github Python analyzed e0d1e88

iowarp/clio-agent

github

A science agent supporting any general AI agent in performing data management operations at scale. Builds upon the heritage of the IOWarp platform and proudly represents work done at Gnosis Research Center at Illinois Tech. Supported by NSF.

maintainer
iowarp
license
NOASSERTION
first seen
2026-06-17
last seen
2026-07-29
releases · 30d
18
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 2m ago · see ecosystem CVEs →

risk trajectory 2 movements
  • B · 32 C · 49
  • 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 1 findings · grade factor +5
  1. medium dangerous code

    dynamic exec: __import__(), eval()/exec()

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

analyzed commit e0d1e88 · analyzer v28 · 17h ago

skills & prompt files 6

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:iowarp/clio-agent/badge.svg)](https://mcpobservatory.com/servers/github:iowarp/clio-agent/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 iowarp.