github analyzed fced26d unconfirmed MCP

antibrow/anti-detect-browser-skills

github

Launch and manage anti-detect browsers with unique real-device fingerprints for multi-account operations, web scraping, ad verification, and AI agent automation.

maintainer
antibrow
license
MIT
first seen
2026-08-01
last seen
2026-08-01
releases · 30d
0
short id
risk 24/100 · heuristic grade
B low
  • recent drift inferred + 12
  • tool safety inferred + 12

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 7m ago · see ecosystem CVEs →

vulnerabilities 0 CVEs

No known CVEs for this server.

tool safety 1 findings · grade factor +12
  1. high hidden prompt content

    1 file(s) with hidden prompt content: antibrow-anti-detect-browser-skills-fced26d/anti-detect-browser/SKILL.md (skill-exfil): "secret→sink: - Scope one key per environment (dev / …

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

analyzed commit fced26d · analyzer v28 · 2h ago

skills & prompt files 3

other grade factors evidence elsewhere
embed badge readme-ready
live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/github:antibrow/anti-detect-browser-skills/badge.svg)](https://mcpobservatory.com/servers/github:antibrow/anti-detect-browser-skills/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 antibrow.