alphameta

v2.4.4 suspicious
6.0
Medium Risk

IBKR trading + SEC research API gateway

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks in terms of network calls, shell execution, and obfuscation, but the presence of a suspicious non-HTTPS link and lack of repository metadata suggest potential issues with its origin and trustworthiness.

  • Suspicious non-HTTPS link
  • Lack of repository metadata
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
  • 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: Suspicious non-HTTPS link and lack of repository indicate potential risk.

📦 Package Quality Overall: Low (2.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (3585 chars)
○ 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

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 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

Email domain looks legitimate: intelliscale.com

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://127.0.0.1:18080/api/v1/execute
⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author "GAO KE" 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 alphameta 
Create a financial analysis tool using Python's 'alphameta' package which integrates Interactive Brokers (IBKR) trading capabilities with SEC research data. This tool will allow users to retrieve real-time stock prices, historical market data, and company filings from the SEC. Additionally, it should provide functionality to analyze these data points, such as calculating moving averages, identifying trends, and generating alerts based on user-defined criteria.

Steps to create the application:
1. Set up the environment: Install Python and necessary packages including 'alphameta'. Ensure you have the required credentials for accessing IBKR and SEC APIs.
2. Design the user interface: Develop a simple yet intuitive UI where users can input ticker symbols, select timeframes, and set alert conditions.
3. Implement data retrieval: Use 'alphameta' to fetch real-time and historical stock price data from IBKR. Similarly, use the package to access relevant company filings and financial reports from the SEC.
4. Data processing and analysis: Incorporate algorithms to calculate technical indicators like moving averages and relative strength index (RSI). Also, develop methods to parse and summarize key information from SEC filings.
5. Alert system: Allow users to set thresholds for stock price movements or changes in company filings. When these conditions are met, the system should send notifications via email or SMS.
6. Testing and validation: Test the application thoroughly to ensure accuracy and reliability of the data retrieved and processed. Validate the alert system to confirm it functions correctly under various scenarios.
7. Deployment: Once tested successfully, deploy the application so that it can be accessed online or through a mobile app.

Suggested Features:
- Real-time stock price updates
- Historical data visualization
- Technical analysis tools (moving averages, RSI)
- SEC filing summaries
- Customizable alerts based on price movement or filing changes
- User-friendly dashboard for managing settings and viewing results

💬 Discussion Feed

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