activity
20212026
most citedLLM4Fuzz: Guided Fuzzing of Smart Contracts with Large Language Models

8 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CR2026

Semia: Auditing Agent Skills via Constraint-Guided Representation Synthesis

Hongbo Wen, Ying Li, Hanzhi Liu +4

An agent skill is a configuration package that equips an LLM-driven agent with a concrete capability, such as reading email, executing shell commands, or signing blockchain transac…

cs.CR2026

Synthesizing Multi-Agent Harnesses for Vulnerability Discovery

Hanzhi Liu, Chaofan Shou, Xiaonan Liu +4

LLM agents have begun to find real security vulnerabilities that human auditors and automated fuzzers missed for decades, in source-available targets where the analyst can build an…

cs.CR2024★ 8 cited

LLM4Fuzz: Guided Fuzzing of Smart Contracts with Large Language Models

Chaofan Shou, Jing Liu, Doudou Lu +1

As blockchain platforms grow exponentially, millions of lines of smart contract code are being deployed to manage extensive digital assets. However, vulnerabilities in this mission…

cs.CR2023

ItyFuzz: Snapshot-Based Fuzzer for Smart Contract

Chaofan Shou, Shangyin Tan, Koushik Sen

Smart contracts are critical financial instruments, and their security is of utmost importance. However, smart contract programs are difficult to fuzz due to the persistent blockch…

cs.SE2022

Rare-Seed Generation for Fuzzing

Seemanta Saha, Laboni Sarker, Md Shafiuzzaman +4

Starting with a random initial seed, fuzzers search for inputs that trigger bugs or vulnerabilities. However, fuzzers often fail to generate inputs for program paths guarded by res…

cs.CR2021★ 2 cited

CorbFuzz: Checking Browser Security Policies with Fuzzing

Chaofan Shou, Ismet Burak Kadron, Qi Su +1

Browsers use security policies to block malicious behaviors. Cross-Origin Read Blocking (CORB) is a browser security policy for preventing side-channel attacks such as Spectre. We…