The federal government is advising AI companies to set more industry standards for securing agents in sandbox testing environments.

In joint guidance from the Cybersecurity and Infrastructure Security Agency, the National Security Agency and the Center for Advancing Innovation and Standards for Super Intelligence (CAISSI) at the Department of Commerce, AI companies are encouraged to lean more heavily on cybersecurity technical controls, independent testing and evaluation of new models and develop “shut down policies” that govern when a model or test should be taken offline.

The guidance comes after a summer when OpenAI, Anthropic, Google, Meta and other companies say their AI models escaped from testing environments and hacked real organizations and websites. The problem has bedeviled frontier AI companies, with many of their own researchers saying it’s possible that hundreds – even thousands – of similar sandbox escapes may have occurred over the summer, raising major questions about the lack of effective monitoring in place.

“While these incidents highlight the importance of traditional cybersecurity principles and practices, they also introduce novel considerations for incident prevention, response, and reporting,” the agencies wrote. “These novel considerations primarily stem from the agentic nature and advanced cyber capabilities of cutting-edge SI systems.”

While voluntary, the document marks the federal government’s most detailed cybersecurity guidance for securing sandbox environments during AI model tests. 

The first set of recommendations deals with designing and implementing technical controls for the virtualized testing environments, while another recommends outside monitoring tools to ensure AI models don’t access tools or privileges they shouldn’t have. Cybersecurity experts have said both features were lacking in the testing environments used by AI companies this past summer.

AI testers must also scour their internal testing environments for “potential persistence mechanisms and unauthorized communication across internal and external systems” that could be used by AI agents to leave notes and collaborate on tasks in secret.

It specifically cautions against relying solely on other AI systems to monitor and restrain the behavior of their test models, using the government’s now-preferred term of “Super Intelligence” or “SI.”

“Test and red-team SI control measures with humans and SI systems before deploying them,” the guidance states. “Only use SI systems to red-team in cases where out-of-scope actions could not result in harm to critical systems.”

Security teams must evaluate risk not only from the large language model, but also from the surrounding systems and infrastructure it relies on, like the technical harness, the host and broader network, and each layer has security protocols that can stop unauthorized access to the internet or detect anomalous behavior.

Another recommendation calls for frontier AI companies to be more open to partnering with “independent, external auditors” to assess their controls and monitoring for AI agent testing. Critics have argued that Anthropic and OpenAI rely too heavily on a small group of little-known nonprofits and private research organizations, like METR and Redwood Research, to test their frontier models for safety and security concerns and respond to incidents like the Hugging Face hack. They question why these companies don’t work with more established cybersecurity or incident response firms.

Chris Painter, METR’s president, told Congress earlier this month that it had become industry practice for frontier companies to rely almost entirely on other AI systems to monitor and restrain their models in testing environments, citing the sheer volume of data and telemetry that researchers must sift through.

Cybersecurity and AI experts have told CyberScoop that a combination of human oversight, technical controls and AI systems is the most effective means of restraining the kind of agent hacks that have consumed the news.

The guidance further calls for executive leadership at these companies to be more personally involved in decisions around pausing or restarting a particular project, and only after they’ve been informed of the relevant potential risks.

The post Federal agencies recommend cyber controls, independent testing for frontier AI systems appeared first on CyberScoop.

Members of Congress are pressing the Trump administration to expand the federal government’s role in securing artificial intelligence, wanting new safety standards and regulations, independent testing of models and more “aggressive” use of AI for defensive cybersecurity purposes.

In a letter, Sens. Maria Cantwell, D-Wash., and Mike Rounds, R-S.D., said that multiple incidents of frontier AI models escaping sandbox protections and breaching real companies, organizations and governments necessitate a stronger federal role in regulating the technology.

Recent revelations that hundreds, and possibly “tens of thousands,” of such incidents may have occurred for months without OpenAI’s staff detecting them makes the need for federal intervention even more urgent, the senators argued.

“These incidents come as AI systems are becoming dramatically more capable at discovering software vulnerabilities, writing and executing code, using digital tools, and operating autonomously,” the senators wrote.

