Aug 2026· International Conference on Automated Software Engineering· Vol 33· 0 citations· 34 references
TL;DR
The proposed SymDict, a hybrid fuzzing system based on symbolic dictionaries, reduces redundant symbolic execution by performing constraint solving only at uncovered branches in frontier basic blocks, and partitions constraint sets into solvable subsets, combines solutions with offset information to create symbolic dictionaries, and uses these dictionaries to guide fuzzing mutations.
Hybrid kernel fuzzing combines kernel fuzzing and symbolic execution: symbolic execution resolves hard-to-reach branch conditions, while kernel fuzzing mitigates path explosion. This collaboration has shown strong potential for uncovering deep kernel vulnerabilities. However, existing approaches have not fully accounte...
Lu Xu, Baosheng Wang, Bo Yu et al.· IEEE Transactions on Informa...· 0 citations
Code obfuscation is a fundamental technique for software protection and intellectual property defense, yet its effectiveness has been increasingly undermined by advances in symbolic execution and automated deobfuscation. Existing countermeasures based on path explosion, path divergence, or complex constraints suffer...
Mo-Xuan Wang, Hai-Yan Hu, Hao-Hang Qin et al.· Journal of computing and sec...· 0 citations
Prototype pollution is a critical class of taint-style vulnerabilities in JavaScript programs, enabling attackers to tamper with object prototypes and thereby alter program behavior in unexpected and often dangerous ways. Despite its severity, existing detection techniques struggle with excessive false positives and po...
De-Zhen Kong, Pei-Sen Yao, Jia-Kun Liu et al.· ACM Transactions on Software...· 0 citations
Fuzzing finds bugs by testing software behavior with high volumes of input. To create semantically valid inputs for different targets, traditional fuzzers require significant engineering effort. LLM-based fuzzing approaches can be adapted to create inputs for a wide range of software but introduce new issues: every tes...
We present repair-driven greybox fuzzing, a new approach to greybox fuzzing that combines the strengths of unstructured, byte-level input mutation and grammar-guided input generation. By increasing input diversity while preserving input validity, repair-driven fuzzing promises to improve bug-finding ability for systems...
Bachir Bendrissou, Alastair F. Donaldson, Cristian Cadar· 0 citations
SyzHarness is a framework that combines LLM reasoning with coverage-guided fuzzing for patch-based Linux kernel vulnerability reproduction and achieves a 73% bug reproduction success rate, substantially outperforming prior directed greybox fuzzing.
Xing-Yu Li, Jue-Fei Pu, Hao-Nan Li et al.· 0 citations
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