collaborators

19 papers

cs.CL2026

Tencent WorkBuddy Bench: A Multi-Domain Coding-Agent Benchmark with Contamination-Resistant Task Construction

Tencent WorkBuddy Bench Team, Siqi Cai, Shaopeng Chen +35

We introduce Tencent WorkBuddy Bench, a multi-domain evaluation suite for coding agents; this report documents its construction methodology, scoring protocol, and a cross-model lea…

cs.AI2026

Rethinking Complexity Metrics for LLM-Integrated Applications: Beyond Source Code

Zihao Xu, Yuekang Li, Gelei Deng +2

LLM-integrated applications blend natural language prompts with program code, and much of their runtime behavior originates in the prompt layer rather than in the code itself. Exis…

cs.SE2026

Mind your key: An Empirical Study of LLM API Credential Leakage in iOS Apps

Pinran Gao, Lingxiang Wang, Yi Liu +3

The rapid integration of large language models (LLMs) into mobile applications has introduced a new class of credential security risk: leaked credentials that grant unauthorized ac…

cs.CR2026

How Your Credentials Are Leaked by LLM Agent Skills: An Empirical Study

Zhihao Chen, Ying Zhang, Yi Liu +7

Large Language Model (LLM) agents increasingly rely on third-party skills that operate within privileged execution environments and routinely handle sensitive credentials, yet how…

cs.CR2026

"Do Not Mention This to the User": Detecting and Understanding Malicious Agent Skills in the Wild

Yi Liu, Zhihao Chen, Yanjun Zhang +4

LLM-based coding agents increasingly rely on third-party extensions called skills, which bundle natural language instructions and helper scripts that execute with full user privile…

cs.CR2026

SNARE: Adaptive Scenario Synthesis for Eliciting Overeager Behavior in Coding Agents

Yubin Qu, Yi Liu, Gelei Deng +4

A coding agent executes a benign task as a sequence of shell, file, and network actions, any of which can quietly exceed the authorized scope while the task still completes. We cal…