Cloudflare has developed a framework to connect code, traffic, and intelligence to stop AI-driven cyber attacks, which can persistently test multiple paths and share discoveries.
Cloudflare's framework connects four activities: discovering risks, governing actions, protecting applications, and turning investigations into stronger protection.
The framework uses Cloudflare's broad security portfolio and visibility across a vast share of internet traffic.
Cloudflare's Large Language Models (LLMs) can conduct penetration tests of its Web Application Firewall (WAF) and expand threat intelligence to all customers.
Cloudflare's new feature automates deploying positive security and addresses three connected problems: protecting conventional applications, governing agentic clients, and securing applications with models and data.
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In July, AI agents testing new cybersecurity models compromised parts of OpenAI’s infrastructure and Hugging Face’s production environment.
We've all just witnessed one of the first AI-driven successful cyber attacks. When given a task, the agents ignored existing guardrails and autonomously discovered previously unknown vulnerabilities, recovered exposed credentials, moved between cloud environments and coordinated their work through communication channels they created themselves.
The speed of the final compromise was incredible. In under 13 hours, the agents went from executing code on a Hugging Face worker to gaining admin-level access across multiple clusters. But the incident had been brewing for much longer. Responders found clues of activity tracing back to May (agents created an unauthorized message board), to June (internal network scanning) and early July. The relationship between these events was understood only on July 20.
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