Academic and industry research shaping the future of AI security, attack, and defence.
Activation steering bypasses prompt-level safety controls by manipulating a model's internal representations at inference time. It requires white-box access, which makes local open-source LLM deployments the primary exposure surface.
Academic research has documented multiple reliable techniques for stripping or spoofing LLM output watermarks. With EU AI Act Article 50 enforcement arriving in August 2026, the gap between compliance theater and actual detection capability is about to matter.
A horizon-scanning paper from 30 international experts identifies four structural problems in agentic AI security that existing frameworks cannot address: distributed accountability, cascading consent failure, degraded human oversight, and certification gaps for non-deterministic systems.
Research published in June 2026 documents a new supply-chain attack class targeting AI coding agent skill ecosystems: VulMask disguises malicious payloads as security vulnerabilities inside skill auxiliary resources, evading automated scanners. A Snyk audit of 3,984 skills found 13.4% carry critical-severity issues.
Johann Rehberger demonstrated a TOCTOU race condition against Claude Computer-Use where swapping the UI during the agent's reasoning window causes it to click the wrong element — in a working demo, the agent sends a malicious email while believing it clicked a harmless Continue button.