authsec-autogen

v0.1.0 suspicious
7.0
High Risk

AuthSec integration for AutoGen — secure AI delegation token retrieval

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate network risk due to its use of GET and POST requests, which could potentially be exploited for data exfiltration. Additionally, the metadata risk score is high due to the absence of maintainer history and a non-existent repository, raising concerns about its legitimacy.

  • Moderate network risk from HTTP request usage
  • High metadata risk due to lack of maintainer history and non-existent repository
Per-check LLM notes
  • Network: The use of GET and POST requests is common but may indicate potential data exfiltration if URLs are controlled by external factors.
  • 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 package is suspicious due to lack of maintainer history and a non-existent repository, indicating potential malicious intent.

📦 Package Quality Overall: Low (2.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (8415 chars)
○ 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

  • 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 score 3.0

Found 2 network call pattern(s)

  • ": res = requests.get(url, headers=headers, timeout=5) else:
  • e: res = requests.post(url, headers=headers, json=payload, timeout=5)
✓ 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: authnull.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 authsec-autogen 
Develop a secure AI assistant manager using the 'authsec-autogen' package. This application will allow users to manage and delegate secure tokens for AI assistants, ensuring that each assistant operates within predefined security constraints. Here’s a step-by-step guide on how to build this application:

1. **Setup Project Environment**: Start by setting up your Python environment. Ensure you have the latest version of Python installed. Use virtual environments to isolate dependencies.
2. **Install Required Packages**: Install 'authsec-autogen' along with other necessary packages such as Flask for web serving, SQLAlchemy for database management, and any additional libraries needed for authentication and authorization.
3. **Design Database Schema**: Plan out the database schema to store user information, assistant details, and token data securely. Consider using SQLAlchemy ORM for easier database interactions.
4. **Implement User Authentication**: Set up user registration, login, and logout functionalities. Utilize Flask-Login for session management and ensure all sensitive data is encrypted during transmission.
5. **Integrate AuthSec-AutoGen**: Use 'authsec-autogen' to handle the generation and management of secure tokens for AI assistants. This includes retrieving tokens from AuthSec service and securely storing them within your application.
6. **Create Assistant Management Features**: Allow users to create, delete, and modify their AI assistants. Each assistant should have its own set of permissions and tokens managed through 'authsec-autogen'.
7. **Secure Token Delegation**: Implement a feature where users can delegate tokens to specific AI assistants for tasks, ensuring that these delegations are logged and auditable.
8. **Security Measures**: Incorporate robust security measures such as rate limiting, input validation, and protection against common web vulnerabilities like XSS and CSRF attacks.
9. **Testing**: Thoroughly test your application for both functionality and security. Use tools like Selenium for UI testing and OWASP ZAP for security audits.
10. **Documentation**: Write comprehensive documentation explaining how to use the application, including setup instructions and API references if applicable.

Suggested Features:
- Multi-factor authentication for added security.
- Role-based access control for managing different levels of permissions.
- A dashboard for monitoring assistant activities and token usage.
- Integration with popular AI services for seamless assistant creation.
- Detailed logging and alerting system for suspicious activities.

By following these steps and incorporating the suggested features, you will create a robust and secure AI assistant management tool that leverages the power of 'authsec-autogen' for token management.

💬 Discussion Feed

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