arcmemory-bendex

v0.1.0 suspicious
4.0
Medium Risk

Memory integrity monitoring for AI agents — Bendex Geometry

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal direct security risks, but its low maintainer activity and poor metadata quality raise concerns about its reliability and potential maintenance issues.

  • Low maintainer activity
  • Poor metadata quality
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access to function properly.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of credential theft.
  • Metadata: The package shows low maintainer activity and poor metadata quality, which could indicate potential risks but does not conclusively point to malicious intent.

📦 Package Quality Overall: Low (3.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 9 type-annotated function signatures (partial)
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in 9hannahnine-jpg/arc-gate
  • 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository 9hannahnine-jpg/arc-gate appears legitimate

⚠ Maintainer History score 8.0

4 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)
  • 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 arcmemory-bendex 
Create a memory integrity monitoring tool for AI agents using the Python package 'arcmemory-bendex'. Your task is to develop a mini-application that ensures the security and reliability of AI agent operations by continuously monitoring their memory usage and detecting any anomalies or potential threats. This tool should serve as a robust solution for safeguarding AI systems from malicious attacks or accidental data corruption.

Key Features:
1. Real-time Monitoring: Implement a feature that tracks the memory usage of AI agents in real-time, providing immediate alerts when any unusual activity is detected.
2. Integrity Checks: Utilize the 'arcmemory-bendex' package to perform regular integrity checks on the AI agent's memory, ensuring data consistency and preventing unauthorized modifications.
3. Detailed Reports: Generate comprehensive reports that detail the memory usage patterns and any detected issues over time, allowing users to analyze the health of their AI systems.
4. User Interface: Develop a user-friendly interface where users can monitor the status of their AI agents, configure alert settings, and access historical data.
5. Integration Capabilities: Ensure your application can integrate with popular AI frameworks and platforms, making it easy for developers to incorporate memory integrity monitoring into their existing projects.

How to Use 'arcmemory-bendex':
- Initialize the monitoring process by importing and configuring the necessary modules from the 'arcmemory-bendex' package.
- Schedule periodic integrity checks using the package's built-in functions, which will scan the AI agent's memory for inconsistencies.
- Implement callback functions that trigger when specific conditions are met (e.g., memory usage exceeds a certain threshold), allowing for automated responses such as logging events or sending notifications.
- Leverage the package's reporting tools to compile detailed analyses of memory usage trends and potential vulnerabilities, helping to maintain the long-term stability and security of AI systems.

💬 Discussion Feed

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