SECSEC-001 — Model Security Vulnerabilities
Interpretability Tools Weaponised to Bypass AI Safety Controls
4/5Sector: TechnologyGeography: GlobalStage: OperateIngested: —
Executive Summary
Mechanistic interpretability techniques designed to audit AI models can be repurposed to locate and disable safety-critical neurons or craft targeted adversarial attacks. Boards face regulatory exposure as transparency mandates may inadvertently expand the attack surface of deployed AI systems.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024) ↗https://airisk.mit.edu/
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