AI Analysis
Final verdict: SUSPICIOUS
The package has a moderate risk score primarily due to missing author information and the lack of a public repository, raising concerns about its origin and legitimacy.
- Metadata risk with missing author information
- Lack of a public repository
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communications.
- Shell: No shell execution patterns detected, indicating no immediate signs of malicious activities such as command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of potential malicious intent due to the missing author information and the lack of a public repository.
Package Quality Overall: Low (3.6/10)
✦ High
Test Suite
9.0
Test suite present — 7 test file(s) found
7 test file(s) detected (e.g. test_alignment.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (2193 chars)
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
○ Low
Multiple Contributors
1.0
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
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
Email domain looks legitimate: gmail.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 3.0
Repository not found (deleted or private)
Repository not found (deleted or private)
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 ataserinyelMSA
Create a command-line tool called 'BioAligner' that leverages the 'ataserinyelMSA' package to perform multiple sequence alignment on biological sequences. This tool should allow users to input a set of DNA or protein sequences and output the aligned sequences. Here are the steps and features you should include:
1. **Sequence Input**: Users should be able to provide their sequences either through a file upload or directly in the command line.
2. **Alignment Execution**: Utilize the 'ataserinyelMSA' package to align the sequences using the MAFFT algorithm. Ensure the user can specify different parameters for the alignment process if needed.
3. **Output Display**: The aligned sequences should be displayed in a clear and readable format. Additionally, provide options for exporting the results to common formats such as FASTA or PHYLIP.
4. **Help Documentation**: Include comprehensive help documentation accessible via a '--help' option that explains all available commands and options.
5. **Error Handling**: Implement robust error handling to manage invalid inputs, file read errors, and other potential issues gracefully.
6. **Version Information**: Add a version information flag ('--version') that shows the current version of BioAligner.
7. **Optional Features**: Consider adding optional features like sequence quality filtering, automatic detection of sequence type (DNA/Protein), and alignment visualization capabilities.
Ensure your implementation is modular, well-documented, and adheres to best coding practices. Use Python's argparse module for command-line argument parsing and ensure the tool is easy to install and run.
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