SpecGuard: Inference-Time Backdoor Detection For Free

TL;DR - SpecGuard detects backdoor-triggered LLM behavior by reusing token-acceptance signals already produced during speculative decoding, adding no model-computation overhead. This enables always-on runtime monitoring without assumptions about trigger structure or extra generation passes.

• Backdoor activation creates a prediction mismatch between a clean draft model and the compromised target model, changing draft-token acceptance rates.
• The authors formalize this signal and argue that attackers cannot suppress it without weakening the backdoor.
• SpecGuard reportedly works across multiple backdoor types and model families, including stealthy attacks missed by input-level filters.
• The approach repurposes an existing inference optimization rather than adding separate detection computation.