axiongraph

v0.0.5 suspicious
4.0
Medium Risk

Invisible events. Replayable graphs. An append-only execution-graph event model and deterministic reducer — provider-agnostic, storage is a port.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of network, shell, and obfuscation activities, but the metadata risk score is high due to recent repository creation and lack of engagement metrics.

  • Metadata risk is high due to recent repository creation
  • Lack of engagement metrics suggests low activity
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
  • Metadata: The repository was created recently and lacks engagement metrics, indicating potential low activity or intent.

📦 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 (4086 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
  • 30 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 17 commits in cachetronaut/axiongraph-py
  • 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 5.0

Git history flags: Repository created very recently: 5 day(s) ago (2026-06-03T19:33:28Z)

  • Repository created very recently: 5 day(s) ago (2026-06-03T19:33:28Z)
  • 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 axiongraph 
Create a mini-application called 'EventLogAnalyzer' using the Python package 'axiongraph'. This application will serve as a tool for developers to log and analyze invisible events in their applications, ensuring that every event is replayable and stored in an append-only manner. The goal is to demonstrate the power of axiongraph's event model and deterministic reducer in maintaining a consistent and reliable record of application events.

### Features:
1. **Event Logging**: Implement a feature where users can log events without exposing sensitive information, leveraging axiongraph's ability to handle invisible events.
2. **Event Replay**: Develop a replay functionality that allows users to re-execute the sequence of logged events exactly as they occurred, showcasing the deterministic nature of axiongraph.
3. **Graph Visualization**: Integrate a graph visualization component to visually represent the sequence of events in a user-friendly manner, highlighting the structure and flow of operations.
4. **Querying and Filtering**: Enable users to query and filter events based on specific criteria such as time stamps, event types, or custom metadata, proving the flexibility and utility of the axiongraph package.
5. **Storage Agnosticism**: Demonstrate how 'EventLogAnalyzer' can work with different storage backends without changing its core logic, thanks to axiongraph's provider-agnostic approach.

### Steps to Build the Application:
1. **Setup Environment**: Install necessary packages including axiongraph, and set up a development environment.
2. **Design Data Models**: Define data models for events and their metadata, considering how these will interact with axiongraph's event model.
3. **Implement Event Logging**: Use axiongraph to log events in an append-only fashion, ensuring no events are overwritten or deleted.
4. **Develop Replay Functionality**: Create a mechanism to replay logged events, emphasizing the deterministic behavior provided by axiongraph.
5. **Integrate Graph Visualization**: Utilize a graph visualization library to create dynamic visual representations of event sequences.
6. **Add Query and Filter Capabilities**: Implement a search function that allows users to find and filter events based on various parameters.
7. **Test with Different Storage Backends**: Showcase the application's ability to work seamlessly with multiple storage solutions, highlighting axiongraph's agnostic nature.
8. **Documentation and User Guide**: Provide comprehensive documentation detailing how to use 'EventLogAnalyzer', including examples and best practices.

This project not only leverages the unique capabilities of axiongraph but also provides a practical demonstration of its effectiveness in real-world scenarios.

💬 Discussion Feed

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