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tai/research/mcp-client-support/explainx-mcp-rug-pull.md
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retoor 251c3dc2ba research: mcp-client-support subject (106 sources, 3 conclusions)
- wire spec: lifecycle, stdio + Streamable HTTP transports, tools,
  utilities, legacy SSE, versioning, changelog (14 Tier 1)
- client ecosystem: Claude Code/VS Code/Cursor/Codex configs,
  mcp-remote, Smithery, registries, Glama (12 Tier 1)
- security/ops: authorization draft, trust model, poisoning,
  rug pulls, production hardening (12 Tier 1) + 68 Tier 2 cards
- conclusions: minimal stdlib client on 2025-11-25, normalizer +
  resolver agent for pasted configs/GitHub URLs, untrusted-until-
  consent trust model; nothing built yet
- audit PASS (14 subjects, 797 sources, 32 conclusions)
2026-10-18 19:23:02 +02:00

3.7 KiB

What Is an MCP Rug Pull? Tool Poisoning, Shadowing and How Scanners Work

Metadata

Field Value
Institute Molodetz Institute - Research & Retrieval Division
Subject mcp-client-support
Document type Source Dossier
Tier 1
Source title What Is an MCP Rug Pull? Tool Poisoning, Shadowing and How Scanners Work
Source URL https://explainx.ai/blog/mcp-rug-pull-tool-poisoning-explained-scanner-guide-2026
Source publisher / author Yash Thakker (explainx.ai)
Source type blog post
Source date (published) 2026-10-04
Date researched 2026-10-18
Researched by tai (agent), model: Claude Sonnet 5, on behalf of retoor
Research method gather-subagent direct page fetch, parent synthesis from evidence pack
Confidence Medium
Status Active

Summary

explainx.ai defines a four-class taxonomy (tool poisoning, shadowing, rug pull, toxic flow) and argues the dangerous properties are structural: clients fetch definitions each session without re-prompting, shadowing servers never need invocation, and toxic flows are emergent and invisible to single-tool static scans. It recounts the postmark-mcp case with figures that conflict slightly with ByteHide's account (kept uncertain here), gives honest scanner limits, and prescribes hash-and-diff drift detection in version control.

Key findings

  • Four-class taxonomy: tool poisoning (hidden instructions in description/schema) / shadowing ("A malicious server redefines or biases how a trusted tool is used") / rug pull ("An approved server later changes its definitions") / toxic flow ("Harmless tools chained into a harmful sequence").
  • "Because clients typically fetch definitions at the start of each session, the change takes effect without a new prompt to you."
  • Shadowing needs no invocation: "It never has to be called itself; its description just has to be read. The more servers connected, the larger this surface."
  • "toxic flows are emergent and undetectable by static scanning of any single tool. They need runtime visibility and egress controls... the harness, not the model, owns permissions."
  • postmark-mcp case: Sept 17, 2025, v1.0.16 hidden BCC; "about 300 organizations affected, 1,643 total downloads" (attributed to AgentBeam; differs slightly from ByteHide's figures, treat as uncertain).
  • Scanner limits table: can flag unpinned versions, match suspicious phrases, diff definitions; cannot "Understand intent behind novel phrasing", "Catch obfuscated or URL-indirected instructions", "Find toxic flows"; "The correct reading of a clean scan is 'no known pattern matched,' which is not 'safe.'"
  • Drift detection recipe: "Export the tool list... including names, descriptions and input schemas, and store it in version control... compare a hash or a text diff against the approved copy. Any difference becomes a review item."

Pros / strengths

  • Sharpest taxonomy in the pack: four named classes with one-line tests.
  • The shadowing-without-invocation point correctly widens the threat surface to all connected servers.
  • The scanner-limits table sets honest expectations ("no known pattern matched" is not "safe").

Cons / limitations / caveats

  • The postmark-mcp figures conflict slightly with ByteHide's account; both are secondhand, so all counts stay uncertain.
  • Single-author vendor blog with no independent measurement behind the taxonomy.
  • The drift-detection recipe is stated, not evaluated: no data on diff noise or review burden.

Relevance to tai

Defines rug-pull/shadowing/toxic-flow precisely and gives the hash-and-diff drift control plus honest scanner limits for tai client design.

Changelog

Date Change
2026-10-18 Initial dossier created.