3 papers
cs.CR2025
CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities
Yuxuan Zhu, Antony Kellermann, Dylan Bowman +13
Large language model (LLM) agents are increasingly capable of autonomously conducting cyberattacks, posing significant threats to existing applications. This growing risk highlight…
cs.MA2025
Teams of LLM Agents can Exploit Zero-Day Vulnerabilities
Yuxuan Zhu, Antony Kellermann, Akul Gupta +4
LLM agents have become increasingly sophisticated, especially in the realm of cybersecurity. Researchers have shown that LLM agents can exploit real-world vulnerabilities when give…
cs.CR2025
Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents
Qiusi Zhan, Richard Fang, Henil Shalin Panchal +1
Large Language Model (LLM) agents exhibit remarkable performance across diverse applications by using external tools to interact with environments. However, integrating external to…