INTEL_REPORT
arXiv — Cryptography & Security (cs.CR) · published 6/29/2026, 4:00:00 AM · TLP amber
Summary
Ingested excerpt (first ~500 chars of normalized text).
When the Aggregator Cheats: Data-Free Backdoors in Federated LLM-based QA Systems arXiv:2606.27511v1 Announce Type: new Abstract: Large Language Model (LLM)-based question-answering (QA) systems are increasingly deployed in sensitive domains such as healthcare, mental health counseling, and legal consultation. Federated learning (FL) enables collaborative training without sharing raw client data, for which locally trained models are aggregated at a central server (i.e., a cl…
https://arxiv.org/abs/2606.27511
sha256:fa4bd3664754364e66b0b7455affe49fa7a5ae84ea90a00b572ab051fbde95eb
What we pulled out
Deterministic extractor (IOC + allowlisted tokens + ATT&CK IDs present in DB).
Indicators
Linked with report → mentions → indicator. Values open the indicator workspace.
No indicators linked for this report.
Malware families
Allowlist token matches only.
Threat actors mentioned
Allowlist mentions — not a formal attribution verdict.
ATT&CK techniques
MITRE IDs referenced in text and present in local technique table.
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