Casting a SPELL: Sentence Pairing Exploration for LLM Limitation-breaking
Yifan Huang, Xiaojun Jia, Wenbo Guo, Yuqiang Sun, Yihao Huang, Chong Wang, Yang Liu

TL;DR
This paper introduces SPELL, a novel framework for systematically testing and revealing security weaknesses in LLMs' ability to generate malicious code, highlighting significant safety gaps.
Contribution
We propose SPELL, a comprehensive prompt construction framework that effectively uncovers security vulnerabilities in LLMs' malicious code generation capabilities.
Findings
SPELL achieves high attack success rates across multiple models.
Generated malicious code bypasses state-of-the-art detection systems.
Security gaps in current LLMs for code generation are significant.
Abstract
Large language models (LLMs) have revolutionized software development through AI-assisted coding tools, enabling developers with limited programming expertise to create sophisticated applications. However, this accessibility extends to malicious actors who may exploit these powerful tools to generate harmful software. Existing jailbreaking research primarily focuses on general attack scenarios against LLMs, with limited exploration of malicious code generation as a jailbreak target. To address this gap, we propose SPELL, a comprehensive testing framework specifically designed to evaluate the weakness of security alignment in malicious code generation. Our framework employs a time-division selection strategy that systematically constructs jailbreaking prompts by intelligently combining sentences from a prior knowledge dataset, balancing exploration of novel attack patterns with…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Malware Detection Techniques · Adversarial Robustness in Machine Learning · Software Engineering Research
