autolevels

v1.3.6 suspicious
6.0
Medium Risk

A tool for automatic photo enhancement using curve corrections.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits high obfuscation risk and shell execution without clear context, raising concerns about its true intentions. However, there is no direct evidence of malicious activities or network risks.

  • High obfuscation risk due to code injection and compression/encoding
  • Shell execution detected but unclear purpose
Per-check LLM notes
  • Network: No network calls detected, which is normal and not indicative of malicious activity.
  • Shell: Shell execution is detected but without clear context on what 'autolevels' command does, it's hard to determine if it's benign or malicious; further investigation into the purpose of 'autolevels' command is recommended.
  • Obfuscation: The presence of code injection and the use of compression/encoding techniques suggests potential for malicious activities.
  • Credentials: No clear patterns indicating credential harvesting were detected.
  • Metadata: The author information is incomplete and the maintainer seems to be new or inactive, which raises some suspicion but not enough to conclude malice.

📦 Package Quality Overall: Medium (5.4/10)

✦ High Test Suite 9.0

Test suite present — 4 test file(s) found

  • Test runner config found: pyproject.toml
  • Test runner config found: conftest.py
  • 4 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (10071 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

  • 8 type-annotated function signatures (partial)
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in yellowdolphin/autolevels
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 8.0

Found 4 obfuscation pattern(s)

  • compressed_data = base64.b64decode(encoded_data[4:]) # Use zlib with appropriate w
  • code injection "f'{x.__import__('os').system('rm -rf /')}'", "f'{x.__class__.__bases__[0]
  • _.__globals__}'", 'f"{__import__("os").system("ls")}"', # Format string injection
  • zip format return zlib.decompress(compressed_data, 15 + 32) # Handle hex-encoded data
⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • h given args.""" result = subprocess.run(f'autolevels {args}'.split(), capture_output=True, text=True
✓ 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 yellowdolphin/autolevels 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 autolevels 
Create a user-friendly image enhancement mini-app using Python that leverages the 'autolevels' package for automatic photo correction. This app should allow users to upload images, apply autolevels enhancements, and save the enhanced version. Here’s a step-by-step guide on what the application should achieve:

1. **Setup**: Install necessary packages including 'autolevels', 'Pillow' for image handling, and 'Flask' or 'Dash' for web interface.
2. **User Interface**: Design a simple yet intuitive UI where users can upload their images. Ensure there’s a button to trigger the enhancement process.
3. **Image Enhancement**: Implement the core functionality using 'autolevels'. When the user clicks the enhance button, the uploaded image should undergo autolevels processing, which automatically adjusts the contrast and brightness of the image.
4. **Display Results**: After enhancement, display both the original and enhanced images side by side so users can compare them easily.
5. **Save Option**: Provide an option for users to download the enhanced image directly from the app.

Additional Features:
- Include sliders to manually adjust parameters if desired, allowing for more control over the enhancement process.
- Add a feature to save the settings used for future reference or reapplication.
- Integrate error handling to ensure smooth operation even when dealing with non-image files or corrupted images.

The goal is to create an accessible tool that anyone can use to improve their photos without needing advanced knowledge of photo editing software.

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