🤖 AI Analysis

Final verdict: SAFE

The package is considered safe with a moderate risk score due to its legitimate network calls and lack of any malicious patterns such as shell execution, obfuscation, or credential harvesting. However, the metadata risk slightly increases the score.

Network calls are legitimate
No shell execution detected
No obfuscation detected
No credentials harvesting detected
Single package from maintainer

Per-check LLM notes

Network: The observed network calls are likely part of the package's intended functionality to download content from URLs, but should be reviewed for legitimacy of the URLs and data handling.
Shell: No shell execution patterns detected.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
Metadata: The maintainer has only one package, indicating a potentially new or less active account.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

ub contents API.""" req = urllib.request.Request(url, headers={"User-Agent": "refgenDetector-installe
ller"}) try: with urllib.request.urlopen(req, timeout=30) as resp: return json.lo
?')} bytes) …") req = urllib.request.Request(raw_url, headers={"User-Agent": "refgenDetector-inst
tor-installer"}) with urllib.request.urlopen(req, timeout=120) as resp, open(out_path, "wb") as f

✓ 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: crg.eu>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Mireia Marin i Ginestar" 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 RefgenDetector

Develop a mini-application named 'GenomeIdentifier' using Python that leverages the 'RefgenDetector' package to identify the reference genome assembly used in BAM/CRAM files and VCFs. This application should be designed for bioinformaticians and researchers who need to quickly determine the specific version of a genome assembly used in their data without manually inspecting file headers or metadata.

### Key Features:
- **File Input:** Allow users to upload one or more BAM/CRAM files or VCF files.
- **Automatic Detection:** Use RefgenDetector to analyze the input files and automatically detect the reference genome assembly used.
- **Detailed Report Generation:** Generate a detailed report for each analyzed file, including the detected genome assembly version, confidence scores, and any discrepancies noted between different files.
- **User Interface:** Implement a simple and intuitive command-line interface for ease of use.
- **Batch Processing:** Enable batch processing of multiple files at once, outputting a summary report for all processed files.
- **Integration with External Tools:** Provide options to integrate the detected information with external tools like variant callers or alignment tools for further analysis.

### Utilization of 'RefgenDetector':
- Integrate RefgenDetector within the application to perform the detection process. Specifically, utilize its functions to read file headers, analyze alignment records, and infer the reference genome assembly from these inputs.
- Ensure that the application handles various file formats and genome species supported by RefgenDetector.
- Include error handling and informative messages to guide users through any issues encountered during file analysis.