🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to shell execution and concerns over metadata. While there is no direct evidence of malicious activity, the lack of author information and low repository activity raise suspicion.

Shell execution may indicate legitimate functionality but also potential for abuse.
Anonymous author and low repository activity suggest possible supply-chain risks.

Per-check LLM notes

Network: No network calls detected, which is normal and not indicative of malicious activity.
Shell: Shell execution suggests the package may run external commands, which could be legitimate but requires further investigation to ensure it's not being used maliciously.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating low risk of unauthorized access.
Metadata: The package shows some red flags such as an anonymous author and low activity in the git repository, but there's no clear evidence of malicious intent.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

""" try: result = subprocess.run(command, check=True, capture_output=True, text=True, cwd=wor

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: inrae.fr>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 aegis-bio

Your task is to develop a fully functional mini-application called 'GenomeAnalyzer' that leverages the capabilities of the 'aegis-bio' Python package to analyze genomic data. This application will serve as a tool for biologists and researchers to extract meaningful annotations from genomic sequences, integrate these annotations into a comprehensive database, and visualize the results for easier interpretation.

**Step-by-Step Development Guide:**
1. **Setup and Installation**: Begin by setting up a virtual environment for your project and installing the necessary packages including 'aegis-bio'. Ensure you have Python installed on your system and proceed with pip installation commands.
2. **Data Input**: Design a user-friendly interface where users can upload their genomic sequence files (e.g., FASTA format). Implement error handling to ensure only valid file types are accepted.
3. **Annotation Extraction**: Utilize 'aegis-bio' to process the uploaded sequences and extract relevant biological annotations such as gene names, functions, and locations. The package's core functionalities should be explored here, focusing on how it facilitates the extraction process.
4. **Database Integration**: Create a simple database (SQLite recommended for simplicity) to store the extracted annotations alongside metadata like upload time, user ID, etc. This will allow users to retrieve previous analyses and track changes over time.
5. **Visualization**: Develop a feature that visualizes the annotated sequences using matplotlib or any other suitable library. The visualization should clearly highlight key features like gene locations and functions.
6. **User Interface**: While a command-line interface is acceptable, aim for a web-based interface using Flask or Django. This will make the application more accessible and user-friendly.
7. **Documentation and Testing**: Write comprehensive documentation detailing how to use GenomeAnalyzer, including setup instructions, example usage, and troubleshooting tips. Perform thorough testing to ensure all components work seamlessly together.

**Suggested Features**:
- Support for multiple file formats (FASTA, GFF, etc.)
- Advanced search functionality within the database for quick retrieval of specific annotations
- Real-time progress indicators during long-running tasks
- Export options allowing users to save their analyses in various formats (CSV, JSON)
- Integration with external APIs for additional annotation sources

By completing this project, you'll not only gain hands-on experience with 'aegis-bio', but also create a valuable tool for the scientific community.