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Defusing Explosive Prompts: Understanding and Preventing Trigger-Based Prompt Injections in LLM Agents
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
Research identifies explosive prompts, a dormant indirect prompt injection technique triggered conditionally in LLM agents.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 22 September 2026
- Collected by OneBench
- 23 Sept 2026, 03:02 UK
Stored source excerpt
arXiv:2609.22510v1 Announce Type: cross Abstract: As LLM applications integrate with external tools, they are increasingly exposed to indirect prompt injection (IPI), where adversarial instructions are…
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The factual summary is a OneBench synthesis, not a quotation or independent verification. Collection time is not publication time. Open the source for its full context; related reporting can share the same underlying announcement.
OneBench interpretation
Institutional assessment
So what
Dormant, trigger-based prompt injections bypass static ingestion filters, complicating security controls for autonomous financial-agent workflows.
Do what
Review agent tool-execution boundaries with the security team to evaluate conditional payload risks.