{
  "id": 6173,
  "url": "https://arxiv.org/abs/2604.07551v1",
  "title": "MCP-DPT: A Defense-Placement Taxonomy and Coverage Analysis for Model Context Protocol Security",
  "summary": "The Model Context Protocol (MCP) enables large language models (LLMs) to dynamically discover and invoke third-party tools, significantly expanding agent capabilities while introducing a distinct security landscape. Unlike prompt-only interactions, MCP exposes pre-execution artifacts, shared context, multi-turn workflows, and third-party supply chains to adversarial influence across independently operated components. While recent work has identified MCP-specific attacks and evaluated defenses, e",
  "authors": "Mehrdad Rostamzadeh, Sidhant Narula, Nahom Birhan, Mohammad Ghasemigol, Daniel Takabi",
  "category": "research",
  "topics": "military-security,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-08T19:53:26.000Z",
  "fetched_at": "2026-07-14T16:32:20.053Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6173",
  "original_url": "https://arxiv.org/abs/2604.07551v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}