🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits several concerning behaviors including interaction with shell commands and password managers, suggesting potential risks related to credential handling and execution of system commands. While there are no clear signs of malicious intent, the combination of these factors warrants further scrutiny.

High shell risk due to potential interaction with password managers
Code obfuscation techniques that could be used for code injection

Per-check LLM notes

Network: The use of aiohttp with a custom User-Agent suggests the package is making network requests to identify itself to servers.
Shell: Executing 'pass show' indicates interaction with password managers which could imply handling sensitive credentials, raising concerns about potential misuse.
Obfuscation: The use of eval with f-string and unusual syntax suggests potential for code injection or obfuscation.
Credentials: The usage of keyring.get_password and getpass.getpass may indicate credential handling, but could be legitimate for user authentication purposes.
Metadata: The package shows low maintenance and metadata quality but lacks clear indicators of malicious intent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

cookies() async with aiohttp.ClientSession( headers={"User-Agent": f"{NAME}/{VERSION}"},

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

] = capture result = eval(f"f{right!r}", {}, locals_dir) return Transformed(Pu

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

name}'") result = subprocess.check_output(["pass", "show", self._passname], text=True) except

⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

self._password = keyring.get_password(self._keyring_name, self._username) # If that fails
wait in_daemon_thread(lambda: getpass.getpass(prompt)) async def prompt_yes_no(query: str, default: Opti

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Garmelon/PFERD appears legitimate

⚠ 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 PFERD

Create a mini-application called 'Bulk Downloader' using the Python package 'PFERD'. This application should allow users to download multiple files from a list of URLs efficiently. The core functionality of PFERD revolves around downloading files in bulk, making it perfect for this use case. Here’s a detailed plan on how to implement the application:

1. **User Interface**: Design a simple command-line interface where users can input a text file containing newline-separated URLs of files they wish to download. Additionally, provide options for specifying a directory where the downloaded files will be stored.
2. **Input Validation**: Ensure that the provided URLs are valid and that the specified download directory exists or can be created. Handle any exceptions gracefully, providing informative error messages.
3. **Download Functionality**: Use PFERD to handle the actual downloading process. Implement a feature to monitor the progress of each download and display it to the user in real-time. Consider implementing a retry mechanism for failed downloads.
4. **Concurrency Control**: Allow users to specify the number of simultaneous downloads. Utilize PFERD's capabilities to manage these concurrent downloads effectively without overwhelming the system.
5. **Error Handling & Logging**: Implement robust error handling to manage various scenarios such as network issues, invalid URLs, or storage capacity limits. Log all actions and errors to a log file for later review.
6. **Additional Features**: Optionally, add features like resuming interrupted downloads, filtering file types based on extensions, and compressing the downloaded files into a single archive.
7. **Documentation**: Provide clear documentation on how to install and run the application, including examples of how to format the URL list file.

This project aims to demonstrate the power and ease of use of PFERD while providing a practical tool for anyone needing to download multiple files from the web.