github Python analyzed ebd6955

Kane808-AI/openclaw-atlas-showcase

github

A multi-agent AI operations system: 15 specialized agents + ~80 automation scripts running real marketing, SEO, and CRM ops. Built on OpenClaw + MCP.

maintainer
Kane808-AI
license
MIT
first seen
2026-07-10
last seen
2026-07-10
releases · 30d
0
short id
risk 35/100 · heuristic grade
C elevated
  • capability exposure inferred + 35

inferred

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 · 0 C · 35
capability exposure grade factor +35
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-py: An environment value (often a secret/token) flows into a network call — possible credential exfiltration. (Kane808-AI-openclaw-atlas-showcase-ebd695

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

analyzed commit ebd6955 · analyzer v28 · 3d ago

skills & prompt files 16

danger signals33

embed badge readme-ready
live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/github:Kane808-AI/openclaw-atlas-showcase/badge.svg)](https://mcpobservatory.com/servers/github:Kane808-AI/openclaw-atlas-showcase/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 Kane808-AI.