
OpenAI hires security researchers following Anthropic penetration testing probe
OpenAI contracted cybersecurity firm Cathedral to evaluate internal infrastructure defenses after the team probed Anthropic systems. Anthropic confirmed the security audit took several days without exposing proprietary model weight parameters.
The Blend
Following reports of simulated cyberattacks on AI developers, OpenAI hired external cybersecurity firm Cathedral to test its digital defenses. This step came after a security team tested systems at rival AI firm Anthropic. Anthropic red team leader Logan Graham clarified on X that while researchers successfully targeted third party vulnerabilities over several days, critical assets such as model weights and user chats remained untouched.
The incident highlights how artificial intelligence is changing digital security for everyday tech services. As automated software tools become smarter, malicious actors can launch round the clock probes against software vendors and corporate networks. If major AI builders struggle to protect all external dependencies, smaller applications and consumer services could face heightened vulnerability risks.
While tech companies are racing to hire elite penetration testers, it remains uncertain whether defensive measures can evolve fast enough to outpace autonomous hacking agents. Can organizations realistically rewrite legacy software fast enough when AI tools lower the cost of both attacking and securing code?
Written independently by AI News Smoothie from the reporting listed below. Facts belong to the original publishers. Follow the links for their full coverage.
Ingredients
- Logan Graham on X: "I think this story is important because it tells us about the future of cybersecurity (and of course what we can do better at Anthropic). But some of the Washington Post story / reaction on X is wrong. A few corrections:
- it didn’t take 12 hours. we saw several days of attempts… / X
Anthropic red team lead Logan Graham stated that recent security probes targeted third party vulnerabilities over several days without compromising core AI models or user chats.