async-runtime-auditor

v0.1.1 suspicious
4.0
Medium Risk

Runtime audit CLI for detecting asyncio degradation and threadpool saturation.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of legitimacy but the metadata risk score is relatively high due to low repository engagement and recent activity, raising suspicion.

  • Metadata risk is elevated
  • Low network, shell, obfuscation, and credential risks
Per-check LLM notes
  • Network: The observed network calls appear to be legitimate health checks and queries, which could be part of the intended functionality for an 'auditor' package.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting the package does not pose a risk for stealing secrets or credentials.
  • Metadata: The repository's recent activity and low engagement suggest potential risk.

📦 Package Quality Overall: Low (2.2/10)

○ 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 (8819 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 5 commits in priyanshuphenomenal007/async-runtime-auditor
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • try: response = requests.get(health_endpoint, timeout=5) response.raise_for_stat
  • try: response = requests.get( query_endpoint, params={"query":
✓ Code Obfuscation

No obfuscation patterns detected

✓ 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 score 5.0

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
  • All 5 commits happened within 24 hours
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Priyanshu" 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 async-runtime-auditor 
Your task is to develop a Python-based utility called 'AsyncAuditTool' which leverages the 'async-runtime-auditor' package to monitor and analyze the performance of asyncio applications. This tool will help developers identify potential issues such as asyncio degradation and threadpool saturation, ensuring their applications run smoothly and efficiently.

### Project Scope:
1. **Setup**: Begin by installing the necessary packages including 'async-runtime-auditor'. Ensure your environment is set up correctly to support asyncio and concurrent operations.
2. **Monitoring Functionality**: Implement a function within AsyncAuditTool that periodically audits the runtime of an asyncio application. This function should use 'async-runtime-auditor' to detect any signs of asyncio degradation or threadpool saturation.
3. **Analysis Reports**: Develop a feature that generates detailed analysis reports based on the collected data from the monitoring phase. These reports should highlight problematic areas such as high CPU usage, excessive I/O wait times, and other performance bottlenecks.
4. **Alert System**: Integrate an alert system into AsyncAuditTool. When the tool detects significant performance issues, it should notify the user via email or another preferred method.
5. **User Interface**: Design a simple command-line interface (CLI) for AsyncAuditTool, allowing users to easily start/stop monitoring sessions and view analysis reports.
6. **Documentation**: Provide comprehensive documentation explaining how to install and use AsyncAuditTool, along with examples of common use cases.

### Suggested Features:
- Real-time monitoring of asyncio tasks and threads.
- Historical data storage and trend analysis.
- Customizable alert thresholds for different types of performance metrics.
- Integration with popular logging frameworks like Loguru or Python's built-in logging module.
- Support for both Windows and Unix-like operating systems.

### Utilizing 'async-runtime-auditor':
- Use 'async-runtime-auditor' to perform periodic audits of the asyncio runtime. This includes checking for threadpool saturation, asyncio event loop performance, and other critical metrics.
- Leverage the package's CLI capabilities to streamline the auditing process and ensure consistent results across different environments.
- Incorporate 'async-runtime-auditor' into your alert system to trigger notifications based on specific audit outcomes.

By completing this project, you will create a valuable tool for developers working with asyncio applications, helping them maintain optimal performance and reliability.

💬 Discussion Feed

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