VGX: Large-Scale Sample Generation for Boosting Learning-Based Software Vulnerability Analyses. - Yu Nong; Richard Fang; Guangbei Yi; Kunsong Zhao; Xiapu Luo; Feng Chen 001; Haipeng Cai (ICSE, 2024)

Removing RLHF Protections in GPT-4 via Fine-Tuning. - Qiusi Zhan; Richard Fang; Rohan Bindu; Akul Gupta; Tatsunori Hashimoto; Daniel Kang (NAACL (Short Papers), 2024)

LLM Agents can Autonomously Hack Websites. - Richard Fang; Rohan Bindu; Akul Gupta; Qiusi Zhan; Daniel Kang (CoRR, 2024)

LLM Agents can Autonomously Exploit One-day Vulnerabilities. - Richard Fang; Rohan Bindu; Akul Gupta; Daniel Kang (CoRR, 2024)

Teams of LLM Agents can Exploit Zero-Day Vulnerabilities. - Richard Fang; Rohan Bindu; Akul Gupta; Qiusi Zhan; Daniel Kang (CoRR, 2024)

Voice-Enabled AI Agents can Perform Common Scams. - Richard Fang; Dylan Bowman; Daniel Kang (CoRR, 2024)

Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents. - Qiusi Zhan; Richard Fang; Henil Shalin Panchal; Daniel Kang (NAACL (Findings), 2025)

CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities. - Yuxuan Zhu; Antony Kellermann; Dylan Bowman; Philip Li; Akul Gupta; Adarsh Danda; Richard Fang; Conner Jensen; Eric Ihli; Jason Benn; Jet Geronimo; Avi Dhir; et al. (CoRR, 2025)