{
  "id": 18689,
  "url": "https://arxiv.org/abs/2608.10530v1",
  "title": "On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models",
  "summary": "Large Language Models (LLMs) have undergone a shift from stateless conversational interfaces to autonomous agents capable of multi-step planning, tool invocation, code execution, and maintaining persistent memory. When these agents operate with real-world privileges---calling APIs, modifying files, and querying databases---a compromised reasoning step can trigger unauthorized data access, irreversible state changes, or cascading failures, yet the security research community has not kept pace. To",
  "authors": "Md Jafrin Hossain, Mohammad Arif Hossain, Nirwan Ansari",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-11T06:11:26.000Z",
  "fetched_at": "2026-08-12T05:10:43.828Z",
  "source_slug": "x-arxiv-red-teaming-query",
  "source_name": "arXiv red teaming query",
  "source_homepage": "https://arxiv.org/a/redteam",
  "ethics_ai_record_url": "https://ethics.ai/record/18689",
  "original_url": "https://arxiv.org/abs/2608.10530v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}