SigMF

v1.11.1 safe
3.0
Low Risk

Easily interact with Signal Metadata Format (SigMF) recordings.

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity or risks associated with network calls, shell executions, obfuscations, or credential harvesting. However, the metadata risk due to the maintainer's new or inactive account and lack of proper author details slightly increases the uncertainty.

  • No network calls
  • No shell execution patterns
  • No obfuscation
  • No credential harvesting patterns
  • Metadata risk due to maintainer's account status
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network interaction for its functionality.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command injection or similar attacks.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of unauthorized access.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, which may indicate a lower level of commitment or oversight.

🔬 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

Repository sigmf/SigMF appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • 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 SigMF 
Create a Python-based mini-application that processes and analyzes radio frequency (RF) signals using the SigMF package. Your application should be capable of reading, writing, and manipulating SigMF metadata files which store information about RF signal recordings. Here's a detailed breakdown of the project requirements:

1. **Signal Importation**: Allow users to import SigMF-compliant files containing RF signal data. The application should display basic metadata such as sample rate, frequency range, and signal type.
2. **Signal Visualization**: Implement a feature to visualize the imported signal data in real-time or from stored data. This could include plotting the signal in time-domain or frequency-domain views.
3. **Signal Analysis**: Provide tools for analyzing the imported signal data. This could include calculating signal power, identifying peaks, and detecting anomalies within the signal.
4. **Metadata Manipulation**: Enable users to modify metadata associated with the signal files, such as adding annotations, adjusting timestamps, or changing signal parameters.
5. **Export Functionality**: Allow users to export processed or modified signal data back into a new SigMF file, ensuring all changes to metadata are preserved.
6. **User Interface**: Develop a simple yet intuitive graphical user interface (GUI) using libraries like PyQt or Tkinter to facilitate interaction with the application.

In your implementation, make sure to utilize the core functionalities of the SigMF package to handle the loading, saving, and manipulation of SigMF metadata files efficiently. Additionally, explore integrating external Python libraries for advanced signal processing tasks to enhance the capabilities of your application.