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SecureGARD: Dynamic Ontology-Guided Governance for Secure Tool-Using LLM Agents
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
Researchers introduced SecureGARD, an ontology-guided framework designed to mitigate prompt injection risks in tool-using LLM agents.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 5 November 2026
- Collected by OneBench
- 6 Nov 2026, 02:02 UK
Stored source excerpt
arXiv:2611.06682v1 Announce Type: new Abstract: Tool-using large language model (LLM) agents translate model outputs into consequential actions, turning indirect prompt injection into an execution-security problem.…
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