5 papers · 1 filter
Safety in Self-Evolving Agents: A Survey
Jiahao Chen, Zhou Feng, Oubo Ma +28
Large language models (LLMs) exhibit strong general capabilities, yet their parameters typically remain fixed after deployment, limiting learning from new interactions. In open-end…
WeSCE: A Benchmark for Measuring Security Drift in LLM-Driven Code Editing
Zhiyu Zhang, Tingyue Wen, Senke Sun +2
In this work, we introduce WeSCE, a benchmark for quantifying security drift in code editing under weak-security constraints, where tasks specify only functional objectives without…
VIPER-MCP: Detecting and Exploiting Taint-Style Vulnerabilities in Model Context Protocol Servers
Pengyu Sun, Zifeng Kang, Qishu Jin +4
Model Context Protocol (MCP) has emerged as a standard interface for connecting LLM agents to external tools. Because MCP servers expose privileged operations such as shell executi…
DMind-3: A Sovereign Edge--Local--Cloud AI System with Controlled Deliberation and Correction-Based Tuning for Safe, Low-Latency Transaction Execution
Enhao Huang, Frank Li, Tony Lin +1
This paper introduces DMind-3, a sovereign Edge-Local-Cloud intelligence stack designed to secure irreversible financial execution in Web3 environments against adversarial risks an…
DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domain
Enhao Huang, Pengyu Sun, Shuxun Wang +13
The Web3 ecosystem, underpinned by cryptographic primitives and decentralized consensus, represents a high-stakes environment where software vulnerabilities and incentive misalignm…