{
  "id": 16547,
  "url": "https://arxiv.org/abs/2608.03844v1",
  "title": "MAFIA: Query-Only Memory Attacks via Probing and Factual Injection against Audited LLM Agents",
  "summary": "Memory-augmented LLM agents rely on rich context for long-horizon reasoning and acting, yet their memory modules expose a persistent attack surface for malicious records, making the study of memory poisoning threats imperative. However, existing query-only attacks often fail to remain effective in two realistic and prevalent settings: large-scale benign memory pools and active input auditing. Consequently, current approaches fall short when facing the dual challenges of high retrieval competitiv",
  "authors": "Jiaming Chen, Yisen Gao, Yanping Li, Zifan Liu, Yumeng Zhang, Jun Zhang",
  "category": "research",
  "topics": "agents-autonomy,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-04T15:50:26.000Z",
  "fetched_at": "2026-08-05T05:10:44.550Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/16547",
  "original_url": "https://arxiv.org/abs/2608.03844v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}