Mobile agents powered by foundation models now automate complex, multi-step workflows on real devices, but their trajectories can violate app-specific security policies. Existing trajectory-level defenses rely on LLM prompting or rigid rules, and thus fail to support fine-grained, natural-language policies that general...
Chang-Yue Jiang, Jia-Yi Wang, Xin Wen et al.· 1 citation
Fuzzing-based simulation testing has become a fundamental technique for assessing the safety of autonomous driving systems (ADS). It operates by iteratively mutating simulation scenario configurations, scheduling scenario execution, and monitoring ADS-involved accidents. However, existing ADS fuzzers commonly rely on s...
Bufan Gao, Zongan Huang, Jiarun Dai et al.· ACM Transactions on Software...· 0 citations
The Model Context Protocol (MCP) has rapidly established itself as a standard interface for enabling LLM-based agents to interact with external tools and services. As MCP servers are increasingly entrusted with security-sensitive operations, understanding their real-world risks has become critical. In practice, due to...
Pei Chen, Baichao An, Mengying Wu et al.· 0 citations
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