{
 "id": "AIR-2026-1398",
 "slug": "llm-attacker-red-team-framework-for-privacy-in-split-llms",
 "title": "LLM-Attacker Red-Team Framework for Privacy in Split LLMs",
 "summary": "Researchers proposed LLM-Attacker, a unified red-team framework designed to evaluate text reconstruction privacy risks in split and distributed language model systems. The tool standardizes message recording and prediction scoring across different architectures.",
 "type": "attack_on_ai",
 "categories": [
  "data_leak"
 ],
 "severity": 1,
 "targets": [
  "enterprise_deployment",
  "framework_or_tooling"
 ],
 "products": [
  "LLM-Attacker"
 ],
 "incident_date": "2026-10-19",
 "incident_date_precision": "day",
 "first_reported": "2026-10-19",
 "sources": [
  {
   "url": "https://arxiv.org/abs/2610.22722",
   "publisher": "arXiv",
   "title": "The LLM-Attacker: A Unified Red-Team Framework for Privacy Evaluation of Split and Distributed LLM Systems",
   "published_at": "2026-10-19"
  }
 ],
 "source_count": 1,
 "confidence": 0.9,
 "status": "published",
 "origin": "news",
 "tags": [
  "split-llm",
  "privacy-evaluation",
  "text-reconstruction",
  "red-teaming"
 ],
 "created_at": "2026-10-19T05:07:38.588Z",
 "updated_at": "2026-10-19T05:07:38.588Z"
}