audit-ready-memory

v0.0.1 suspicious
4.0
Medium Risk

Audit-ready, local-first memory for AI agents

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network, shell execution, and obfuscation. However, its low activity and poor metadata quality raise concerns about its legitimacy and purpose.

  • Low activity and poor metadata quality
  • No evident malicious activities detected
Per-check LLM notes
  • Network: No network calls suggest the package does not engage in external communications, which is normal unless specific functionality requires it.
  • Shell: No shell executions indicate that the package does not execute system commands, reducing potential risks associated with unauthorized access or operations.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows low activity and poor metadata quality, raising suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (3.0/10)

○ Low Test Suite 1.0

No test suite detected

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

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.humem.ai/audit-ready-memory/
○ 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
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 3 commits in humemai/audit-ready-memory
  • 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 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 "HumemAI" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with audit-ready-memory 
Develop a fully-functional mini-app called 'AuditLogAI' that leverages the 'audit-ready-memory' package to provide a robust, secure, and easily auditable logging system for AI interactions. This application will serve as a crucial tool for developers and data scientists who need to maintain a record of all AI operations, ensuring compliance with regulatory standards and facilitating transparent audits. Here’s a detailed plan on how to approach this project:

1. **Setup**: Begin by installing the 'audit-ready-memory' package and setting up your Python environment. Ensure you have all necessary dependencies installed.

2. **Core Functionality**:
   - Implement a class `AuditLog` that initializes an instance of the 'audit-ready-memory' module to manage logs.
   - Develop methods within the `AuditLog` class for adding new log entries, retrieving logs based on certain criteria (e.g., time range, operation type), and exporting logs in various formats (CSV, JSON).

3. **Security Features**:
   - Integrate encryption capabilities into the log storage process to protect sensitive information.
   - Implement user authentication to restrict access to the logs, ensuring only authorized personnel can view or modify them.

4. **User Interface**:
   - Design a simple command-line interface (CLI) for users to interact with the 'AuditLogAI' app.
   - Provide options for users to add new logs, search through existing logs, and export logs.

5. **Testing & Documentation**:
   - Write comprehensive tests to validate the functionality and security of the application.
   - Create detailed documentation explaining how to install, configure, and use 'AuditLogAI', including examples of common use cases.

By utilizing the 'audit-ready-memory' package, 'AuditLogAI' will not only ensure that all AI-related activities are meticulously logged but also that these logs are stored securely and are easily accessible for audit purposes. This project aims to streamline the process of maintaining an audit trail for AI systems, thereby enhancing transparency and compliance.

💬 Discussion Feed

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