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20242026
most citedNavigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents

8 citations · 10 across the 27 of their papers we have counts for

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Showing 2026Show all

12 papers · 1 filter

cs.CR2026

FedGraph: Defending Federated Large Language Model Fine-Tuning Against Backdoor Attacks via Graph-Based Aggregation

Xi Chen, Chunyi Zhou, Rui Zeng +3

Federated fine-tuning of large language models (LLMs) allows multiple clients to collaboratively adapt models without sharing raw data, offering strong privacy benefits. However, t…

cs.CR2026

A Finger on the Scale: Covert Policy Steering through Agentic Skills

Jiarui Li, Jiahao Chen, Chunyi Zhou +5

Reusable agent skills extend large language model (LLM) agents with task procedures, tool-use guidance, and output constraints. Yet these skills also act as externalized behavioral…

cs.CR2026

The Shape of Ownership: Verifying LLM Provenance through Semantic Structures

Zhongrui Sun, Jiahao Chen, Oubo Ma +4

As large language models (LLMs) are increasingly redistributed, adapted, and served behind opaque APIs, model ownership can no longer be established reliably by inspecting model in…

cs.CR2026

Lilith: Backdoor Generalization under Training-Inference Trigger Shift

Zhou Feng, Jiahao Chen, Chunyi Zhou +6

Machine-learning services increasingly rely on public data, third-party providers, and outsourced training, creating opportunities for data-poisoning attacks that implant persisten…

cs.CR2026

Flipping Minds by Flipping Bits: Decision-Level Cognitive Hijacking of Large Language Models

Yu Yan, Jiahao Chen, Siqi Lu +6

Large Language Models (LLMs) have been widely applied in high-stakes decision-making scenarios such as corporate strategy, and users are increasingly relying on their outputs. Howe…

cs.CR2026

Safety in Self-Evolving LLM Agent Systems: Threats, Amplification, and Case Studies

Ruixiao Lin, Xinhao Deng, Qingming Li +12

Self-evolving LLM agent systems, which autonomously update their model parameters, memory, tools, and architectures, introduce a qualitatively new threat landscape in which adversa…

cs.CR2026

Understanding and Mitigating Prompt Leaking Attacks in Real-World LLM-Based Applications

Yong Yang, Chong Fu, Tong Zhang +6

Large language model (LLM)-based applications rely on system prompts to encode core logic and developer-defined constraints, making these prompts important intellectual property. H…

cs.CR2026

Customization under Fire: Plugin Poisoning in Text-to-Image Ecosystem

Jiahao Chen, Xing He, Yong Yang +6

The prosperity of text-to-image (T2I) models has fostered a vibrant share-and-play ecosystem centered on Low-Rank Adaptation (LoRA) plugins, which allow users to customize and shar…

cs.CV2026

Order within Chaos: Capturing Intrinsic Energy Anomalies for AI-Manipulated Image Forgery Localization

Yiming Wang, Baiqi Wu, Qingming Li +3

Recent advancements in generative AI have led to image editing models capable of producing realistic forgeries that evade traditional image forgery localization methods, as these a…

cs.CR2026

Profiling for Pennies: Unveiling the Privacy Iceberg of LLM Agents

Jiahao Chen, Qi Zhang, Ruixiao Lin +7

Large Language Models (LLMs) have revolutionized how information are collected, aggregated, and reasoned. However, this enables a novel and accessible vector of privacy intrusion:…

cs.CR2026

IntraGuard: Committee-Side Defenses Against Review Outsourcing to Commercial Chatbots

Oubo Ma, Ruixiao Lin, Jiahao Chen +3

LLMs become increasingly capable, editorial boards and program committees are growing concerned about reviewers who fully outsource peer review to commercial chatbots. This concern…

cs.CR2026

Unveiling the Security Risks of Federated Learning in the Wild: From Research to Practice

Jiahao Chen, Zhiming Zhao, Yuwen Pu +4

Federated learning (FL) has attracted substantial attention in both academia and industry, yet its practical security posture remains poorly understood. In particular, a large body…