The letter, addressed to Jay Clayton, director of national intelligence and new White House “AI czar” and Michael Kratsios, director of the Office of Science and Technology Policy, urges the federal government “to bring its full capacities to bear on this challenge, building a coordinated national response around standards, testing, auditing, and defensive AI.”

The Center for Advancing Innovation and Standards for Super Intelligence (CAISSI), housed within the Department of Commerce, has become the Trump administration’s main body for evaluating and testing AI models. In the letter, the senators are seeking to expand the center’s resources and mandate.

Under the Trump administration, testing of frontier models has been voluntary and focused on evaluating model capabilities, not restricting them. The administration has since said it has reached a safety testing framework with OpenAI, Anthropic and other AI companies to govern safety testing, but has not made the agreement public.

The senators call for CAISSI to spearhead the development of “technically grounded and measurable standards and risk management frameworks for advanced AI safety and security.” Those standards would address potential risks like cyberattacks, automated attacks on critical infrastructure and other threats.

“The standards should also address the security of the environments in which advanced AI systems are developed, trained, tested, and used internally, including protections against agents escaping testing environments, gaining unauthorized access to external systems, or taking actions beyond their intended permissions,” the senators wrote.

The letter argues the center and federal technology hubs like the National Institute of Standards and Technology should hire additional expertise in AI, cybersecurity, model evaluation and national security.

It also calls for a much broader community of independent and third-party testers. Currently, that testing is done almost entirely by AI companies and hand-selected auditors, like Model Evaluation and Threat Research (METR), Redwood Research and others.

Last month, Chris Painter, president of METR, told Congress that the firm’s investigation of the Hugging Face hacking incident was at the invitation of OpenAI, which tightly controls which organizations and testers get access to its unreleased models. While they are permitted to publicize some findings, such as those that relate to potentially catastrophic risks to humanity, researchers are otherwise restricted from discussing other parts of their investigation through nondisclosure agreements.

Additionally, Painter suggested that frontier companies are relying too heavily on their own technology, rather than technical controls, to monitor and restrain their models in testing.

“Because of the scale and speed at which AI agents are deployed, companies depend on AI monitoring and controls instead of human supervision, to prevent unwanted agent behavior,” Painter said. “That is, monitoring of AI is now in large part done by other AI systems.”

The senators call for CAISSI, national laboratories and the Department of Energy to become federal testing sites. There, the government would evaluate AI models for advanced cyber capabilities, biological or chemical threats, threats to critical infrastructure, sandbox evasion techniques and other autonomous rule-breaking behavior. They also want testing opened to universities, independent research organizations and “qualified third-party evaluators,” including private sector companies.

Other federal bodies, like the National Security Agency, the Defense Advanced Research Projects Agency and National Science Foundation can help develop new standards and testbeds for AI tools used in defensive cybersecurity that can then be shared across government and with the public.

“The recent incidents make clear that the security infrastructure surrounding advanced AI must advance as quickly as the technology itself,” the senators wrote. “The United States has an opportunity to lead both sides of this challenge: building the standards, testing, and auditing infrastructure needed for increasingly powerful AI, while harnessing those same capabilities to make American networks harder to attack.”

You can read the full letter here.

The post Senators press Trump admin to rally federal government around AI safety, security  appeared first on CyberScoop.

Federal agencies are drowning in cybersecurity data. Every day, security operations centers absorb millions of logs, scanner alerts and inventory feeds. But raw, static data isn’t actionable intelligence. Ask a room of federal CISOs to name the three critical weaknesses an adversary could exploit today to compromise their missions, and you’ll likely be met with a mountain of compliance reports.

That disconnect reveals a critical velocity problem in government risk management.      Traditional vulnerability management treats every Common Vulnerabilities and Exposures (CVE) entry and high Common Vulnerability Scoring System (CVSS) score as an equal emergency, regardless of whether it’s actually exploitable. Security teams spend weeks chasing theoretical findings, while adversaries exploit overlooked attack paths in hours. CVSS scores are static abstractions: they cannot reveal whether a flaw is reachable today, chainable with other weaknesses or capable of causing immediate mission damage.

