src_fb50be84b835134c75
- Source-provided label
- Not reported
- Evidence class
- mentioned in report
- Confidence
- Not reported
- Observed
- Oct 07, 2026 04:00 UTC
- Retrieved
- Oct 08, 2026 03:43 UTC
Understanding and Enhancing Backdoor Persistency in LLM Agent Post-Training
arXiv:2610.07510v1 Announce Type: new Abstract: Developers can build LLM agents by adapting third-party models through benign post-training. We study a supply-chain threat in which an attacker supplies a model with a backdoor: hidden behavior that produces malicious outputs when a particular input pattern appears. Focusing on software-engineering agents, we ask whether such backdoors survive the d
Reference details
- Source category
- Research & news
- Report title
Understanding and Enhancing Backdoor Persistency in LLM Agent Post-Training- First reported
- Oct 07, 2026 04:00 UTC
- Last reported
- Oct 07, 2026 04:00 UTC
- Catalog updated
- Oct 08, 2026 03:43 UTC
- Record ID
615a64c50beb6c7cd44971abf69609bdb262ee76279de26a6d6e892adc8b13ed
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Source observations
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Feed collection status
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1 sources: 0 stale, 0 needing attention, 0 paused, 1 unverified.
Review source update dates and status
- src_fb50be84b835134c75Collection status unverifiedLast successful batch: Unverified
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