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Google adds end-to-end Gmail encryption to Android, iOS devices for enterprises | CSO Online

Poisoned truth: The quiet security threat inside enterprise AI Die besten DAST- & SAST-Tools CISA mulls new three-day remediation deadline for critical flaws CISA pushes critical infrastructure operators to prepare to work in isolation CISOs step up to the security workforce challenge 10 Anzeichen für einen schlechten CSO Security agencies draw red lines around agentic AI deployments The fake IT worker problem CISOs can’t ignore How CISOs should utilize data security posture management to inform risk Was ist ein Botnet? Human-centric failures: Why BEC continues to work despite MFA Just 34% of cyber pros plan to stick with their current employer Managing OT risk at scale: Why OT cyber decisions are leadership decisions 4 ways to prepare your SOC for agentic AI ‘Trivial’ exploit can give attackers root access to Linux kernel Bank regulator sounds warning over cybersecurity threat posed by AI models Dismantle implicit trust in OT networks, CISA tells critical infrastructure operators Max-severity RCE flaw found in Google Gemini CLI Stopping the quiet drift toward excessive agency with re-permissioning ODNI to CISOs on threat assessments: You’re on your own 10 wichtige Security-Eigenschaften: So setzen Sie die Kraft Ihres IT-Sicherheitstechnik-Teams frei Researchers unearth industrial sabotage malware that predated Stuxnet by 5 years AWS leans on prior ingenuity to face future AI and quantum threats What it takes to win that CSO role Third Party Risk Management: So vermeiden Sie Compliance-Unheil Critical Cursor bug could turn routine Git into RCE Securing RAG pipelines in enterprise SaaS What CISOs need to get right as identity enters the agentic era Stopping AiTM attacks: The defenses that actually work after authentication succeeds EDR-Software – ein Kaufratgeber Microsoft patched an ‘agent-only’ role that was not AI is reshaping DevSecOps to bring security closer to the code The 'manager of agents': How AI evolves the SOC analyst role 4 Wege aus der Security-Akronymhölle New US House privacy bills raise hard questions about enterprise data collection Scattered Spider co-conspirator pleads guilty Security-KPIs und -KRIs: So messen Sie Cybersicherheit Bitwarden CLI password manager trojanized in supply chain attack 3 practical ways AI threat detection improves enterprise cyber resilience The curious case of Sean Plankey’s derailed CISA nomination Google gets agent-ready for the Mythos age Google drafts AI agents secure systems against AI hackers CNAPP – ein Kaufratgeber Riddled with flaws, serial-to-Ethernet converters endanger critical infrastructure NFC tap-to-pay gets tapped by hackers Anthropic bets on EPSS for the coming bug surge SBOM erklärt: Was ist eine Software Bill of Materials? 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Anthropic Mythos spurs White House to weigh pre-release reviews for high-risk AI models
2026-05-05 · via Google adds end-to-end Gmail encryption to Android, iOS devices for enterprises | CSO Online

The Trump administration is in early discussions about whether advanced AI models should be vetted before public release, according to reporting from the New York Times, the Wall Street Journal, and Axios.

The conversations center on systems capable of facilitating cyberattacks, particularly models that could help users identify and exploit software vulnerabilities. Officials are considering several options, including formal pre-release review processes and government-led testing for higher-risk systems. No proposal has been finalized, and no timeline has been set.

What has changed

The discussions mark a shift in tone, if not yet in policy. On Jan. 20, 2025, Donald Trump’s first day back in office during his second term, he revoked Biden’s Executive Order 14110 on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.

Three days later, he issued his own order, “Removing Barriers to American Leadership in Artificial Intelligence,” signaling a significant shift away from the Biden administration’s emphasis on oversight and risk mitigation toward a framework centered on deregulation and the promotion of AI innovation.

Among the things that order effectively ended: The Biden framework had introduced mandatory red-teaming for high-risk AI models, enhanced cybersecurity protocols, and monitoring requirements for AI used in critical infrastructure. The new discussions suggest certain security risks — particularly those tied to offensive cyber capabilities — warrant a more interventionist posture, even as the administration remains broadly opposed to sweeping AI regulation.

The Mythos factor

The discussion follows Anthropic’s recent introduction of Mythos, a model the company has described as representing a watershed moment for cybersecurity.

Anthropic has said Mythos Preview has found thousands of high-severity vulnerabilities, including some in every major operating system and web browser, and that AI models have reached a level of coding capability where they can surpass all but the most skilled humans at finding and exploiting software vulnerabilities. In one benchmark, the company reported significantly higher success rates compared to earlier models.

Anthropic has not released the model publicly. Instead, it launched Project Glasswing, committing up to $100 million in usage credits to a select group of technology and cybersecurity companies to use Mythos for defensive purposes — finding and patching vulnerabilities before malicious actors can exploit them.

Anthropic has also been briefing the Cybersecurity and Infrastructure Security Agency, the Commerce Department, and other stakeholders on the potential risks and benefits of Mythos Preview. OpenAI has developed a comparable model and has released it to a small set of companies through an existing trusted-access program.

What a review might mean

Pre-release evaluation of AI models is not a new idea, but it remains poorly defined in the US policy context. The Biden executive order Trump revoked had required developers of the largest AI systems to notify the government and share safety test results before deployment — one of several provisions the Trump administration characterized as burdensome obstacles to innovation.

The institutional picture has also shifted. The US AI Safety Institute, created under the Biden order to conduct pre-deployment evaluation and housed within the National Institute of Standards and Technology, was substantially reorganized after Trump took office. In June 2025, the agency was renamed the Center for AI Standards and Innovation, and its mission was revised.

Commerce Secretary Howard Lutnick framed the change as a repudiation of what he called the use of safety as a pretext for censorship and regulation. The renamed center’s mandate now includes leading unclassified evaluations of AI capabilities that may pose risks to national security, with a stated focus on demonstrable risks such as cybersecurity, biosecurity, and chemical weapons, potentially positioning it to play a role in any future review process.

Other governments have moved further and faster. The UK’s AI Security Institute has conducted pre-deployment evaluations of several frontier models, working directly with labs, including Anthropic and OpenAI, to assess risk thresholds before release. The EU AI Act, which began phasing in last year, establishes mandatory conformity assessments for high-risk AI applications.

The US has not established a comparable framework or legal authority to require such reviews.

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