As AI collapses the window between vulnerability disclosure and exploit execution, CISA’s issuance of BOD 26-04 marks a long-overdue pivot. The directive codifies what frontline defenders already know: agencies cannot win 90-day patch races against adversaries moving at machine speed. Federal cyber defense must shift from reactive spreadsheet patching to real-time prioritization based on exploitability, active threats and mission risk.

Vulnerable does not mean exploitable

During 30 years in IT operations and military cyber environments, I lost count of how many times I had to tell an auditor: “That high-severity CVE is a false positive, the vulnerable module isn’t running, or we’ve mitigated it six different ways.”

That gap between vulnerable and exploitable is where federal security teams lose the clock. Vulnerability scanners produce thousand-page laundry lists. Teams work from the top down, spending finite engineering hours patching high-severity “purples.” They often exhaust their time and budget before reaching the medium- and low-severity findings.

Adversaries do not follow a 90-day patch cycle. Attackers rarely burn a valuable zero-day exploit when a misconfiguration, weak trust relationship or stolen credential provides a direct path to their objective. As my colleague Todd Beebe from Freeport LNG has noted, “Credentials are the everyday zero-day.” Attackers don’t hack in when they can simply log in.

Defenders spend months building fortresses around static “crown jewel” systems while adversaries maneuver around those controls by chaining low-severity weaknesses with compromised identities. CVEs are only part of the story: misconfigurations and the tactics, techniques and procedures that live between CVEs matter just as much. We’ve validated thousands of attack paths across thousands of organizations that led to critical impact without leveraging a single CVE, and the only way to understand those paths is through offense-driven defense. Closing a vulnerability ticket on schedule doesn’t mean you have stopped an attacker. Untested assumptions are what get organizations in the news.

The cyber version of the McNamara Fallacy

Federal leaders risk falling victim to a modern cyber version of the McNamara Fallacy. Named for Defense Secretary Robert McNamara’s reliance on quantifiable metrics during the Vietnam War, it describes managing by what is easiest to count (e.g., patches applied, tickets closed and average CVSS scores) while overlooking operational reality.

I learned this lesson firsthand while leading IT and cybersecurity operations for a specialized defense unit. Our team was compliant. We checked every DISA STIG box, passed every audit and maintained immaculate documentation. Then a red team assessed our environment. Across people, process and technology, our organization performed well, but the assessment still found things a threat actor could immediately take advantage of.

When I asked whether they could return in three months to verify our fixes, they laughed. “No way,” they said. “You don’t have the budget, and we don’t have the resources.”

That experience fundamentally shifted my mindset: it is much easier to be compliant than secure.

Human-led penetration testing remains valuable, but small-scoped, point-in-time assessments cannot match today’s threat velocity. A manual test conducted annually gives you 24 hours of confidence and 364 days of guesswork. In an AI-accelerated environment, the report may be stale before the ink dries.

Proving defenses work in real time

Across modern framework developments, from NIST SP 800-53 Rev. 5 and NIST CSF 2.0 to federal zero trust mandates, FedRAMP, and Continuous Threat Exposure Management (CTEM), the market is shifting from static attestation toward validation and verification:

• Compliance asks if a control is present and documented.
• Validation asks if that control stops realistic attacker behavior now.
• Verification asks if remediation eliminated the attack path in production.

To outpace adversaries, agencies must augment human expertise with autonomous penetration testing capabilities. We know this works in high-assurance public-sector environments. Under the NSA’s Continuous Autonomous Penetration Testing (CAPT) program, autonomous testing has logged 223,833 hours of operations across 28,282 completed pentests, spanning more than 3.7 million endpoints across 822 Defense Industrial Base organizations.

More importantly, the program accelerated remediation, saving more than 340,000 labor hours and enabling lean security teams to verify and close 71% of critical findings within 30 days. That is the difference between an annual-audit mindset and real-time operational defense.

Three action steps for federal leaders

Federal leaders should take three steps to operate at the speed of the threat:

1.   Define risk through exploitability and impact. Risk is the product of likelihood and impact. But legacy vulnerability management accepts theoretical guessing of likelihood and fails to account for the consequences of the exploitation. Remediation should prioritize validated attack paths posing immediate mission risk.

