agentgovern

v0.1.0b13 suspicious
4.0
Medium Risk

Compliance-as-code middleware for agentic AI workflows.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has some legitimate features but raises concerns due to incomplete metadata and potential network interactions with unknown services.

  • Missing repository and author details
  • Potential network calls to unknown services
Per-check LLM notes
  • Network: Network calls are expected if the package interacts with external services, but further investigation is needed to confirm legitimacy.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The missing repository and author details raise concerns about the legitimacy of the package.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • try: with httpx.Client(headers=self._auth_headers(), timeout=5.0) as client:
  • actions}) async with httpx.AsyncClient(headers=self._auth_headers(), timeout=10.0) as client:
  • try: async with httpx.AsyncClient(headers=self._auth_headers(), timeout=10.0) as client:
  • }, } with httpx.Client( headers={"X-API-Key": self.api_key},
  • hable try: with httpx.Client(timeout=2.0) as client: resp = client.get(f"{_P
✓ 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: zirahn.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 4.0

2 maintainer concern(s) found

  • 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 agentgovern 
Develop a mini-application named 'ComplianceBot' that leverages the 'agentgovern' package to ensure compliance in AI-driven decision-making processes. This application will serve as a middleware solution for monitoring and enforcing compliance rules in real-time within various AI workflows. Here's a detailed breakdown of what your project should accomplish:

1. **Setup**: Begin by installing the 'agentgovern' package using pip. Ensure you have a clean Python environment set up.
2. **Define Compliance Rules**: Create a set of compliance rules that the AI agents must adhere to. These rules could include data privacy regulations, ethical guidelines, or specific business policies. Store these rules in a structured format accessible to the 'agentgovern' middleware.
3. **Integrate AI Agents**: Integrate at least two different types of AI agents into your application. For example, one might be responsible for processing customer support tickets, while another handles automated financial transactions. Each agent should have its own set of tasks and capabilities.
4. **Middleware Implementation**: Use 'agentgovern' to monitor the actions of these AI agents in real-time. Implement mechanisms for these agents to check against the defined compliance rules before executing any task. If a rule is violated, the action should be blocked or flagged for human review.
5. **Reporting Mechanism**: Develop a reporting system that logs all compliance checks and violations. This system should be able to generate periodic reports summarizing the compliance status and highlighting any issues.
6. **User Interface**: Create a simple web-based UI that allows users to view the compliance status, configure rules, and manage AI agents. The UI should provide clear visualizations and easy-to-understand summaries of compliance activities.
7. **Testing & Validation**: Test your application thoroughly to ensure that it accurately enforces compliance rules across all AI agents. Validate that the middleware correctly blocks non-compliant actions and that the reporting mechanism works as expected.
8. **Documentation**: Write comprehensive documentation explaining how to install, configure, and use 'ComplianceBot'. Include examples of compliance rules and scenarios where the application would intervene.

Your goal is to create a robust, user-friendly tool that demonstrates the power and flexibility of the 'agentgovern' package in ensuring compliance in dynamic AI environments.