anteumbra

v0.0.1.dev0 suspicious
5.0
Medium Risk

Placeholder for Anteumbra security platform

πŸ€– AI Analysis

Final verdict: SUSPICIOUS

The package has a low risk score for direct threats but shows signs of being newly created with poor metadata quality, raising concerns about its legitimacy.

  • Low metadata quality
  • Newly created package
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no immediate risk of unauthorized system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of being newly created and having low metadata quality, which could indicate potential risk.

πŸ“¦ Package Quality Overall: Low (1.2/10)

β—‹ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
β—‹ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
β—‹ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
β—‹ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
β—‹ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked β€” contributor count unavailable

πŸ”¬ Heuristic Checks

βœ“ Outbound Network Calls

No suspicious network call patterns found

βœ“ Code Obfuscation

No obfuscation patterns detected

βœ“ Shell / Subprocess Execution

No shell execution patterns detected

βœ“ Credential Harvesting

No credential harvesting patterns detected

βœ“ Typosquatting

No typosquatting candidates detected

βœ“ Registered Email Domain

No author email provided

βœ“ Suspicious Page Links

All external links appear legitimate

βœ“ 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 β€” brand new package
  • Author "SxyLao1" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
βœ“ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

πŸ’‘ AI App Starter Prompt

Use this prompt to build a project with anteumbra
Your task is to develop a small, but fully-functional cybersecurity monitoring tool using the 'anteumbra' Python package. This tool will serve as a basic intrusion detection system (IDS) aimed at monitoring network traffic for suspicious activities indicative of potential cyber threats. Here’s a step-by-step guide on what your application should achieve and how you can utilize the 'anteumbra' package effectively:

1. **Project Setup**: Start by setting up your development environment. Ensure you have Python installed along with the necessary packages like 'anteumbra'. Use pip to install any additional libraries you might need for data handling and visualization.

2. **Data Collection**: Your IDS needs to collect network traffic data. Decide whether to use simulated data or real-time network traffic capture. If using real-time, consider integrating with tools like Wireshark or Python's Scapy for packet capture.

3. **Feature Extraction**: Utilize the 'anteumbra' package to extract key features from the collected network traffic data. These features could include packet sizes, frequency of connections, unusual port usage, etc. Document how each feature contributes to identifying potential threats.

4. **Threat Detection Algorithm**: Develop a simple algorithm within your application that leverages the extracted features to detect anomalies or suspicious patterns. This could involve statistical analysis, anomaly detection techniques, or even machine learning models if you're comfortable with them. Explain how 'anteumbra' assists in implementing these detection methods.

5. **Alert System**: Implement an alert system that triggers notifications when potential threats are detected. Consider sending alerts via email, SMS, or logging them into a file for review. Discuss how 'anteumbra' can be integrated into this alert mechanism.

6. **User Interface**: Create a simple user interface (UI) where users can interact with your IDS. This UI should allow users to start/stop monitoring, view current status, and access logs or alerts. Think about how 'anteumbra' could enhance the functionality or design of this UI.

7. **Documentation & Testing**: Finally, write comprehensive documentation explaining how to set up and use your IDS. Include instructions for testing the system with different types of network traffic to ensure its effectiveness.

In your implementation, focus on showcasing the capabilities of the 'anteumbra' package and how it streamlines the process of developing a robust cybersecurity solution. Highlight any unique features or functionalities provided by 'anteumbra' that make your IDS stand out.

πŸ’¬ Discussion Feed

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