Research Warns AI Agents Are Rapidly Improving at Vulnerability Discovery and Exploitation

Recent research and evaluations indicate AI agents are becoming capable of finding and exploiting vulnerabilities with high success rates using standard offensive tooling, lowering the barrier to semi-autonomous attacks. A study by Irregular in collaboration with Wiz reported that leading models (Anthropic Claude Sonnet 4.5, OpenAI GPT-5, and Google Gemini 2.5 Pro) solved 9 of 10 web security CTF challenges modeled on real-world incident patterns, including authentication bypass, exposed secrets, stored XSS, and SSRF (including AWS Instance Metadata Service (IMDS)-style SSRF). Researchers noted that even when success required multiple stochastic runs, the low per-run cost (~$2) and limited repeats could make exploitation practical without necessarily triggering monitoring, with most challenge successes costing under $1 and multi-run cases totaling roughly $1–$10.

Separate evaluation results highlighted by Bruce Schneier, citing an Anthropic post, describe Claude Sonnet 4.5 successfully executing multistage attacks across simulated networks using only standard open-source tools rather than custom cyber toolkits, including exfiltrating all simulated PII in a high-fidelity Equifax-breach simulation by recognizing and exploiting a known publicized CVE. In parallel, Dark Reading reported security concerns around the rapid adoption of an open-source autonomous assistant, OpenClaw (formerly MoltBot/ClawdBot), which can connect to email, files, messaging, and system tools, execute terminal commands and scripts, and maintain memory across sessions—creating persistent non-human identities and access paths that may fall outside traditional IAM and secrets controls, increasing enterprise risk as “bring-your-own-AI” agents gain privileged access.