INTEL_REPORT
arXiv — Cryptography & Security (cs.CR) · published 6/9/2026, 4:00:00 AM · TLP amber
Summary
Ingested excerpt (first ~500 chars of normalized text).
Hallucination Cascade: Analyzing Error Propagation in Multi-Agent LLM Systems arXiv:2606.07937v1 Announce Type: new Abstract: Large Language Models (LLMs) generate fluent text but remain vulnerable to hallucinations, producing unsupported, inconsistent, and factually incorrect claims. Most prior work treats hallucination as a static property of isolated outputs. In multi-agent LLM systems, however, responses are exchanged across agents, revised through sequential stages, and…
https://arxiv.org/abs/2606.07937
sha256:f3edc428d226dc05d4bd74708c8f90cecacf53a802f991cb2d01f4e09fc29299
What we pulled out
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Indicators
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Malware families
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Threat actors mentioned
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ATT&CK techniques
MITRE IDs referenced in text and present in local technique table.
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