axiora

v0.12.0 suspicious
6.0
Medium Risk

The official Python library for the axiora API

🤖 AI Analysis

Final verdict: SUSPICIOUS

While the package shows no signs of immediate malicious intent such as network calls or shell executions, the low engagement and sparse maintainer information in the repository raise concerns about its reliability and long-term support.

  • Low repository engagement
  • Sparse maintainer information
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
  • Metadata: The repository's low engagement and sparse maintainer information suggest potential unreliability.

📦 Package Quality Overall: Medium (5.2/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5611 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 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 598 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 78 commits in axioradev/axiora-sdk
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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

Email domain looks legitimate: axiora.dev>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 axiora 
Create a Python-based mini-application named 'Axionet' which serves as a network monitoring tool utilizing the 'axiora' library. This tool should be able to perform real-time network diagnostics on local devices and remote servers. The primary goal of Axionet is to provide users with comprehensive insights into their network health and performance, including metrics such as latency, packet loss, and connection stability.

### Core Features:
1. **Network Connectivity Check**: Implement a feature that periodically checks if a given IP address or domain name is reachable. Use the 'axiora' library to initiate and manage these checks efficiently.
2. **Latency Measurement**: Measure the round-trip time (RTT) between the user's device and the target IP or domain name. Display this information in a human-readable format, such as milliseconds.
3. **Packet Loss Detection**: Determine the percentage of packets lost during transmission from the user's device to the target location. This will help users understand the reliability of their connections.
4. **Connection Stability Analysis**: Analyze multiple RTT measurements over a short period to determine the stability of the connection. Highlight any significant fluctuations that could indicate issues.
5. **User-Friendly Interface**: Develop a simple yet effective command-line interface (CLI) where users can input IP addresses or domain names, select the type of test they want to run, and view results directly.
6. **Logging and Reporting**: Allow users to save test results to a log file and generate reports based on historical data. This feature will enable users to track changes in network performance over time.

### Utilization of 'axiora' Package:
- **Initialization**: Use 'axiora' to initialize network diagnostic sessions.
- **Execution**: Leverage the package's functions to execute connectivity checks, latency tests, and packet loss detection.
- **Data Handling**: Employ 'axiora' to handle the data collected from these operations, ensuring accurate and reliable results.
- **Integration**: Integrate 'axiora' functionalities seamlessly within the CLI to provide an intuitive user experience.

By building 'Axionet', you'll not only demonstrate proficiency in using the 'axiora' library but also create a valuable tool for anyone interested in monitoring their network performance.

💬 Discussion Feed

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