AI Analysis
Final verdict: SAFE
The package is deemed safe with minimal risks identified. The network, shell, obfuscation, and credential risks are all low.
- Low network risk
- No shell execution detected
- No obfuscation detected
- No credential harvesting detected
Per-check LLM notes
- Network: Network calls are common in packages that interact with APIs or external services, but should be reviewed for legitimacy and security practices.
- Shell: No shell execution patterns detected, which is expected and safe.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which could indicate a new or less active account.
Package Quality Overall: Low (4.6/10)
β Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
β Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (5169 chars)
β Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
β Medium
Type Annotations
7.0
Partial type annotation coverage
Type checker (mypy / pyright / pytype) referenced in project50 type-annotated function signatures detected in source
β¦ High
Multiple Contributors
8.0
Active multi-contributor project
4 unique contributor(s) across 100 commits in OpenRailAssociation/authentik-user-managerSmall but multi-author team (3β4 contributors)
Heuristic Checks
Outbound Network Calls
score 7.5
Found 5 network call pattern(s)
"GET": response = requests.get(url, headers=self.headers, params=data, timeout=10)": response = requests.post(url, headers=self.headers, json=data, timeout=10)": response = requests.patch(url, headers=self.headers, json=data, timeout=10)": response = requests.delete(url, headers=self.headers, timeout=10) else:nd the email with smtplib.SMTP(self.smtp_server, int(self.smtp_port)) as server:
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: deutschebahn.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository OpenRailAssociation/authentik-user-manager appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Max Mehl" 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 authentik-user-manager
Create a user management utility using the 'authentik-user-manager' Python package. This utility will allow administrators to manage users of an Authentik instance through YAML configuration files, making it easier to add, modify, or delete users without directly interacting with the Authentik API. Hereβs a step-by-step guide on what your application should accomplish: 1. **Setup**: Start by setting up a virtual environment for your project and installing the 'authentik-user-manager' package. Ensure you have a basic understanding of YAML files as these will be used for user configurations. 2. **Configuration File**: Design a sample YAML file that contains user details such as username, password, email, and any other necessary attributes like roles or permissions. This file will serve as the basis for adding or updating users. 3. **Command Line Interface (CLI)**: Develop a CLI tool where administrators can run commands to interact with the utility. The commands should include options to add new users, update existing ones, delete users, and display all current users managed by the utility. 4. **User Management Functions**: Implement functions within the utility to handle each of the CLI commands. For example, when adding a new user, the utility should read the provided YAML file, validate the data, and then use the 'authentik-user-manager' package to create the user in Authentik. 5. **Error Handling and Validation**: Ensure robust error handling and validation for the user data. This includes checking if the YAML file is correctly formatted, if the required fields are present, and if the actions being performed (add, update, delete) are valid and possible within Authentik. 6. **Security Considerations**: Since the utility will handle sensitive information like passwords, ensure that these are securely stored in the YAML files and transmitted safely during operations. Use encryption methods where necessary. 7. **Documentation**: Provide comprehensive documentation on how to set up the utility, use the CLI commands, and manage users effectively. Include examples and best practices for using the utility securely. 8. **Testing**: Write tests to verify that the utility works as expected under various scenarios, including edge cases like attempting to add a duplicate user or delete a non-existent one. 9. **Deployment**: Finally, consider how the utility could be deployed in different environments. Think about packaging it into a distributable format such as a Docker container for easy deployment. Suggested Features: - Support for importing multiple users from a single YAML file. - Option to generate random secure passwords for new users. - Integration with version control systems for managing changes to user configurations over time. - Logging of all operations for audit purposes.
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