Server-Side Request Forgery (SSRF)Weakness · CWE-918

CVE-2026-7147

HIGH · 7.3 CVSS v3.1 Published 2026-04-27
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
82/100
Remediation priority · High
Remotely reachable No privileges Zero-click

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
A vulnerability was detected in JoeCastrom mcp-chat-studio up to 1.5.0. Affected by this issue is some unknown functionality of the file server/routes/llm.js of the component LLM Models API. Performing a manipulation of the argument req.query.base_url results in server-side request forgery. Remote exploitation of the attack is possible. The exploit is now public and may be used. The project was informed of the problem early through an issue report but has not responded yet.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · high confidence

The mcp-chat-studio application up to v1.5.0 contains an SSRF vulnerability in the LLM Models API (file server/routes/llm.js). The application accepts user-controlled input via the req.query.base_url parameter and uses it to make server-side HTTP requests without proper validation, allowing attackers to induce the server to request arbitrary URLs.

MitigationImplement strict allowlist-based validation for the base_url parameter to restrict requests to approved endpoints, and apply network segmentation to prevent the server from reaching internal services or cloud metadata endpoints.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
None
Scope
Unchanged
Confidentiality
Low
Integrity
Low
Availability
Low

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Identify if mcp-chat-studio is installed
    Locate the application installation directory and look for package.json or check running processes for 'mcp-chat-studio' or 'mcp-chat'
    Affected if The application is present in the environment
  2. Check the installed version
    Inspect package.json, package-lock.json, or run npm list mcp-chat-studio to determine the version number
    Affected if The version is v1.5.0 or earlier (any version up to and including v1.5.0)
  3. Verify the LLM Models API endpoint exists
    Inspect the file server/routes/llm.js in the application directory to confirm the endpoint handles base_url query parameter
    Affected if The file exists and contains code that uses req.query.base_url for HTTP requests
  4. Test if the base_url parameter is accepted
    Send a GET request to the LLM API endpoint with a test base_url parameter, e.g., /api/llm/models?base_url=http://example.com
    Affected if The application accepts and processes the base_url parameter without rejecting or validating it
  5. Confirm network accessibility from the server
    Review outbound firewall rules or network policies to determine if the application server can initiate arbitrary outbound HTTP connections
    Affected if The server has unrestricted outbound network access, allowing potential SSRF to reach internal services or metadata endpoints

You are affected if mcp-chat-studio version v1.5.0 or earlier is running with the LLM Models API exposed and the base_url parameter is accepted without validation.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

From vendor data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Implement strict allowlist-based validation for the base_url parameter to restrict requests to approved endpoints, and apply network segmentation to prevent the server from reaching internal services or cloud metadata endpoints.

Have this fixed Scoped from the published advisory
  • Consultation3.0 h
  • Implementation6.0 h
  • Testing4.0 h
  • Review / QA2.0 h
15.0 hours of engineering $2,640
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2026-7147 in production — separate from our analysis above.

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What this is

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What belongs here
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  • Version or environment caveats, and links to real fixes
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