AI Analysis
Final verdict: SUSPICIOUS
The package DemonzJwt v1.1.0 has a moderate risk score due to its low metadata quality, which raises suspicion about its legitimacy and maintenance efforts.
- Metadata risk indicates low effort in package creation
- Lack of maintainer history and author details
Per-check LLM notes
- Network: Fetching versions from a remote server is common for packages that need to check for updates or validate compatibility with certain libraries.
- Shell: No shell execution patterns detected, which is normal and expected.
- Obfuscation: No obfuscation patterns detected, suggesting normal code readability and no hidden malicious intentions.
- Credentials: No credential harvesting patterns detected, indicating the package does not appear to be involved in stealing secrets or credentials.
- Metadata: The package shows signs of low effort and could be suspicious due to lack of maintainer history and author details.
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
ain/versions.json" SESSION = requests.Session() # ==================== VERSION FETCH ====================
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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 8.0
4 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with DemonzJwt
Your task is to develop a simple yet functional user authentication system using Python and the 'DemonzJwt' package. This system will allow users to register, log in, and maintain their session securely through JWT tokens. Here's a detailed breakdown of the steps and features you need to implement: 1. **User Registration**: Create a registration form where users can sign up with their email address and password. Upon successful registration, the system should generate a JWT token for the user. 2. **Login Functionality**: Implement a login feature where users can enter their credentials. After successful verification, the system should return a JWT token to the user. 3. **Session Management**: Utilize the JWT token to manage user sessions. Ensure that each request from the authenticated user includes the JWT token to validate their identity. 4. **Logout Feature**: Provide a logout option that invalidates the current JWT token, effectively ending the user's session. 5. **Security Measures**: Include basic security measures such as hashing passwords before storing them in the database and ensuring that all communication is over HTTPS. 6. **Error Handling**: Properly handle errors such as incorrect login details, expired tokens, and unauthorized access attempts. 7. **Documentation**: Write clear documentation explaining how to use the authentication system and how 'DemonzJwt' is integrated into it. In your implementation, ensure that 'DemonzJwt' is used for generating, validating, and managing JWT tokens. This will be crucial for maintaining secure user sessions. Additionally, consider adding features like token expiration and refresh mechanisms to enhance the user experience and security.