GenAI OpenTelemetry Auto-Instrumentation Library A comprehensive wrapper for automatic instrumentation of LLM/GenAI applications Supports all major LLM providers and MCP (Model Context Protocol) tool calls
- capability exposure inferred + 35
- tool safety inferred + 5
- trust mitigators mixed − 8
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 3m ago · see ecosystem CVEs →
- C · 52 → B · 32
- C · 44 → C · 52
- B · 27 → C · 44
- A · 0 → B · 27
No known CVEs for this server.
- medium dangerous code
dynamic exec: eval()/exec(), __import__()
analyzed commit 7107a91 · analyzer v30 · 2d ago
danger signals2
- dynamic code execution eval()/exec() Mandark-droid-genai_otel_instrument-7107a91/examples/dspy_example.py :172
result = eval(expression) # nosec B307 - Example code only - dynamic code execution __import__() Mandark-droid-genai_otel_instrument-7107a91/scripts/debug/simple_test.py :132
module = __import__(parts[0])
[](https://mcpobservatory.com/servers/github:Mandark-droid/genai_otel_instrument/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 Mandark-droid.