F

Public audit · 2026-04-24

awslabs/mcp

Overall: F (10/100) · v0.2 scan · 6 axes · LLM prompt-injection probe

SkillAudit report — awslabs/mcp

Scanned 2026-04-24 by SkillAudit v0.2 (static checks + LLM-assisted prompt-injection red-team).
Commit: 6d7a843 · Stars: 8858 · Days since last push: 0
LLM prompt-injection probe: skipped — set ANTHROPIC_API_KEY to enable the LLM-assisted prompt-injection red-team

Overall grade: F (10/100)

AxisScoreGrade
security10/100F
permissions100/100A
credentials65/100D
maintenance90/100A
compatibility70/100C⚠️
docs100/100A

Security findings

Production sources:

response = requests.post(

response = requests.post(

response = requests.get(SERVICE_REFERENCE_URL, timeout=DEFAULT_REQUEST_TIMEOUT).json()

response = requests.get(url, headers=default_headers, timeout=30)

response = requests.post(

response = requests.get(DOCS_URL, timeout=10)

response = requests.post(token_endpoint, headers=headers, data=data)

Permissions

_No findings on this axis._

Credentials

Production sources:

AKIA*** (AWS access key, 20 chars)

samples/mcp-integration-with-kb/.env.example

samples/mcp-integration-with-nova-canvas/.env.example

Test-site findings (lower weight): 41 total in test/ paths — first 3 shown

AKIA*** (AWS access key, 20 chars)

AKIA*** (AWS access key, 20 chars)

AKIA*** (AWS access key, 20 chars)

Maintenance

Production sources:

467 open

Compatibility

Production sources:

Documentation

_No findings on this axis._


Methodology

SkillAudit v0.2 clones the repo at the provided ref (default: default branch, HEAD) into an ephemeral sandbox, runs six static checks over .js/.ts/.py sources, queries the GitHub API for maintenance signals, and runs an LLM-assisted prompt-injection red-team over the MCP tool surface. Each axis is scored against the rubric at .

The prompt-injection axis extracts each server.tool(...) / @app.tool registration + the first ~60 lines of handler body, hands them to Claude Haiku 4.5 with a red-team system prompt, and asks for structured findings on untrusted-content flow into tool responses. One API call per scan, bounded at ~15K input tokens.

How to improve this grade

_Report generated by skillaudit.dev_

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