audit-stream

v0.1.0 suspicious
6.0
Medium Risk

Append-only governance event stream. Hash-chained for tamper-evidence, SSE for live tailing, REST for queries. The cross-cutting telemetry layer for the Kinetic Gain portfolio.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some red flags, particularly due to its lack of metadata and activity, as well as hosting on an unpopulated repository, which raises concerns about its legitimacy and origin.

  • Metadata risk score of 5/10 due to missing author details and lack of repository activity
  • Hosted on an unpopulated git repository, raising suspicion
Per-check LLM notes
  • Network: The presence of a network call to localhost suggests internal testing or debugging rather than malicious activity, but it could still indicate unexpected behavior.
  • Shell: No shell execution patterns were detected, indicating low risk.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating safe handling of sensitive information.
  • Metadata: The package is new with no activity, missing author details, and hosted on an unpopulated git repository, raising suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 2 test file(s) found

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

Some documentation present

  • Detailed PyPI description (6123 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • Type checker (mypy / pyright / pytype) referenced in project
  • 29 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 5 commits in mizcausevic-dev/audit-stream-py
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • tp://localhost:8093" with httpx.Client(base_url=base, timeout=5.0) as client: # decision-ca
✓ 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: kineticgain.com>

✓ 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 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 audit-stream 
Create a real-time audit logging system using the Python package 'audit-stream'. This system will serve as a critical component for monitoring and ensuring the integrity of operations within a small e-commerce platform. Your task is to design and implement a mini-application that captures and logs all significant events (e.g., user login attempts, product purchases, admin actions) in a tamper-evident manner, allowing for real-time monitoring and historical analysis.

**Steps to Follow:**
1. **Setup Environment**: Begin by setting up your Python environment and installing the necessary packages, including 'audit-stream'. Ensure you have the latest version installed.
2. **Define Event Types**: Identify and define the types of events you want to log. These could include user logins, product views, purchases, and administrative actions.
3. **Implement Event Logging**: Use 'audit-stream' to create a logging mechanism that appends each event to a secure, hash-chained stream. This ensures that once an event is logged, it cannot be altered without detection.
4. **Real-Time Monitoring**: Set up a feature that allows users to subscribe to the audit stream via Server-Sent Events (SSE). This enables real-time tailing of the audit logs from a web interface or other client applications.
5. **Query Interface**: Develop a RESTful API that provides access to the audit logs. Users should be able to query logs based on various criteria such as time range, event type, and user ID.
6. **Security Measures**: Implement basic security measures such as authentication for accessing the REST API and securing the connection between clients and the server.
7. **Testing**: Write tests to ensure that your implementation works correctly and that the tamper-evidence properties hold.
8. **Documentation**: Provide comprehensive documentation explaining how to set up and use your audit logging system.

**Suggested Features**:
- Support for multiple concurrent subscribers to the SSE stream.
- Ability to filter events based on severity levels (info, warning, error).
- Integration with existing logging frameworks (if applicable).
- Optional encryption of log data at rest and in transit.
- A simple UI for browsing and searching through past logs.

Utilize the 'audit-stream' package's capabilities to ensure that your audit logging system is robust, secure, and easy to integrate into existing systems.

💬 Discussion Feed

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