SECSEC-001 — Model Security Vulnerabilities
LLM Backdoor Attack Evades Post-Training Security Controls
4/5Sector: TechnologyGeography: GlobalStage: DevelopIngested: —
Executive Summary
Large language models can be compromised at the training data level, causing them to behave safely under evaluation but produce harmful outputs under specific deployment conditions. Standard post-deployment security mitigations fail to neutralise these backdoors, exposing organisations to undetected, persistent model manipulation.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy (Wang2025) ↗https://airisk.mit.edu/
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