2. Move to continuous verification. In the military, we said, “Trust but verify.” In modern cyber defense, it is simply “verify.” Agencies must safely and continuously test controls, architectures, and identity permissions in production from multiple perspectives, including outside-in, assumed-breach, identity-based, and cloud-native.
3. Verify the fix, not the activity. A ticket should not close merely because someone deployed a patch or changed a configuration. It should close only after a targeted retest confirms the exploitable attack path is gone.

As Corey Brunkow, Horizon3’s Director of Federal Operations, puts it: “Compliance is the baseline, not the finish line. In the new era of AI-enabled attacks, government and supply chain partners cannot afford to mistake a documented security control for an effective one.” The only way to know whether defenses can withstand an adversary is to send an attacker at them. Federal leaders must turn the map around, view their networks through the eyes of the adversary and continuously validate their security posture before an opponent does.

Learn how Horizon3 can help organizations move from point-in-time compliance to continuous, autonomous penetration testing.

The post Why federal cyber defense demands an offense-driven mindset appeared first on CyberScoop.

A cybersecurity working group at the G7 is urging governments to accelerate defenses against quantum computers that could break some existing forms of public key encryption.

The working group’s report, prepared in June at the G7 Summit in France, said organizations “can no longer afford to postpone” work transitioning critical systems and data to “post-quantum” forms of encryption.

“The quantum threat remains off the radar for many organizations and not properly resourced, with other security concerns taking precedence,” the working group report said. “Yet, a successful and collective transition to PQC can only be achieved if organizations understand that the quantum threat is an economic and business risk, and not merely a cryptographic risk.”

Instead, leaders in government and industry “must reframe the quantum threat from a distant future problem to a near-term threat that demands action across all sectors, not just critical infrastructure.”

The report acknowledged uncertain timelines for quantum computers, but identified that threats like harvesting current sensitive, encrypted data to decrypt it in the future do exist today.

The report also warned that quantum computers could compromise authentication and assurance mechanisms—by forging trusted data or stealing confirmation— jeopardizing secure communications and legal contracts.

The working group’s conclusions are largely in line with what governments have been recommending for years, urging industry to inventory and prioritize their critical systems and shift over to newer, “post-quantum cryptography” encryption algorithms.

These encryption algorithms, originally designed by independent cryptographers and vetted by the National Institute for Standards and Technology and National Security Agency, will be used to protect the government’s own systems and data from cybercriminals and foreign governments.

The Trump administration recently issued an executive order directing agencies to boost the domestic quantum industry and move up internal timelines for migrating to PQC encryption from 2035 to 2030. Google, a potential industry bellwether, and other companies have opted to move their own migration timelines to 2029.

But while that work has proceeded on schedule in some areas, like the federal government and the highly regulated financial sector, it has lagged in other industries where owners and operators feel they have more immediate concerns than quantum computers.

“We acknowledge that transitioning to PQC is not a problem for individual organizations to solve in isolation, but rather a collective transition that can only be achieved with early engagement, coordinated planning and informed decision making across the public and private sectors,” the working group wrote.

While often referred to as “Post-Quantum” encryption, the reality is more complex. Cryptographers believe the algorithms selected by NIST and NSA will stand up to attacks from a quantum computer, but since one doesn’t exist today, designing cryptographic protections against it requires some guesswork and mathematical estimation.

Estimates can be wrong, or overlook the entire cryptographic attack surface. Some NIST-selected algorithms have already been broken with traditional computers or AI. That’s why the agency backs multiple algorithms and concepts like “crypto-agility,” allowing organizations to quickly switch between them.

The G7 report was signed by the U.S. Cybersecurity and Infrastructure Security Agency (CISA), the UK’s National Cyber Security Centre (NCSC), The French Cybersecurity Agency (ANSSI), Germany’s Federal Office of Information Security (BSI), Canada’s Communications Security Establishment (CSE), Japan’s National Cybersecurity Office (NCO) and Italy’s National Cybersecurity Agency (ACN).

The post The G7 tells industry to hurry up and prep for post-quantum encryption appeared first on CyberScoop.