6 citations · 11 across the 19 of their papers we have counts for
9 papers · 1 filter
CyberArena: Benchmarking AI Agents in Live Symmetric Attack-and-Defense Combat
Bangya Liu, Jianhong Tu, Yueyang Pan +18
AI agents are demonstrating increasingly strong offensive and defensive cybersecurity capabilities in the real world. Current benchmarks mostly evaluate agents in isolation against…
AgentXploit: Autonomous Repository-to-Runtime Red-Teaming for AI Agents
Weida Liang, Shi Qiu, Zhun Wang +6
AI agents combine language models with external data and tools that can modify files, call APIs, or execute code. Security failures can arise when adversarial content changes an ag…
CyberGym-E2E: Scalable Real-World Benchmark for AI Agents' End-to-End Cybersecurity Capabilities
Tianneng Shi, Robin Rheem, Dongwei Jiang +13
AI has the potential to transform cybersecurity by enabling systems that can autonomously detect, analyze, and remediate software vulnerabilities. However, existing cybersecurity e…
Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens
Peizhi Niu, Wenjie Qu, Shangding Gu +14
Claw-like AI agents (e.g., OpenClaw) are always-on processes with persistent access to credentials, files, tools, and external services. They take on system-level responsibilities…
PromptArmor: Simple yet Effective Prompt Injection Defenses
Tianneng Shi, Kaijie Zhu, Zhun Wang +13
Despite their potential, recent research has demonstrated that LLM agents are vulnerable to prompt injection attacks, where malicious prompts are injected into the agent's input, c…
AgentVigil: Generic Black-Box Red-teaming for Indirect Prompt Injection against LLM Agents
Zhun Wang, Vincent Siu, Zhe Ye +6
The strong planning and reasoning capabilities of Large Language Models (LLMs) have fostered the development of agent-based systems capable of leveraging external tools and interac…
CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale
Zhun Wang, Tianneng Shi, Jingxuan He +3
AI agents have significant potential to reshape cybersecurity, making a thorough assessment of their capabilities critical. However, existing evaluations fall short, because they a…
Progent: Securing AI Agents with Privilege Control
Tianneng Shi, Jingxuan He, Zhun Wang +4
AI agents interact with external environments through tool calls, exposing them to attacks like indirect prompt injection that can trigger unauthorized actions. Securing these agen…
Frontier AI's Impact on the Cybersecurity Landscape
Yujin Potter, Wenbo Guo, Zhun Wang +6
The impact of frontier AI (i.e., AI agents and foundation models) in cybersecurity is rapidly increasing. In this paper, we comprehensively analyze this trend through multiple aspe…