apeawake

v0.5.1 suspicious
6.0
Medium Risk

Keep your laptop awake while an AI agent finishes its task

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package uses direct shell execution which can pose significant risks due to potential unauthorized system modifications. Although it does not appear to engage in credential harvesting or network activity that could directly exfiltrate data, the overall risk is elevated due to the unusual use of shell commands and the maintainer's lack of verified identity.

  • High shell risk due to use of os.system with sudo
  • Maintainer metadata lacking proper identification
Per-check LLM notes
  • Network: No network calls detected.
  • Shell: Direct use of os.system to execute shell commands, especially with sudo, can be risky and is not typical for a package named 'apeawake'. This could indicate potential for unauthorized system changes.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, which may indicate potential risk.

📦 Package Quality Overall: Low (3.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (3581 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

  • 36 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 6 commits in RobinDFeder/apeawake
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • {e}") # Apply settings — os.system() gives sudo a real TTY for password prompt failed = Fal
  • TTERY_SETTINGS: ret = os.system(f"sudo pmset {target} {key} {value}") if ret != 0:
  • ey, value = parts os.system(f"sudo pmset {target} {key} {value}") try: os.r
  • ue in sleep_settings: os.system(f"sudo -n pmset {target} {key} {value} 2>/dev/null") class
  • for the session.\n") os.system("sudo -v") # Background thread refreshes sudo token
  • # 4 minutes os.system("sudo -v -n") # -n = non-interactive, uses cached token
✓ 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

Repository RobinDFeder/apeawake 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 apeawake 
Create a Python-based utility named 'TaskGuard' that ensures your computer remains active while an AI-assisted task runs in the background. This utility will leverage the 'apeawake' package to keep the system awake, preventing it from going into sleep mode due to inactivity. TaskGuard should be user-friendly and capable of running on both Windows and macOS systems. Here’s a detailed breakdown of what your application should achieve:

1. **User Interface**: Design a simple command-line interface (CLI) that allows users to input the path to the AI script they wish to run and select options like 'Run Once', 'Run Until Completion', or 'Keep Running'.
2. **Integration with 'apeawake'**: Utilize the 'apeawake' package to monitor the system's activity level and simulate keyboard/mouse events to prevent the system from sleeping. Ensure that 'apeawake' is only activated when the AI task starts and deactivated once the task completes.
3. **AI Task Execution**: Implement functionality within TaskGuard that executes the specified AI script. The AI script could be anything from training a machine learning model to generating text with a language model. Ensure that TaskGuard can handle different types of scripts by allowing users to specify the execution method (e.g., Python, Jupyter Notebook).
4. **Status Monitoring**: Provide real-time feedback about the status of the AI task and the system's wakefulness. This includes displaying progress updates from the AI task and alerts if the system attempts to go to sleep despite 'apeawake' efforts.
5. **Customization Options**: Allow users to customize settings such as the frequency of simulated activity events and the threshold at which the system considers itself inactive. These settings should be saved in a configuration file for easy access.
6. **Error Handling and Logging**: Implement robust error handling to manage any issues that arise during the execution of the AI task or the operation of 'apeawake'. Log these errors in a readable format for troubleshooting purposes.
7. **Security Considerations**: Ensure that TaskGuard does not interfere with the normal operation of security software or other critical system processes. Also, consider adding safeguards against unauthorized use or modification of the AI scripts.

By completing this project, you'll create a versatile tool that simplifies the process of running long-running AI tasks without worrying about the system falling asleep.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!