6 papers
Taming Various Privilege Escalation in LLM-Based Agent Systems: A Mandatory Access Control Framework
Zimo Ji, Daoyuan Wu, Wenyuan Jiang +5
Large Language Model (LLM)-based agent systems are increasingly deployed for complex real-world tasks but remain vulnerable to natural language-based attacks that exploit over-priv…
Taxonomy, Evaluation and Exploitation of IPI-Centric LLM Agent Defense Frameworks
Zimo Ji, Xunguang Wang, Zongjie Li +6
Large Language Model (LLM)-based agents with function-calling capabilities are increasingly deployed, but remain vulnerable to Indirect Prompt Injection (IPI) attacks that hijack t…
CryptoScope: Utilizing Large Language Models for Automated Cryptographic Logic Vulnerability Detection
Zhihao Li, Zimo Ji, Tao Zheng +2
Cryptographic algorithms are fundamental to modern security, yet their implementations frequently harbor subtle logic flaws that are hard to detect. We introduce CryptoScope, a nov…
INTEGRALBENCH: Benchmarking LLMs with Definite Integral Problems
Bintao Tang, Xin Yang, Yuhao Wang +3
We present INTEGRALBENCH, a focused benchmark designed to evaluate Large Language Model (LLM) performance on definite integral problems. INTEGRALBENCH provides both symbolic and nu…
Towards Provable (In)Secure Model Weight Release Schemes
Xin Yang, Bintao Tang, Yuhao Wang +3
Recent secure weight release schemes claim to enable open-source model distribution while protecting model ownership and preventing misuse. However, these approaches lack rigorous…
Measuring and Augmenting Large Language Models for Solving Capture-the-Flag Challenges
Zimo Ji, Daoyuan Wu, Wenyuan Jiang +3
Capture-the-Flag (CTF) competitions are crucial for cybersecurity education and training. As large language models (LLMs) evolve, there is increasing interest in their ability to a…