github Python analyzed · update queued 3f1e844 unconfirmed MCP

Sunwood-ai-labs/OpenFace

github

A local-first, Forgejo-backed AI community hub for models, datasets, Docker Spaces, Skills, MCPs, Prompts, and Pages.

maintainer
Sunwood-ai-labs
license
MIT
first seen
2026-07-17
last seen
2026-08-02
releases · 30d
3
short id
risk 7/100 · heuristic grade
A minimal
  • capability exposure inferred + 10
  • trust mitigators mixed − 3

inferred mixed

The A–E grade is our heuristic synthesis — a "review this" prompt, not a verdict. Each factor is tagged by what backs it: attested (a verifiable record), reported (a third party's claim), or inferred (our own heuristic, e.g. permissions). See methodology.

graded 2m ago · see ecosystem CVEs →

risk trajectory 1 movements
  • A · 10 A · 7
capability exposure grade factor +10
Inferred surface — each links to servers holding it:
vulnerabilities 0 CVEs

No known CVEs for this server.

tool safety 1 findings · grade factor +0
  1. low dangerous code

    env-secret-flows-to-network-js: A process environment value (often a secret/token) flows into a network call — possible credential exfiltration. (Sunwood-ai-labs-OpenFace-3f1e844/f

skills & danger signals github-tarball
prompt-surface shipped agent-instruction files + hidden-content / dangerous-code findings — quoted from the analyzed source

analyzed commit 3f1e844 · analyzer v27 · 1w ago

skills & prompt files 2

embed badge readme-ready
live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/github:Sunwood-ai-labs/OpenFace/badge.svg)](https://mcpobservatory.com/servers/github:Sunwood-ai-labs/OpenFace/security)

Heuristic, inferred signals — false positives (legitimately powerful tools, forks, language ports) are expected. Treat each as "review this", not a verdict. See the ecosystem-wide picture on the security hub, or the fleet security of Sunwood-ai-labs.