T-autolog

v2.6.0 suspicious
6.0
Medium Risk

Zero-config auto-instrumentation logging for Python

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant obfuscation risk, suggesting potential for hidden malicious activities. The incomplete maintainer information adds to the suspicion, though no concrete malicious activity has been confirmed.

  • High obfuscation risk due to dynamic execution of compiled code
  • Incomplete maintainer information
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no direct system command execution observed.
  • Obfuscation: The code patterns suggest dynamic execution of compiled code which can be used for obfuscation or hiding malicious activities.
  • Credentials: No clear patterns indicative of credential harvesting were found.
  • Metadata: The repository is not found and the maintainer information is incomplete, raising suspicion but not conclusive evidence of malice.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • ) mod.__name__ = name exec(compile(code, f"{name}.py", "exec"), mod.__dict__) return mod
  • mod.__name__ = name exec(compile(code, f"{name}.py", "exec"), mod.__dict__) return mod def _remove_autolog_finde
✓ 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ 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 T-autolog 
Your task is to develop a simple yet powerful command-line utility that monitors and logs the performance of Python scripts running on your local machine. This utility will automatically instrument any Python script to log key metrics such as execution time, memory usage, and exceptions without requiring any configuration changes to the monitored scripts themselves. You'll be using the 'T-autolog' package, which provides zero-config auto-instrumentation logging for Python.

### Project Requirements:
1. **Application Name**: AutoLogMonitor
2. **Core Functionality**:
   - Automatically instrument any Python script to log its execution time, memory usage, and exceptions.
   - Logs should be saved in a structured format (e.g., JSON or CSV).
3. **Features**:
   - Support for multiple log levels (INFO, DEBUG, ERROR).
   - Ability to filter logs based on specific criteria (e.g., only log errors).
   - Command-line interface for controlling the monitoring process.
   - Real-time monitoring and alerting for critical issues (e.g., high memory usage).
4. **How to Use T-autolog**:
   - Import T-autolog at the beginning of your main application file.
   - Configure T-autolog to start logging automatically when a Python script starts.
   - Ensure that T-autolog captures all necessary performance metrics and exceptions.
   - Implement functionality to save logs to a specified directory in real-time.
5. **Steps to Complete the Project**:
   - Set up a virtual environment for your project.
   - Install T-autolog via pip.
   - Write the main application code that initializes T-autolog and sets up the monitoring logic.
   - Develop the command-line interface using argparse or similar libraries.
   - Test your application by monitoring different Python scripts and verifying the logs.
6. **Additional Notes**:
   - Ensure that your application is user-friendly and easy to configure.
   - Consider adding documentation to guide users on how to use AutoLogMonitor effectively.
   - Explore ways to extend AutoLogMonitor to support additional metrics if time permits.