agent-brain-rag

v10.2.1 safe
4.0
Medium Risk

Agent Brain RAG - Intelligent document indexing and semantic search server that gives AI agents long-term memory

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all categories, with no clear signs of malicious intent. The shell command usage could warrant closer monitoring, but the overall evidence does not suggest a supply-chain attack.

  • Low risk in network calls, obfuscation, and credential handling.
  • Potential benign use of shell commands, likely for version control.
Per-check LLM notes
  • Network: The network call appears to be a health check, which is common and generally benign.
  • Shell: Executing shell commands could be legitimate if the package is intended to interact with version control systems like git, but it also introduces a risk of unintended execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package contains non-secure links which may indicate local testing rather than malicious intent. The maintainer has only one package, suggesting a new or less active account.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • try: req = urllib.request.Request(f"{state.base_url}/health/", method="GET")
  • ethod="GET") with urllib.request.urlopen(req, timeout=3) as resp: return bool
  • e: self._client = httpx.AsyncClient( base_url=self._base_url, ti
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • """ try: result = subprocess.run( ["git", "rev-parse", "--show-toplevel"],
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

⚠ Suspicious Page Links score 6.0

Found 3 suspicious link(s) on the package page

  • Non-HTTPS external link: http://127.0.0.1:8000/docs
  • Non-HTTPS external link: http://127.0.0.1:8000/redoc
  • Non-HTTPS external link: http://127.0.0.1:8000/openapi.json
✓ Git Repository History

Repository SpillwaveSolutions/agent-brain appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Spillwave Solutions" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agent-brain-rag 
Create a knowledge management system called 'DocMind' using the Python package 'agent-brain-rag'. This system will serve as a personal or team knowledge base, allowing users to upload documents, create notes, and perform advanced semantic searches. Here’s a detailed breakdown of the steps and features:

1. **Setup Environment**: Ensure you have Python installed and set up a virtual environment. Install 'agent-brain-rag' and any other necessary packages.
2. **User Interface**: Develop a simple web interface where users can log in and manage their documents and notes. Consider using Flask or Django for the backend and Bootstrap for styling.
3. **Document Upload**: Allow users to upload various types of documents (PDFs, Word docs, etc.). Use 'agent-brain-rag' to index these documents for semantic search capabilities.
4. **Note Creation**: Enable users to create notes directly within the application. These notes should also be indexed by 'agent-brain-rag' for seamless integration with document searches.
5. **Semantic Search**: Implement a search feature that allows users to query the indexed documents and notes using natural language. Utilize 'agent-brain-rag' to handle the semantic analysis and return relevant results.
6. **Collaboration Features**: If targeting a team environment, include features like sharing documents and notes with other users, commenting on content, and real-time collaboration.
7. **Security Measures**: Ensure all user data is stored securely, including documents and notes. Implement authentication and authorization mechanisms to protect user information.
8. **Testing and Deployment**: Thoroughly test the application for functionality and security. Deploy it to a cloud service provider such as AWS or Heroku once everything works as expected.

This project aims to leverage 'agent-brain-rag' for its intelligent document indexing and semantic search capabilities, providing users with a powerful tool to organize and retrieve information efficiently.