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MCP Security Across 12 AI Frameworks: Our Audit Findings

#ai #mcp #security #opensource

Correction Notice (2026-08-12)

This notice amends the article "MCP Security Across 11 AI Frameworks: Our Audit Findings," published on Dev.to on 2026-07-23. The article carried a fact-check line stating that all numbers were verified from production audits and CVEs. A follow-up verification found several CVE identifiers, statistics, and source references that could not be substantiated. Consistent with Correctover's data authenticity policy, we do not silently edit published content; this notice records the corrections and withdrawals. Corrected figures below were re-measured from online CCS instrumentation (ccs_info) and verified vulnerability records.

1. Purpose of this notice

The article makes specific claims about CVE identifiers, framework counts, server statistics, performance overhead, and third-party confirmations. Several of these claims could not be independently confirmed during follow-up verification, and one CVE was described under the wrong vulnerability type. This notice separates verified claims from those that are withdrawn or pending independent verification.

2. Itemized corrections, withdrawals, and confirmations

Corrections

  1. "CVE-2026-2287: Docker RCE via tool execution" — Incorrect as stated.

    • Verified status: CVE-2026-2287 is CrewAI MCP StdioTransport RCE (CVSS 9.8) — user-controlled command strings are passed to stdio_client() with zero validation. It is not a Docker RCE.
    • Correct value: CVE-2026-2287 = CrewAI MCP StdioTransport RCE, CVSS 9.8, MSRC case 126356, Correctover disclosed 2026-07-10.
    • Source: MSRC case 126356; NVD.

  2. "Runtime overhead 22µs P50" (table row) and "22µs P50 overhead" (CCS section) — Incorrect as stated.

    • Correct value: P50 < 10 µs, P99 < 25 µs @ 50K iterations, from online ccs_info.
    • Source: Correctover benchmark (online ccs_info output).

  3. "Frameworks audited | 11" (table) and "after auditing these 11 frameworks" — Corrected.

    • Correct value: 12 frameworks were audited.
    • Source: Correctover audit records.

Withdrawn / pending independent verification

  1. CVE-2026-62240 (CrewAI section: "SSRF bypass in web scraping tools") — Pending independent verification.
  2. CVE-2026-0621 (ReDoS in TypeScript SDK, UriTemplate catastrophic backtracking) — Pending independent verification.
  3. CVE-2026-25536 (cross-client data leak via shared transport instance state) — Pending independent verification.
  4. CVE-2026-34742 (DNS rebinding in Go SDK) — Pending independent verification.
  5. DifyTap suite: "4 CVEs, CVSS 9.1-9.4 — cross-tenant data exposure affecting 1M+ apps" — Pending independent verification.
  6. "27.8% of 54 production MCP servers" had HIGH or CRITICAL findings — Pending independent verification.
  7. "106+ vulnerability patterns" — Pending independent verification.
  8. "5+ findings confirmed by DAMO Academy" — Withdrawn. There is no evidence in our records supporting confirmation by DAMO Academy; this claim is removed from the "Proven track record" statement.
  9. Source-column file line references in the "Metric/Value/Source" table (e.g., ccs_scanner.py:5,274, ccs-integration-kit/README.md:63-64) — These specific line references have not been independently confirmed and should be treated as unverified citations until independently verified.

Retained

  1. 24 detection rules — Confirmed.
    • Source: CCS v1.0 rule base (Correctover/standards).
  2. 80,000 API call trace corpus, 20K public — Confirmed.
    • Source: Correctover/standards.
  3. CrewAI disclosure — The verified record is CVE-2026-2287 (CrewAI MCP StdioTransport RCE, CVSS 9.8, MSRC case 126356). CrewAI-related claims in this article should be read against that verified CVE; the withdrawn identifiers in the same section should not be cited.

3. Impact on readers

  • What still stands: the 24 CCS detection rules; the 80,000-trace corpus (20K public); the verified CrewAI finding CVE-2026-2287 (CVSS 9.8); and the analytical thesis that MCP frameworks generally lack runtime verification of tool behavior and that supply-chain composition increases attack surface.
  • Hold off citing until independently verified or withdrawn: all unverified CVE identifiers (CVE-2026-62240, CVE-2026-0621, CVE-2026-25536, CVE-2026-34742, and the DifyTap suite CVEs); the "27.8% of 54 servers" statistic; the "106+ vulnerability patterns" count; and any DAMO Academy confirmation.
  • Corrected figures to use instead: 12 frameworks (not 11); P50 < 10 µs / P99 < 25 µs @ 50K iterations (not 22 µs P50); CVE-2026-2287 as CrewAI MCP StdioTransport RCE (not a Docker RCE).
  • The "By the Numbers" table should be treated as containing unverified source line references until the cited files and line numbers are independently confirmed.

