agentsentinel-crewai

v0.1.0 suspicious
4.0
Medium Risk

Security scanner for CrewAI multi-agent workflows — powered by AgentSentinel on SingularityNET

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package presents a low risk for common threats like obfuscation and credential harvesting but has a moderate risk due to incomplete metadata.

  • Low obfuscation risk
  • Low credential risk
  • Moderate metadata risk due to missing maintainer history and git repository
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity related to secret theft.
  • Metadata: The package shows signs of potential malicious activity due to the lack of maintainer history and a non-existent git repository.

📦 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/neu
  • Detailed PyPI description (3537 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

  • 5 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 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 agentsentinel-crewai 
Create a security dashboard application named 'CrewGuard' using Python, which leverages the 'agentsentinel-crewai' package to monitor and secure CrewAI multi-agent workflows. This application will serve as a comprehensive tool for developers and security analysts to oversee the health and security of their AI workflows. Here’s a step-by-step guide on how to build it:

1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed, then install necessary packages including 'agentsentinel-crewai'. Use pip to install any additional dependencies like Flask for the web interface.

2. **Data Collection**: Utilize 'agentsentinel-crewai' to collect real-time data about the status and vulnerabilities of CrewAI workflows. Implement functions to periodically fetch this data from the API provided by the package.

3. **Dashboard Development**: Develop a simple yet effective web-based dashboard using Flask. This dashboard should display key information such as workflow statuses, recent activity logs, and detected vulnerabilities. Each piece of information should be clearly presented and easy to understand.

4. **Alert System**: Integrate an alert system within the application. Whenever 'agentsentinel-crewai' detects a potential security threat, the application should notify the user via email or SMS. Users should also be able to configure thresholds for alerts based on severity levels.

5. **User Management**: Incorporate basic user management functionalities. Allow users to register, log in, and manage their access rights. Ensure that only authorized personnel can view sensitive information and perform actions on the system.

6. **Custom Reports**: Enable users to generate custom reports based on their needs. These reports should summarize the security status of their workflows over a specified period, highlighting any trends or patterns.

7. **Testing and Deployment**: Before deploying the application, thoroughly test all components to ensure they work seamlessly together. Once satisfied with the functionality, deploy the application either locally or to a cloud service provider.

By following these steps, you'll create a powerful security monitoring tool that not only utilizes 'agentsentinel-crewai' effectively but also provides valuable insights into the security posture of CrewAI workflows.