Grammar-constrained decoding enables a new jailbreak (CodeSpear) on LLMs for malicious code, countered by CodeShield which trains models to output harmless honeypot code under GCD while preserving refusals.
Smoke and mirrors: Jailbreaking LLM-based code generation via implicit malicious prompts
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The paper releases a 1,554-prompt consensus-labeled bank separating executable malicious code requests from security knowledge requests, validated by five-model majority labeling with Fleiss' kappa of 0.876.
citing papers explorer
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Grammar-Constrained Decoding Can Jailbreak LLMs into Generating Malicious Code
Grammar-constrained decoding enables a new jailbreak (CodeSpear) on LLMs for malicious code, countered by CodeShield which trains models to output harmless honeypot code under GCD while preserving refusals.
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A Validated Prompt Bank for Malicious Code Generation: Separating Executable Weapons from Security Knowledge in 1,554 Consensus-Labeled Prompts
The paper releases a 1,554-prompt consensus-labeled bank separating executable malicious code requests from security knowledge requests, validated by five-model majority labeling with Fleiss' kappa of 0.876.