INTEL_REPORT
arXiv — Cryptography & Security (cs.CR) · published 6/26/2026, 4:00:00 AM · TLP amber
Summary
Ingested excerpt (first ~500 chars of normalized text).
Verifying Intent and Harm: A Unified Defense Against LLM-Generated Threats arXiv:2606.26377v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in interactive applications, yet they remain vulnerable to adversarial interactions that induce harmful, deceptive, or policy-violating outputs. Existing defenses typically analyze either user prompts or generated outputs, but not both. However, many real-world attacks exploit a separation between ad…
https://arxiv.org/abs/2606.26377
sha256:d7671a7b011580a500579298627d36a6f9dbfa364b9baf120cb3dca21ca1ec9c
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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