activity
20232026
most citedUnsafer in Many Turns: Benchmarking and Defending Multi-Turn Safety Risks in Tool-Using Agents

1 citations · 2 across the 12 of their papers we have counts for

collaborators

12 papers

cs.AI2026

OpenSage: Self-programming Agent Generation Engine

Hongwei Li, Zhun Wang, Qinrun Dai +11

Agent development kits (ADKs) provide effective platforms and tooling for constructing agents, and their designs are critical to the constructed agents' performance, especially the…

cs.CR2026

TxRay: Agentic Postmortem of Live Blockchain Attacks

Ziyue Wang, Jiangshan Yu, Kaihua Qin +3

Decentralized Finance (DeFi) has turned blockchains into financial infrastructure, allowing anyone to trade, lend, and build protocols without intermediaries, but this openness exp…

cs.CR2026

WebSentinel: Detecting and Localizing Prompt Injection Attacks for Web Agents

Xilong Wang, Yinuo Liu, Zhun Wang +2

Prompt injection attacks manipulate webpage content to cause web agents to execute attacker-specified tasks instead of the user's intended ones. Existing methods for detecting and…

cs.CR2026★ 1 cited

Unsafer in Many Turns: Benchmarking and Defending Multi-Turn Safety Risks in Tool-Using Agents

Xu Li, Simon Yu, Minzhou Pan +5

LLM-based agents are becoming increasingly capable, yet their safety lags behind. This creates a gap between what agents can do and should do. This gap widens as agents engage in m…

cs.CR2026

MalTool: Malicious Tool Attacks on LLM Agents

Yuepeng Hu, Yuqi Jia, Mengyuan Li +2

In a malicious tool attack, an attacker uploads a malicious tool to a distribution platform; once a user inadvertently installs the tool and the LLM agent selects it during task ex…

cs.CL2026

Autonomous Continual Learning for Environment Adaptation of Computer-Use Agents

Tianci Xue, Zeyi Liao, Tianneng Shi +5

Real-world digital environments are highly diverse and dynamic. These characteristics cause agents to frequently encounter unseen environments and distribution shifts, making conti…

cs.CL2026

When Benign Inputs Lead to Severe Harms: Eliciting Unsafe Unintended Behaviors of Computer-Use Agents

Jaylen Jones, Zhehao Zhang, Yuting Ning +6

Although computer-use agents (CUAs) hold significant potential to automate increasingly complex OS workflows, they can demonstrate unsafe unintended behaviors that deviate from exp…

cs.AI2026

Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities

Changdae Oh, Seongheon Park, To Eun Kim +8

Uncertainty quantification (UQ) for large language models (LLMs) is a key building block for safety guardrails of daily LLM applications. Yet, even as LLM agents are increasingly d…

cs.CR2025

Wrangling Entropy: Next-Generation Multi-Factor Key Derivation, Credential Hashing, and Credential Generation Functions

Colin Roberts, Vivek Nair, Dawn Song

The Multi-Factor Key Derivation Function (MFKDF) offered a novel solution to the classic problem of usable client-side key management by incorporating multiple popular authenticati…

cs.CR2025

Decompiling Smart Contracts with a Large Language Model

Isaac David, Liyi Zhou, Dawn Song +2

The widespread lack of broad source code verification on blockchain explorers such as Etherscan, where despite 78,047,845 smart contracts deployed on Ethereum (as of May 26, 2025),…

cs.AI2025

Signal in the Noise: Polysemantic Interference Transfers and Predicts Cross-Model Influence

Bofan Gong, Shiyang Lai, James Evans +1

Polysemanticity is pervasive in language models and remains a major challenge for interpretation and model behavioral control. Leveraging sparse autoencoders (SAEs), we map the pol…

cs.CY2023★ 1 cited

SoK: The Gap Between Data Rights Ideals and Reality

Yujin Potter, Ella Corren, Gonzalo Munilla Garrido +2

As information economies burgeon, they unlock innovation and economic wealth while posing novel threats to civil liberties and altering power dynamics between individuals, companie…