metadata
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- safety
- tool-use
- guardrail
- agents
TS-Guard
TS-Guard is a guardrail model for step-level tool invocation safety detection, introduced in the paper ToolSafe: Enhancing Tool Invocation Safety of LLM-based agents via Proactive Step-level Guardrail and Feedback.
TS-Guard is trained via reinforcement learning with a multi-task reward scheme tailored for agent security, enabling identifying harmful user requests and attack vectors in agent-environment interaction logs, detecting unsafe tool invocation before execution, and providing interpretable analysis and reasoning process.
Resources
- Paper: ToolSafe: Enhancing Tool Invocation Safety of LLM-based agents via Proactive Step-level Guardrail and Feedback
- Repository: GitHub - MurrayTom/ToolSafe
Citation
If you find our work helpful, please consider citing it:
@article{mou2026toolsafe,
title={ToolSafe: Enhancing Tool Invocation Safety of LLM-based agents via Proactive Step-level Guardrail and Feedback},
author={Mou, Yutao and Xue, Zhangchi and Li, Lijun and Liu, Peiyang and Zhang, Shikun and Ye, Wei and Shao, Jing},
journal={arXiv preprint arXiv:2601.10156},
year={2026}
}