🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to potential shell execution and network calls, although these might be legitimate functionalities. However, the low activity of the maintainer's account adds uncertainty.

Moderate shell execution risk
Potential undocumented network calls
Inactive maintainer account

Per-check LLM notes

Network: The network call pattern suggests the package may be attempting to fetch external resources which could be legitimate if documented, but requires verification.
Shell: Shell execution patterns indicate the package is using subprocess calls, which can be legitimate for system checks or operations, but also pose a risk if not properly sanitized or intended for unauthorized actions.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.
Metadata: The maintainer has a new or inactive account and lacks detailed author information, raising some suspicion but not definitive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

start() try: with urllib.request.urlopen(url, timeout=2) as resp: body = resp.rea

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

nt info try: df = subprocess.run( ["df", "-T", str(target.resolve())],
ass try: mount = subprocess.run( ["mount"], capture_output=True, text=True, time
nted to stdout.""" proc = subprocess.run( ["absentia", "check", str(target), "--json"],
{' '.join(cmd)}") return subprocess.run(cmd).returncode def _write_languages_config(dest: Path, la
' '.join(cmd)}\n") return subprocess.run(cmd).returncode def main(argv: list[str] | None = None) ->
eturn stdout.""" result = subprocess.run( [sys.executable, "-m", "pip", *args], captu

✓ 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

Repository skbays03/absentia appears legitimate

⚠ 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 absentia

Create a Python-based code analysis tool named 'CodeGapFiller' using the 'absentia' package. This tool will help developers identify potential gaps or missing functionalities in their existing codebase, suggesting improvements based on common coding practices and best standards. Here’s how you can structure the project:

1. **Project Setup**: Start by setting up a virtual environment and installing necessary packages including 'absentia'.
2. **Code Parsing**: Implement functionality to parse different types of Python files from a given directory. Use 'absentia' to analyze these files for potential holes or missing functionalities.
3. **Analysis and Reporting**: Utilize 'absentia' to find and categorize issues into different types such as unused imports, redundant code blocks, missing error handling, etc. Generate a detailed report summarizing findings.
4. **Suggestion Engine**: Based on the identified issues, develop a feature that suggests fixes or improvements. For instance, if it detects unused imports, suggest removing them; if there's missing documentation, suggest adding comments or docstrings.
5. **Integration with IDEs**: Aim to integrate CodeGapFiller as a plugin or extension for popular IDEs like VSCode or PyCharm, allowing real-time analysis and suggestions during development.
6. **User Interface**: Develop a simple command-line interface (CLI) for users to interact with the tool easily. Additionally, consider building a basic web interface for more advanced users who prefer visual tools.
7. **Testing and Validation**: Ensure thorough testing of all functionalities, including edge cases where 'absentia' might not directly provide solutions but could indicate areas needing human intervention.
8. **Documentation**: Provide comprehensive documentation detailing how to install, use, and extend CodeGapFiller, including examples and best practices.

By following these steps, you'll create a powerful yet user-friendly tool that significantly enhances code quality and maintenance.