acgs-lite

v2.10.1 suspicious
4.0
Medium Risk

Runtime governance for AI agents — deterministic enforcement before execution, MACI role separation, tamper-evident audit trails, and operator intervention workflows.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate risk due to its network activity and the lack of detailed maintainer information.

  • Network calls with unclear purpose
  • Maintainer has minimal public presence
Per-check LLM notes
  • Network: The package makes network calls which could potentially be used for data exchange, but without further context, it's hard to determine if this is intended functionality or malicious behavior.
  • Shell: No shell execution patterns detected, suggesting the package does not attempt to execute arbitrary commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating safe handling of secrets and credentials.
  • Metadata: The maintainer's author name is missing and they appear to have only one package, which may indicate a less established or potentially suspicious account.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • igest}" request = urllib.request.Request( self._url, data=bod
  • ) with urllib.request.urlopen(request, timeout=5): # nosec B310 — scheme validate
✓ 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: acgs.dev>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository dislovelhl/acgs-lite appears legitimate

⚠ 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 acgs-lite 
Create a mini-application named 'AI Agent Supervisor' using Python's 'acgs-lite' package. This application will serve as a runtime governance tool for managing AI agents in a secure and transparent manner. The goal of this project is to demonstrate how 'acgs-lite' can be utilized to enforce deterministic policies, ensure role separation through Mandatory Access Control Interface (MACI), maintain tamper-evident audit logs, and facilitate operator intervention when necessary.

Step 1: Define the roles and responsibilities within your application. Consider having three main roles: Operator, Auditor, and Agent. Each role will have distinct permissions and responsibilities based on the MACI framework provided by 'acgs-lite'.

Step 2: Implement a mechanism for policy enforcement before any action is taken by the AI agents. Use 'acgs-lite' to define these policies and ensure they are strictly followed. For example, an agent should not be allowed to perform certain actions without explicit permission from an Operator.

Step 3: Integrate 'acgs-lite' to manage role separation effectively. Ensure that each role can only perform actions that are defined by their role definitions. For instance, an Auditor should only be able to view audit logs and not alter them.

Step 4: Utilize 'acgs-lite' to create tamper-evident audit trails. Every action performed by the AI agents, Operators, or Auditors should be logged securely. These logs should be immutable and easily accessible for review.

Step 5: Develop an operator intervention workflow. When certain conditions are met (e.g., policy violations, system errors), operators should be able to intervene and take corrective actions. Use 'acgs-lite' to handle these interventions seamlessly.

Suggested Features:
- Role-based access control with clear separation of duties.
- Real-time monitoring of agent activities.
- Detailed audit logs that are tamper-proof.
- A user-friendly interface for operators to manage policies and intervene.
- Automated alerts for policy violations or critical issues.

This project aims to showcase the capabilities of 'acgs-lite' in providing robust governance for AI agents, ensuring security, accountability, and transparency.