afdb-query

v0.2.0 safe
4.0
Medium Risk

Sequence-based programmatic access to the AlphaFold Protein Structure Database

🤖 AI Analysis

Final verdict: SAFE

The package is considered safe based on the analysis. It primarily performs network operations as expected for its functionality, and there are no indications of malicious behavior.

  • Network risk is moderate due to external API calls.
  • Low risk scores in shell execution, obfuscation, and credential handling.
Per-check LLM notes
  • Network: The package makes network calls which seem to be part of its intended functionality, fetching data from a specific URL with parameters.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows low maintenance and metadata quality indicators, but lacks clear malicious signals.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • tries) self._client = httpx.Client(base_url=base_url, timeout=timeout, transport=transport)
  • _expected_shape(): resp = httpx.get( SUMMARY_URL, params={"id": GOT2, "type": "s
  • IKLMNPQRSTVWY" * 3 resp = httpx.get( SUMMARY_URL, params={"id": bogus, "type": "
  • ive files on AFDB. resp = httpx.get( SUMMARY_URL, params={"id": GOT2, "type": "s
  • endswith(".cif") model = httpx.get(model_url, timeout=60, follow_redirects=True) assert mod
  • f_url != model_url conf = httpx.get(conf_url, timeout=60, follow_redirects=True) assert conf
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with afdb-query 
Develop a mini-application called 'ProteinStructureExplorer' using Python's 'afdb-query' package. This tool aims to provide researchers and students with a simple yet powerful interface to query and visualize protein structures from the AlphaFold database based on sequence information.

### Features:
1. **Sequence Input:** Users should be able to input a protein sequence either by pasting it directly into the application or uploading a FASTA file.
2. **Query Execution:** Once the sequence is provided, the application will use 'afdb-query' to search the AlphaFold database for matching protein structures.
3. **Results Display:** After querying, the application should display relevant results such as the protein name, UniProt ID, and confidence score of the structure prediction.
4. **Visualization:** Implement a feature that allows users to visualize the 3D structure of the selected protein using a library like PyMOL or similar visualization tools.
5. **Export Option:** Provide an option for users to export the visualized 3D structure as a PDB file for further analysis or sharing.
6. **User Interface:** Design a user-friendly graphical interface using a framework like PyQt or Tkinter to make the application accessible and easy to use.

### Utilization of 'afdb-query':
- Use 'afdb-query' to perform the actual query against the AlphaFold database. Ensure that you handle API keys or any necessary authentication properly if required by the package.
- Explore the documentation of 'afdb-query' to understand how to parse the response and extract useful information about the protein structures.
- Consider implementing error handling for cases where no results are found or when there are issues with the input sequence.

### Additional Considerations:
- Ensure that the application is well-documented, including instructions on how to install dependencies and run the application.
- Add comments and docstrings in your code to improve readability and maintainability.
- Test your application thoroughly with various sequences to ensure reliability and robustness.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!