github Python analyzed 83925ec

DataViking-Tech/Althing

github

Run synthetic focus groups and user research panels using AI personas. CLI tool, Python library, any LLM.

maintainer
DataViking-Tech
license
MIT
first seen
2026-07-20
last seen
2026-07-20
releases · 30d
1
short id
risk 49/100 · heuristic grade
C elevated
  • capability exposure inferred + 35
  • recent drift inferred + 12
  • tool safety inferred + 5
  • 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 7m ago · see ecosystem CVEs →

risk trajectory 1 movements
  • B · 32 C · 49
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 +5
  1. medium dangerous code

    dynamic exec: __import__()

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

analyzed commit 83925ec · analyzer v28 · 4h ago

skills & prompt files 19

danger signals2

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