AI Analysis
Final verdict: SUSPICIOUS
The package shows low risk in terms of network calls, shell execution, and obfuscation. However, the missing repository, inactive maintainer, and single version release raise concerns about potential supply-chain risks.
- Repository not found and maintainer appears inactive
- Only one version has been released
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 the package does not execute external commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The repository is not found, the maintainer seems new and inactive, and there's only one version released, which raises suspicion.
Package Quality Overall: Low (3.6/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
7.0
Some documentation present
Documentation URL: "Documentation" -> https://marketplace.singularitynet.io/servicedetails/org/neuDetailed PyPI description (1835 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
3 type-annotated function signatures (partial)
○ Low
Multiple Contributors
1.0
Could not retrieve contributor data from GitHub
GitHub API error: 404
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
score 3.0
Repository not found (deleted or private)
Repository not found (deleted or private)
Maintainer History
score 6.0
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" 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 agentsentinel-autogen
Develop a Python-based application named 'AutoGenGuard' which acts as a security monitor for AutoGen multi-agent systems. This tool will utilize the 'agentsentinel-autogen' package to ensure secure and ethical operations within these environments. Here’s a step-by-step guide to building this application: 1. **Setup Project Environment**: Begin by setting up your Python environment. Ensure you have the latest version of Python installed, then create a virtual environment and install the 'agentsentinel-autogen' package via pip. 2. **Design Application Structure**: Create a modular structure for your application. Include modules for initializing the security scanner, monitoring agent interactions, logging events, and generating reports. 3. **Integrate 'agentsentinel-autogen'**: Use 'agentsentinel-autogen' to scan conversations between agents for potential security risks such as data leakage, unauthorized access attempts, or malicious activities. Integrate the package’s scanning capabilities into your application’s core functions. 4. **Implement Real-Time Monitoring**: Develop a feature that allows real-time monitoring of agent conversations. Whenever an agent interaction is detected, the application should use 'agentsentinel-autogen' to analyze the conversation and flag any suspicious activities immediately. 5. **Generate Detailed Reports**: Implement a reporting system that summarizes all monitored activities and flagged incidents. The report should include timestamps, details of the interaction, the type of security risk identified, and recommendations for action. 6. **User Interface**: Create a simple command-line interface (CLI) for users to interact with 'AutoGenGuard'. Users should be able to start/stop monitoring, view reports, and configure settings directly from the CLI. 7. **Testing and Validation**: Test the application thoroughly using simulated agent interactions. Validate its effectiveness in identifying various types of security threats accurately. 8. **Documentation and Deployment**: Document the setup process, configuration options, and usage instructions for 'AutoGenGuard'. Prepare it for deployment in real-world scenarios where AutoGen multi-agent systems are employed. Suggested Features: - Support for multiple concurrent monitoring sessions. - Customizable alerting mechanisms (e.g., email, SMS). - Integration with existing logging frameworks. - User role management for accessing different levels of information.