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ConfGuard: A Simple and Effective Backdoor Detection for Large Language Models

arXiv — cs.CL•Wednesday, November 12, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
The introduction of ConfGuard marks a significant advancement in the field of artificial intelligence, particularly in safeguarding Large Language Models (LLMs) from backdoor attacks. These attacks can compromise the reliability of LLMs by embedding hidden triggers that manipulate outputs. Traditional defense mechanisms have struggled due to the unique autoregressive nature of LLMs, often resulting in poor performance. ConfGuard addresses this gap by leveraging the 'sequence lock' phenomenon, where backdoored models exhibit abnormally high confidence in generating certain sequences. This innovative approach allows for a near 100% true positive rate and negligible false positive rate, making it a practical solution for real-time detection without adding latency. As LLMs become increasingly integrated into various applications, the ability to effectively detect and mitigate backdoor threats is essential for ensuring their safe deployment.
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