SECSEC-001 — Model Security Vulnerabilities
Deep Learning Framework Vulnerabilities Expose LLM Infrastructure
4/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
Large language models inherit critical security flaws in their underlying frameworks, including buffer overflow, memory corruption, and input validation failures. Boards face regulatory and operational exposure where AI systems rest on software infrastructure with known, unmitigated vulnerabilities.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024) ↗https://airisk.mit.edu/
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