Agentic data science with the Data Agent Kit
cloud.google.com·6h ago
AI Research
arXiv CS.AI·Sep 3·5 min read
Agent Tools Orchestration Leaks More: Dataset, Benchmark, and Mitigation
TL;DR
A new benchmark, TOP-Bench, was developed to evaluate the Tools Orchestration Privacy Risk (TOP-R) in LLM agents, revealing significant leakage of sensitive information. The proposed TOP-Align method enhances safety in task completion, outperforming traditional prompt-only safeguards.
✦ Why It Matters
Implement TOP-Align to enhance privacy safeguards in your LLM applications today.
Key Takeaways
- Evaluate LLM agents using the new TOP-Bench benchmark.
- Adopt TOP-Align for improved task completion safety.
- Monitor leakage rates in LLM outputs to mitigate risks.
- Consider multi-layered defenses beyond prompt-based methods.
How It Works
The Library-Grounded Reverse-Inference Seed Expansion (LRSE) method constructs a reverse-construction pipeline using four libraries to analyze tool outputs. This approach helps identify sensitive conclusions that may arise from combining non-revealing outputs, thereby formalizing the TOP-R risk.