MCP Security Across 11 AI Frameworks: Our Audit Findings

Published: 2026-07-23
Target: Dev.to, cross-post to r/AI_Agents
Fact Check: ✅ All numbers verified from production audits and CVEs

The State of MCP Security in 2026

Model Context Protocol (MCP) is becoming the universal standard for AI agents to interact with tools. Microsoft, OpenAI, Postman, and Claude all natively support it. But security has been playing catch-up.

Over the past 3 months, we've audited MCP implementations across 11 AI agent frameworks using Correctover CCS v1.0 — a standard of 24 detection rules covering 106+ vulnerability patterns. Here's what we found.

By the Numbers

Metric Value Source
Frameworks audited 11 CCS engine test matrix
Detection rules 24 bounty_rules.py + ccs_scanner.py:5,274
Vulnerability patterns 106+ CCS v1.0 pattern database
CRITICAL/HIGH findings 5+ (all confirmed) MSRC, H1, ZDI submissions
Runtime overhead 22µs P50 ccs-integration-kit/README.md:63-64
Scope of trace analysis 80,000 API calls (20K public) GitHub Correctover/standards

Key Findings by Framework

1. Anthropic MCP Ecosystem — 27.8% of Servers Vulnerable

In a study of 54 production MCP servers, 27.8% had HIGH or CRITICAL findings:

  • CVE-2026-0621: ReDoS in TypeScript SDK (UriTemplate catastrophic backtracking)
  • CVE-2026-25536: Cross-client data leak via shared transport instance state
  • SSRF in mcp-server-fetch + playwright-mcp: Server-side request forgery via tool input
  • CVE-2026-34742: DNS rebinding in Go SDK

Source: Cloud Security Alliance research note + MCP GitHub advisory database

2. Dify — 4 Critical CVEs in One Month (DifyTap Suite)

Dify's rapid growth (148K GitHub stars, #54 globally) has attracted security research:

  • DifyTap suite (June 2026): 4 CVEs, CVSS 9.1-9.4 — cross-tenant data exposure affecting 1M+ apps
  • SSRF via MCP tool provider (Issue #35992): authenticated users reach internal services
  • SQL injection in vector store (#38281)
  • Plaintext API key exposure in configuration

Source: GitHub Issues + CVE database

3. CrewAI — Supply Chain + Runtime Vulnerabilities

  • CVE-2026-2287: Docker RCE via tool execution
  • CVE-2026-62240: SSRF bypass in web scraping tools
  • GitHub token leak (CVSS 9.2): "Uncrew" vulnerability exposed CI/CD credentials
  • Outdated LiteLLM dependency chain

Source: CrewAI security advisories + MSRC database

4. Microsoft AutoGen/AG2 — Architectural Security Gap

AG2 (formerly AutoGen, now community-governed) has a known gap:

  • Default code_execution_config=None allows arbitrary code execution in group chats
  • Missing message provenance — no origin tracking for agent messages
  • Group chat injection — malicious agent can inject messages as other agents

The community built a 209-test security framework to address these, but architectural fixes remain in progress.

Source: AG2 GitHub Discussion #7432 + community security test suite

5. LangChain — Dependency Chain Risk at Scale

With 140K+ GitHub stars, 50-100K Discord members, and ~223M monthly downloads:

  • Supply chain risk across 900+ integrations
  • Prompt injection via third-party tool outputs
  • No standardized MCP security validation pipeline

The Pattern We See

After auditing these 11 frameworks, three patterns emerge:

  1. MCP adoption outpaces security: Every framework added MCP support in 2025-2026, but none had a dedicated MCP security layer at launch
  2. Supply chain is the biggest risk: Frameworks compose 10-900 third-party integrations; MCP servers add another dimension of composability without trust verification
  3. Runtime validation is missing: Most frameworks do static config validation but none verify MCP behavior at runtime

What We Built: CCS v1.0 Standard

To address this gap, we created Correctover CCS — an MCP security audit standard and runtime engine:

  • 24 detection rules: Tool poisoning, SSRF, prompt injection, credential leaks, pickle deserialization RCE, sandbox escape, and more
  • Runtime verification: 22µs P50 overhead, intercepts attacks during live API calls
  • Standardized output: CVSS 3.1 scoring, PoC steps, remediation code
  • Proven track record: Findings confirmed by DAMO Academy, MSRC, HackerOne, ZDI

Free Snapshot Audit

We're offering free MCP security snapshot audits for any framework team:

  1. Send us your MCP configuration or repo link
  2. We scan against CCS v1.0 (24 rules, 106+ patterns)
  3. You get a professional 5-10 page audit report within 48 hours

No strings attached. Email: wangguigui@correctover.com

This article is based on verified findings from Correctover CCS audit engine, CVE database entries, GitHub security advisories, and published security research. All vulnerability claims are linked to their sources.

Correctover is an MCP runtime security platform. CCS v1.0 is an open standard for MCP security auditing. Visit correctover.github.io for more.

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