🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has some level of obfuscation and low maintainer activity, raising concerns about its transparency and ongoing support. These factors do not definitively indicate malicious intent, but they increase suspicion.

Obfuscation risk at 4/10
Low maintainer activity

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution detected, reducing the risk of unauthorized system command execution.
Obfuscation: The code appears to be obfuscated for path manipulation rather than malicious intent, but the complexity may hide potential issues.
Credentials: No patterns indicative of credential harvesting were detected.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, which could indicate potential issues but does not conclusively suggest malicious intent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 12 test file(s) found

Test runner config found: pyproject.toml
12 test file(s) detected (e.g. test_anidb.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (5264 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 5.0

Partial type annotation coverage

219 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

il = str(tmp_path) + ("\\" if __import__("sys").platform == "win32" else "/") groups = discover([path_w

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ 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 anipyrenamer

Create a command-line tool named 'AnimeRenamerPro' using Python that leverages the 'anipyrenamer' package to automatically rename anime files based on their ED2K hashes and metadata from AniDB. This tool will be designed to streamline the organization of anime collections by ensuring all files are correctly named according to user preferences.

**Steps to Build the Application:**
1. **Setup Environment**: Ensure you have Python installed and set up a virtual environment. Install the 'anipyrenamer' package along with other necessary dependencies like argparse for command-line argument parsing.
2. **Design User Interface**: Create a simple yet intuitive command-line interface where users can specify the folder containing their anime files, select options for renaming (e.g., include episode numbers, sort by release date), and decide whether to download cover art and episode information.
3. **Implement Core Functionality**: Utilize 'anipyrenamer' to scan through the specified directory, identify anime files, and use their ED2K hashes to fetch accurate metadata from AniDB. The application should then rename the files according to the chosen format and any additional user-specified rules.
4. **Enhance with Additional Features**: Consider adding options for bulk renaming, support for multiple subtitle languages, and integration with cloud-based storage services for backing up renamed files.
5. **Testing and Debugging**: Thoroughly test the application under various conditions, including handling large file sizes, different naming conventions, and network issues accessing AniDB.
6. **Documentation and Deployment**: Provide comprehensive documentation detailing how to install and use the application. Package it as a standalone executable for easy distribution.

**Suggested Features**:
- Support for both batch and individual file renaming.
- Ability to filter by anime title, season, or series type.
- Option to save and load renaming configurations.
- Integration with popular cloud storage solutions for backup purposes.
- Detailed logging and error handling mechanisms.