AI Analysis
The package has a low risk profile due to lack of network calls, shell executions, obfuscations, and credential risks. However, the metadata risk score is elevated due to the repository's novelty and limited activity metrics, raising suspicions about potential supply-chain risks.
- Repository is new with no activity metrics
- Maintainer has only one package on PyPI
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
- Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The repository is new with no activity metrics, and the maintainer has a single package on PyPI, which raises suspicion.
Package Quality Overall: Low (4.0/10)
Partial test coverage signals detected
2 test file(s) detected (e.g. test_concurrency.py)
Some documentation present
Detailed PyPI description (1727 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
16 type-annotated function signatures detected in source
Single-author or unverifiable project
1 unique contributor(s) across 11 commits in leno166/autodoipSingle author with few commits — possibly a personal or throwaway project
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Git history flags: Repository created very recently: 4 day(s) ago (2026-06-03T12:58:26Z)
Repository created very recently: 4 day(s) ago (2026-06-03T12:58:26Z)Repository has zero stars and zero forks
1 maintainer concern(s) found
Author "leno augenstern" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a diagnostic tool application named 'AutoDiagTool' using Python and the 'autodoip' package. This application will serve as a simple yet powerful interface for diagnosing vehicles through the DoIP protocol. The goal of AutoDiagTool is to provide a user-friendly way to interact with the diagnostics services offered by modern vehicles according to ISO 13400 standards. Step 1: Setup the Project Environment - Install Python and necessary libraries including 'autodoip'. - Create a virtual environment and install the 'autodoip' package. Step 2: Design the User Interface - Develop a command-line interface (CLI) for easy interaction. - Optionally, create a basic GUI using Tkinter or another lightweight library. Step 3: Implement Core Functionality - Use 'autodoip' to establish a connection to a vehicle's ECU over a network. - Implement functions to read data from and write data to the ECU based on DoIP specifications. Step 4: Add Advanced Features - Include support for different types of diagnostic requests such as reading diagnostic trouble codes (DTCs), reading sensor data, and performing software updates. - Allow users to customize their requests with specific parameters. - Implement error handling to manage issues like connection failures and invalid responses. Step 5: Testing and Validation - Test the application with real vehicles if possible, ensuring it adheres to DoIP standards. - Validate that all implemented features work correctly under various conditions. How 'autodoip' is Utilized: - For establishing DoIP connections and sending/receiving diagnostic messages. - To handle the low-level details of the DoIP protocol, allowing developers to focus on higher-level functionality.
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