🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant obfuscation techniques, which could indicate attempts to hide malicious activities. Additionally, the lack of detailed metadata raises concerns about its legitimacy.

High obfuscation risk
Minimal package metadata

Per-check LLM notes

Network: No network calls detected, which is normal unless the package's functionality requires external API interactions.
Shell: No shell execution patterns detected, indicating the package does not execute system commands, which is safe.
Obfuscation: The presence of base64 and rot13 decoding suggests potential obfuscation practices, which could be used for hiding code or data.
Credentials: No clear patterns indicative of credential harvesting were found.
Metadata: The package appears to be newly created with minimal activity and metadata, raising suspicion but not conclusive evidence of malintent.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

t) % 4) decoded_b64 = base64.b64decode(padded_text).decode('utf-8') if decoded_b64 and deco
try: decoded_rot13 = codecs.decode(text, 'rot_13') if decoded_rot13.isprintable(): resul

✓ 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 "Nala Goodman" 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 NGKRIP

Create a fully-functional mini-application in Python that utilizes the 'NGKRIP' package to facilitate encoding and decoding challenges typical in Capture The Flag (CTF) competitions. Your application should serve as a versatile tool for CTF participants to practice and enhance their skills in cryptography and problem-solving.

Steps to create the application:
1. Install the NGKRIP package using pip if it's not already installed.
2. Design a simple GUI interface using a library such as Tkinter, allowing users to input their text or data.
3. Implement at least three different encoding/decoding methods available in the NGKRIP package, such as Caesar Cipher, Base64, and Hexadecimal encoding.
4. Add functionality for users to select which method they want to apply to their input text/data.
5. Ensure the application provides clear output after processing the user's input.
6. Include error handling to manage invalid inputs gracefully.
7. Document your code thoroughly, explaining how each part of the application works, especially where NGKRIP functions are utilized.
8. Test the application with various inputs to ensure reliability and accuracy.

Suggested Features:
- A dropdown menu for selecting the type of encoding/decoding.
- A text area for inputting the text/data.
- A button to trigger the encode/decode process.
- A display area to show the result.
- Clear instructions and feedback messages for the user.

How NGKRIP is Utilized:
- Use NGKRIP's encoding and decoding functions to perform the transformations on user input.
- Explore the documentation of NGKRIP to understand how to use its specific functions for different types of encoding/decoding schemes.
- Ensure that the implementation correctly leverages NGKRIP's capabilities to provide accurate results.