open-notebook
Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 16+ AI providers including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral with complete data privacy through self-hosting.
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High
Do not use without reviewing
Security
1 high severity finding. You should review these findings carefully before considering using this skill.
W007: Insecure credential handling detected in skill instructions.
What this means
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
Why it was flagged
The document instructs users (and shows code) to place secrets directly into an exported environment variable and to POST an "api_key" value in JSON (e.g., "sk-..."), which requires embedding secret values verbatim in commands/requests and thus would force an LLM to handle/output secrets directly.
Low
Low-risk findings.
2 low severity findings. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required workflow involves adding “web URL” sources and then “chat/execute” with `include_sources`/`include_notes`, meaning runtime-ingested web-page text authored by outsiders can be fetched and incorporated into the agent’s LLM context (indirect prompt injection risk).
W012: Unverifiable external dependency detected (runtime URL that controls agent).
What this means
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
Why it was flagged
The Quick Start downloads and then runs a remote docker-compose file from https://raw.githubusercontent.com/lfnovo/open-notebook/main/docker-compose.yml (curl ... then docker-compose up -d), which fetches and executes remote container images and therefore is a runtime installation dependency that executes remote code.
- Repository
- K-Dense-AI/scientific-agent-skills
- Commit
757b63b
- Audited
- Security analysis
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