activity
20232026
most citedAVA: Inconspicuous Attribute Variation-based Adversarial Attack bypassing DeepFake Detection

1 citations · 1 across the 12 of their papers we have counts for

collaborators

15 papers

cs.CR2026

SceneJail: Exploiting Video Scenario Context to Jailbreak Multimodal LLMs

Wenyu Chen, Li Wang, Chuanchao Zang +5

Video Multimodal Large Language Models (Video-MLLMs) support reasoning over video inputs, yet remain vulnerable to jailbreak attacks that elicit policy-violating responses. Existin…

cs.CR2026

Transferable End-to-End Optimization for Indirect Long-Term Memory Poisoning in LLM Agents

Chuanchao Zang, Jianing Wang, Wenyu Chen +5

Long-term memory can turn untrusted external content into persistent influence over an LLM agent's future decisions, creating the threat of indirect memory poisoning. A successful…

cs.CR2026

Understanding and Exploiting Initialization Anchoring Weakness in Feedback-Based Agent Planning

Chuanchao Zang, Jianing Wang, Wenyu Chen +6

Feedback-based planning improves agent reliability by incorporating tool observations and corrective feedback. However, its protection may not be distributed uniformly across plann…

cs.CR2026

Extracting Knowledge from Tools in LLM Agents

Chuanchao Zang, Jianing Wang, Wenyu Chen +6

LLM agents commonly use knowledge-based tools and access their underlying files, databases, and search indexes through tool invocation. This integration improves agents' ability to…

cs.CR2026

Understanding Stage-Wise Utility-Risk Trade-offs in LLM Agent Memory

Chuanchao Zang, Zijian Cao, Xiangtao Meng +6

Long-term memory is becoming a core capability of LLM agents, enabling personalization and long-horizon interaction. However, memory mechanisms that retain, transform, or expose mo…

cs.CR2026

Isolated but Exposed: Persistence-Based Memory Extraction Attack on LLM Agents

Xinyu Gao, Wenyu Chen, Xiangtao Meng +5

LLM-based agents extend large language models with long-term memory (LTM) that persists privacy-sensitive user data across sessions. Production systems mitigate extraction risks th…

cs.CV2026

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models

Yanting Miao, Yutao Sun, Dexin Wang +8

Visual latent reasoning lets a multimodal large language model (MLLM) create intermediate visual evidence as continuous tokens, avoiding external tools or image generators. However…

cs.CR2026

Defenses at Odds: Measuring and Explaining Defense Conflicts in Large Language Models

Xiangtao Meng, Wenyu Chen, Chuanchao Zang +5

Large language models (LLMs) may require additional defenses after deployment as risks and governance requirements evolve. Subsequent defenses can interact with earlier defenses, r…

cs.CR2026

Not All Tokens Are Created Equal: Query-Efficient Jailbreak Fuzzing for LLMs

Wenyu Chen, Xiangtao Meng, Chuanchao Zang +6

Large Language Models(LLMs) are widely deployed, yet are vulnerable to jailbreak prompts that elicit policy-violating outputs. Although prior studies have uncovered these risks, th…

cs.CR2026

VidLeaks: Membership Inference Attacks Against Text-to-Video Models

Li Wang, Wenyu Chen, Ning Yu +2

The proliferation of powerful Text-to-Video (T2V) models, trained on massive web-scale datasets, raises urgent concerns about copyright and privacy violations. Membership inference…

cs.CR2025

One Risk Down, Another Up: Cross-Risk Interactions Induced by LLM Defenses

Xiangtao Meng, Tianshuo Cong, Li Wang +4

Large Language Models (LLMs) are increasingly deployed in high-stakes settings, where they face diverse risks. Numerous defense strategies have been proposed to mitigate these risk…

cs.CV2025

Beyond the Safety Tax: Mitigating Unsafe Text-to-Image Generation via External Safety Rectification

Xiangtao Meng, Yingkai Dong, Ning Yu +3

Text-to-image (T2I) generative models have achieved remarkable visual fidelity, yet remain vulnerable to generating unsafe content. Existing safety defenses typically intervene int…

cs.CR2025

FaceSwapGuard: Safeguarding Facial Privacy from DeepFake Threats through Identity Obfuscation

Li Wang, Zheng Li, Xuhong Zhang +2

DeepFakes pose a significant threat to our society. One representative DeepFake application is face-swapping, which replaces the identity in a facial image with that of a victim. A…

cs.CR2025

Beyond Known Fakes: Generalized Detection of AI-Generated Images via Post-hoc Distribution Alignment

Li Wang, Wenyu Chen, Xiangtao Meng +2

The rapid proliferation of highly realistic AI-generated images poses serious security threats such as misinformation and identity fraud. Detecting generated images in open-world s…

cs.CV2023★ 1 cited

AVA: Inconspicuous Attribute Variation-based Adversarial Attack bypassing DeepFake Detection

Xiangtao Meng, Li Wang, Shanqing Guo +2

While DeepFake applications are becoming popular in recent years, their abuses pose a serious privacy threat. Unfortunately, most related detection algorithms to mitigate the abuse…