OpenAI-compatible audio server in Docker. 7 ASR backends (Whisper, Distil-Whisper, Parakeet, Canary, Canary-Qwen) + 2 TTS engines (Kokoro, Qwen3-TTS voice cloning). Single /v1/audio/{transcriptions,speech,voices} surface. CPU + CUDA images. Hot model swap. MCP server built in.
- capability exposureinferred+35
- recent driftinferred+12
- tool safetyinferred+12
- trust mitigatorsmixed−3
inferredmixed
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 12m ago · see ecosystem CVEs →
- A · 0 → C · 56
no known CVEs for this server.
- highhidden prompt content
1 file(s) with hidden prompt content: psyb0t-docker-talkies-a1b7d2a/.agents/.skills/talkies/SKILL.md (skill-exfil): "secret→sink: ```bash"
analyzed commit a1b7d2a · analyzer v17 · 12h ago
skills & prompt files 1
- ⚠ hidden: skill: skill-exfilpsyb0t-docker-talkies-a1b7d2a/.agents/.skills/talkies/SKILL.md:466
secret→sink: ```bash
- recent drift+12 capability drift →
[](https://mcpobservatory.com/servers/github:psyb0t/docker-talkies/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 psyb0t.