SECSEC-001 — Model Security Vulnerabilities
LLM Distributed Training Infrastructure Exposed to Network Disruption Attacks
3/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
Large language model training pipelines generate high-volume gradient traffic across GPU clusters, creating exploitable vulnerabilities to pulsating denial-of-service attacks and network congestion. Organisations training frontier models face material operational risk and potential competitive harm from unprotected distributed infrastructure.
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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