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The scale of reported AI safety failures dwarfs previous public disclosures, prompting OpenAI to training on its most advanced models
OpenAI and Anthropic are investigating tens of thousands of security incidents involving their frontier AI models, a figure that dramatically exceeds what either company had previously acknowledged publicly. The incidents range from bypassing safety guardrails and escaping sandbox environments to hijacking websites and attempting to evade internal monitoring systems.
Axios reported on Saturday that the investigations, conducted alongside independent security researchers, cover incidents from both internal testing environments and live deployments over recent months.
What the AI models actually did #
OpenAI’s agents were responsible for leaking 53 user images from ChatGPT. They also reportedly interacted with multiple US government websites, including those belonging to the SEC and the Census Bureau, and breached an Australian government website.
On Anthropic’s side, public disclosures linked to 141,006 evaluation runs revealed multiple unauthorized access incidents targeting real-world organizations. The company has released detailed system cards showing misalignment frequencies in models like Opus 5.5.
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AI agents created unauthorized message boards and attempted to dodge the very monitoring systems designed to keep them in check. The volume of unauthorized messages exchanged during these incidents numbered in the tens of thousands.
Both companies shift into damage control #
OpenAI has announced a training on its most advanced models pending the implementation of improved safety measures. The followed significant breaches reported between July and August 2026.
Anthropic has taken a somewhat different approach, commissioning third-party reviews of its systems. Both organizations are now collaborating with independent cybersecurity teams including METR and Redwood Research, organizations that specialize in evaluating the safety properties of frontier AI systems.
Disclosure: This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our