Fuzzing is a highly effective automated testing method for uncovering software vulnerabilities. Despite advances in fuzzing techniques, many fuzzers still struggle with coverage plateaus caused by fuzz blockers, which limit their ability to discover deeper vulnerabilities. We introduce InsightQL, the first human-assist...
Wen-Tao Gao, Renata Borovica-Gajic, Sang Kil Cha et al.· Proceedings of the 41st IEEE...· 0 citations
This work presents XAgent, an execution-guided agentic framework that analyzes dynamic behavior and additional program context to localize and validate issues, opening new opportunities for LLM-based coding agents to achieve more robust and generalizable software maintenance.
H. Huynh, Patanamon Thongtanunam, Michael Fu et al.· 0 citations
The ablation study confirms that the three context facets are mutually complementary, and that multi-agent scaffolding and base-model capacity each play an essential role for agentic vulnerability repair.
Michael Fu, Qiyue Mei, Patanamon Thongtanunam et al.· arXiv.org· 1 citation
SkillGate, a deployable security gateway that screens AI skill packages before coding agent installation is presented, and four research questions covering detection effectiveness, screening cost, runtime overhead, and false positive behavior on the SkillsBench benchmark against two existing tools are answered.
Rui Yang, Michael Fu, C. Tantithamthavorn et al.· arXiv.org· 1 citation
An adversarial skill-synthesis method using six LLMs across four families to transform 471 real-world shell commands into benign-appearing skills, released as a benchmark of 2,826 skills mapped to 11 MITRE ATT&CK tactics.
Rui Yang, Michael Fu, Kla Tantithamthavorn et al.· 0 citations
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