AgentXploit divides auditing between two roles.
Two-stage auditing finds more exploitable flaws in AI agent repositories
AgentXploit separates source-code attack-path discovery from runtime exploitation, outperforming comparison systems on two security benchmarks.
Top University
Weida Liang · Shi Qiu · Zhun Wang · Simon Sure · Xiaoyuan Liu · Tianneng Shi · +3 more
National University of Singapore · University of North Carolina at Chapel Hill · University of California, Berkeley · University of Chicago · University of California, Santa Barbara
Research Digest··2 min read
Thread:Agent Security & Attacks
The authors built an automated white-box auditing system that analyzes an AI agent's repository for attacker-controlled paths to sensitive operations, then tests concrete exploits in a controlled runtime.
Why this paper
From National University of Singapore and 4 others · Released code · Part of Agent Security & Attacks, now 32 papers
In one line
AgentXploit separates repository attack-path discovery from runtime exploitation, achieving 59.3% end-to-end success on 72 vulnerabilities.
What it released
Code
What we could check
- ✓Code link in the paper (github.com)
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ✓Limitations stated by the authors
- ✓Reports numbers on named benchmarks (2 benchmarks)
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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