Last analyzed Sep 9, 2026

Language Model Security Database

Explore primary-source AI security research, evaluated models, attack techniques, and defensive evidence.

985 research findings · 1119 evaluated models

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Confounder Gadgets Reroute LLMs

Published Jan 3, 2025Analyzed Jan 14, 2026Source: arXiv

A vulnerability exists in Large Language Model (LLM) routing systems (control planes) that allows for the manipulation of inference flow via adversarial input sequences. LLM routers, which dynamically direct user queries to either "weak" (cheaper) or "strong" (expensive) models based on predicted query complexity, can be bypassed by appending specific, pre-optimized token sequences known as "confounder gadgets." These gadgets artificially inflate the router's complexity score for an input…

Rerouting llm routers

Evaluated models: Not reported

Research methodology

Entries summarize publicly available primary-source security research. Model names reflect only systems explicitly evaluated by the cited paper, and measurements are research-reported unless independent verification is stated.

Discovery and publication are separate: new papers enter a candidate queue, then require human review and explicit approval before publication. Updates follow that review process, not a guaranteed daily publishing schedule. “Last analyzed” is the newest analysis date among published entries; it does not mean that all recent research has been covered.