activity
20242026
most citedThe Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs

6 citations · 7 across the 14 of their papers we have counts for

collaborators
Showing cs.CRShow all

5 papers · 1 filter

cs.CR2026

A Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors

Pengxun Li, Litian Zhang, Jianwei Hou +4

Modern AI agent harnesses expose lifecycle hooks that bind shell commands to runtime events such as session start, tool calls, and file edits. These commands run with host privileg…

cs.CR2026

ClawKeeper: Comprehensive Safety Protection for OpenClaw Agents Through Skills, Plugins, and Watchers

Songyang Liu, Chaozhuo Li, Chenxu Wang +8

OpenClaw has rapidly established itself as a leading open-source autonomous agent runtime, offering powerful capabilities including tool integration, local file access, and shell c…

cs.CR2026

From static to adaptive: immune memory-based jailbreak detection for large language models

Jun Leng, Yu Liu, Litian Zhang +3

Large Language Models (LLMs) serve as the backbone of modern AI systems, yet they remain susceptible to adversarial jailbreak attacks. Consequently, robust detection of such malici…

cs.CR2026

Jailbreaking LLMs & VLMs: Mechanisms, Evaluation, and Unified Defense

Zejian Chen, Chaozhuo Li, Chao Li +3

This paper provides a systematic survey of jailbreak attacks and defenses on Large Language Models (LLMs) and Vision-Language Models (VLMs), emphasizing that jailbreak vulnerabilit…

cs.CR2025

MirrorShield: Towards Universal Defense Against Jailbreaks via Entropy-Guided Mirror Crafting

Rui Pu, Chaozhuo Li, Rui Ha +3

Defending large language models (LLMs) against jailbreak attacks is crucial for ensuring their safe deployment. Existing defense strategies typically rely on predefined static crit…