aiqbench analysis
Cloudflare has successfully deployed frontier AI models within a controlled harness to autonomously probe its Web Application Firewall (WAF) for vulnerabilities. By treating blocked attacks as starting points, the system iteratively mutated payloads to refine new attack vectors without direct access to internal security logic. This approach yielded 49 actionable findings that directly informed updates to Cloudflare's Managed Rulesets, demonstrating a practical application of AI in defensive cybersecurity operations.
Cloudflare Uses an AI Harness to Probe and Harden its WAF
Cloudflare placed frontier AI models inside a controlled testing harness to probe its Web Application Firewall (WAF), using blocked attacks as starting points for models to generate and refine new variations. By Matt Foster
Cloudflare placed frontier AI models inside a controlled testing harness to probe its Web Application Firewall (WAF), using blocked attacks as starting points for models to generate and refine new variations. Across 45 scenarios, the system generated 1,107 attempts and left 49 findings after human triage. The exercise ultimately contributed to…
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