github Python analyzed 2104c96

777genius/infinity-context

github

Reliable memory and context infrastructure for AI coding agents: source-backed facts, review-gated learning, MCP/SDK/UI, and replaceable Qdrant/Graphiti retrieval.

maintainer
777genius
license
first seen
2026-07-02
last seen
2026-07-27
releases · 30d
0
short id
risk 67/100 · heuristic grade
D high
  • capability exposure inferred + 35
  • recent drift inferred + 20
  • 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 8m ago · see ecosystem CVEs →

risk trajectory 1 movements
  • C · 59 D · 67
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 +12
  1. high dangerous code

    committed secret: OpenAI key

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

analyzed commit 2104c96 · analyzer v28 · 3d ago

skills & prompt files 10

danger signals20

other grade factors evidence elsewhere
embed badge readme-ready
live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/github:777genius/infinity-context/badge.svg)](https://mcpobservatory.com/servers/github:777genius/infinity-context/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 777genius.