github Python analyzed 996ca6e

Who-Visions/NouGenShards

github

Local-first AI memory for coding agents. NouGenShards stores reusable "shards" in a local SQLite + FTS5 database with outcome-weighted retrieval, so agents recall what worked instead of re-prompting. Your agents have prompts — mine have shards.

maintainer
Who-Visions
licence
NOASSERTION
first seen
2026-06-11
last seen
2026-09-08
releases · 30d
0
short id
risk 64/100 · heuristic grade
D high inferred analyzer v33 (current)
  • capability exposure inferred + 35
  • recent drift inferred + 20
  • tool safety inferred + 12
  • 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.

grade last moved 3d ago · see ecosystem CVEs →

risk trajectory 4 movements
  • C · 56 D · 64
  • C · 44 C · 56
  • B · 32 C · 44
  • A · 0 B · 32
capability exposure grade factor +35
Inferred surface — each links to servers holding it:
vulnerabilities 0 CVEs

No known CVEs for this server.

tool safety 3 findings · grade factor +12
  1. high dangerous code

    committed secret: HuggingFace token, Anthropic key · dynamic exec: __import__ sink, eval()/exec()

  2. medium dangerous code

    env-secret-flows-to-network-py: An environment value reaches a network call. Review whether it is a credential leaving the process; the ordinary API-wrapper shape (read a key, call

  3. medium dangerous code

    env-secret-flows-to-network-js: A process environment value reaches a network call. Review whether it is a credential leaving the process; the ordinary API-wrapper shape (read a ke

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

analyzed commit 996ca6e · analyzer v33 · 1d ago

skills & prompt files 4

danger signals11

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