pypi Python analyzed 0.5.2

milu

v0.5.2
pypi

Unified AI agent framework: one interface for 9 LLM providers (Qwen, Kimi, GLM, DeepSeek, MiniMax, Doubao, ChatGPT, Gemini, Claude) with tools, MCP, sub-agents, skills, RAG knowledge base, scheduler, multi-channel IM gateway (WeChat/Feishu/Telegram) and multi-user serving

maintainer
stephon
license
first seen
2026-08-14
last seen
2026-08-14
releases · 30d
1
short id
risk 37/100 · heuristic grade
C elevated
  • capability exposure inferred + 35
  • 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 42s ago · see ecosystem CVEs →

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: eval()/exec()

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

analyzed v0.5.2 · analyzer v32 · 1h ago

skills & prompt files 10

  • agent-rules milu-0.5.2/src/milu/templates/prompts/coder/agent.md
  • agent-rules milu-0.5.2/src/milu/templates/prompts/main/agent.md
  • agent-rules milu-0.5.2/src/milu/templates/prompts/reader/agent.md
  • agent-rules milu-0.5.2/src/milu/templates/prompts/researcher/agent.md
  • agent-rules milu-0.5.2/src/milu/templates/prompts/reviewer/agent.md
  • skill milu-0.5.2/src/milu/templates/skills/frontend-design/SKILL.md
  • skill milu-0.5.2/src/milu/templates/skills/internal-comms/SKILL.md
  • skill milu-0.5.2/src/milu/templates/skills/mcp-builder/SKILL.md
  • skill milu-0.5.2/src/milu/templates/skills/systematic-debugging/SKILL.md
  • skill milu-0.5.2/src/milu/templates/skills/test-driven-development/SKILL.md

danger signals5

  • dynamic code execution eval()/exec() milu-0.5.2/examples/2. agent_basic.py :28 return str(eval(expression)) # noqa: S307
  • dynamic code execution eval()/exec() milu-0.5.2/src/milu/sandbox/local.py :63 exec(code, restricted_globals) # noqa: S102
  • dynamic code execution eval()/exec() milu-0.5.2/tests/test_agent_integration.py :32 result = eval(expression, {"__builtins__": {}}, {})
  • dynamic code execution eval()/exec() milu-0.5.2/tests/test_real_new_providers.py :118 return str(eval(expression))
  • suspicious endpoint api.telegram.org milu-0.5.2/src/milu/channels/telegram.py :40 api_base: str = "https://api.telegram.org"
embed badge readme-ready
live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/pypi:milu/badge.svg)](https://mcpobservatory.com/servers/pypi:milu/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 stephon.