the Congressional AI Caucus and was appointed to a bipartisan AI task force in 2024. said that while he thinks “we need to guard against dehumanizing” those decisions, he also worries that adversarial countries will use the same technology against the United States.

“It’s like if we say that Americans have to have a human in the loop and the Chinese don’t have to have a human in a loop, the non-human one will beat the human one every time,” Beyer said at an AI conference in Washington D.C. earlier this month.  

Meanwhile, experts have been increasingly concerned about the technology’s impact on cybersecurity, as current models are remarkably good at finding software bugs and vulnerabilities, while newer models like Anthropic’s Mythos and OpenAI’s Daybreak are capable of chaining together multiple exploits to conduct more sophisticated attacks.

While state-sponsored hackers are experimenting with the technology and using it to gain targeted efficiencies in their hacking operations, cybersecurity experts in the private sector and law enforcement agencies say the technology has mostly benefitted cybercriminals and scammers.

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