🤖 AI Analysis

Final verdict: SUSPICIOUS

The package ai-fde v0.0.1 has minimal risks associated with network calls, shell execution, and obfuscation. However, the metadata suggests it might be newly created with little activity, which raises suspicion.

Metadata risk score of 4 out of 10 due to recent creation and low activity.
No other significant risks identified.

Per-check LLM notes

Network: No network calls detected, which is normal if the package does not require external communications.
Shell: No shell execution detected, indicating the package does not execute system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
Credentials: No credential harvesting patterns detected, suggesting legitimate usage without secret theft concerns.
Metadata: The package shows signs of being newly created with minimal activity and metadata, raising some suspicion but not definitive evidence of malice.

📦 Package Quality Overall: Low (1.2/10)

○ Low Test Suite 1.0

No test suite detected

No test files or test-runner configuration detected

○ Low Documentation 1.0

No documentation detected

No documentation URL, doc files, or meaningful description found

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

○ Low Type Annotations 1.0

No type annotations detected

No type annotations, py.typed marker, or stub files detected

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "Victor Sanh" 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 ai-fde

Create a Python-based mini-application named 'SecureNote' which allows users to encrypt and decrypt notes using symmetric key cryptography. The application should utilize the 'ai-fde' package, which is assumed to provide functionalities for full disk encryption but will be creatively adapted for file-level encryption of text notes in this scenario.

The application should include the following features:
1. User Registration: Users should be able to register and log in to their accounts.
2. Note Creation: Once logged in, users can create new notes. Each note should be automatically encrypted using a secure key managed by the 'ai-fde' package.
3. Note Encryption: When a user creates or edits a note, it should be encrypted on-the-fly using the 'ai-fde' package.
4. Note Decryption: Upon retrieval, notes should be decrypted seamlessly so that the user can read them without manual intervention.
5. Key Management: The application should securely manage encryption keys, ensuring they are stored safely and not exposed to unauthorized access.
6. Backup and Restore: Users should have the option to back up their encrypted notes and restore them from a backup location.
7. User Interface: Develop a simple command-line interface for interaction. Alternatively, if time permits, consider developing a basic GUI using a Python library such as Tkinter.

The 'ai-fde' package is expected to provide functions for encryption and decryption of files, which you will adapt for text notes. Ensure your implementation demonstrates a good understanding of cryptographic principles and best practices.