Autonomous Attack Bots Learn to Exploit New Bugs Without Human Help
Researchers at a leading university published a paper on arXiv showing that autonomous cyber‑attack agents can generalize learned behaviors to unseen vulnerabilities. By combining reinforcement learning with meta‑learning techniques, the agents develop a “conceptual map” of exploit patterns, allowing them to craft payloads for novel software flaws without