🤖 AI Analysis

Final verdict: SAFE

The package OrderPulse v0.2.57 appears to be safe based on the provided analysis notes. While there are some concerns regarding metadata, such as an anonymous author and low activity, these alone do not constitute evidence of malicious intent or a supply-chain attack.

Low risk scores across all technical categories.
No clear signs of malicious activities.
Metadata concerns exist but are insufficient to conclude malice.

Per-check LLM notes

Network: No network calls suggest normal behavior unless the package's functionality inherently requires them.
Shell: No shell executions indicate that the package does not execute external commands, which is generally safe.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
Metadata: The package shows some red flags such as an anonymous author and low activity in the git repository, but no clear signs of malicious intent.

🔬 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 score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ 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 OrderPulse

Your task is to develop a real-time cryptocurrency trading analysis tool using the Python package 'OrderPulse'. This tool will parse live exchange feeds from popular cryptocurrency exchanges and provide insightful order flow analytics to traders. The application should be designed to run continuously, processing incoming data streams and updating analytics in real-time. Here’s a detailed breakdown of the project requirements and features:

1. **Setup**: Begin by installing the necessary dependencies, including OrderPulse and any other required Python libraries such as pandas for data manipulation and matplotlib for visualization.
2. **Data Ingestion**: Use OrderPulse to connect to a live cryptocurrency exchange feed. Your application should be able to handle multiple exchanges if possible.
3. **Real-Time Processing**: Implement real-time processing logic within your application to analyze the incoming order flow data. This includes calculating key metrics like volume, price changes, and order imbalance.
4. **Analytics Dashboard**: Develop a simple yet effective dashboard that visualizes the processed data. This dashboard should include charts and graphs that update in real-time based on the incoming data.
5. **Alert System**: Integrate an alert system that notifies users via email or SMS when specific conditions are met, such as significant price movements or unusual order flow patterns.
6. **User Interface**: Although not mandatory, consider developing a basic web interface using Flask or Django to allow users to interact with the application more easily.
7. **Documentation**: Ensure that your code is well-documented, explaining how each component works and how it interacts with the OrderPulse library.

By the end of this project, you will have a fully functional real-time cryptocurrency trading analysis tool that leverages the high-performance capabilities of OrderPulse to deliver actionable insights to traders.