apra-mcp

v0.8.22 suspicious
7.0
High Risk

MCP server for Australian Prudential Regulation Authority statistics. Plain-English access to bank capital ratios, superannuation fund-level data, and life + general insurance — every prudentially-regulated entity in Australia, every quarter, with auto-discovery and a CC-BY 3.0 AU attribution contract.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows significant credential risk and some metadata risk, suggesting potential malicious intent. However, it lacks clear evidence of network exploitation or direct harm.

  • High credential risk
  • Unknown author and missing git repository
Per-check LLM notes
  • Network: The use of AsyncClient with a timeout suggests normal HTTP request handling, likely for fetching data from an API or similar service.
  • Shell: No shell execution patterns detected, indicating no immediate risk associated with unauthorized system command execution.
  • Obfuscation: No signs of obfuscation patterns detected.
  • Credentials: Potential credential harvesting attempts observed with references to accessing sensitive files.
  • Metadata: The author has only one package and the git repository is not found, which may indicate potential risk.

📦 Package Quality Overall: Medium (5.6/10)

✦ High Test Suite 9.0

Test suite present — 17 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 17 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/Bigred97/apra-mcp#readme
  • Detailed PyPI description (8474 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 139 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • Cache() self._http = httpx.AsyncClient( timeout=DEFAULT_TIMEOUT, transport=
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 7.5

Found 3 credential access pattern(s)

  • url in ( "file:///etc/passwd", "javascript:alert(1)", "data:text
  • server.describe_dataset("../../etc/passwd") @pytest.mark.asyncio async def test_get_data_filters_wi
  • it server.describe_dataset("../etc/passwd") @pytest.mark.asyncio async def test_describe_dataset_em
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Harry Vass" 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 apra-mcp 
Create a financial analysis tool using Python's 'apra-mcp' package that provides users with detailed insights into Australian bank capital ratios, superannuation funds, and insurance data. This tool should allow users to select specific quarters and entities to analyze. The application should have the following features:

1. **Dashboard Interface**: A simple dashboard where users can input the entity name and select the quarter for which they want data.
2. **Data Retrieval**: Utilize 'apra-mcp' to fetch the required data from the Australian Prudential Regulation Authority's database. Ensure that the data retrieval process is automated and handles any potential errors gracefully.
3. **Data Visualization**: Implement basic charts (line graphs, bar charts) to visualize trends over time for selected entities. For example, display changes in bank capital ratios or growth in superannuation funds.
4. **Export Functionality**: Allow users to export the analyzed data and visualizations as CSV files and PNG images respectively.
5. **Detailed Report Generation**: Generate a PDF report summarizing key metrics and findings for the selected entities. Include relevant charts and tables in the report.
6. **User Authentication**: Implement a basic login system to ensure that only registered users can access the tool. Store user credentials securely.
7. **API Integration**: Provide an API endpoint for developers to integrate the data retrieval functionality of 'apra-mcp' into their own applications.

The goal of this project is to provide a comprehensive yet easy-to-use tool for analyzing financial health indicators of various Australian financial institutions. By leveraging the power of 'apra-mcp', users will gain valuable insights into the performance of banks, superannuation funds, and insurance companies.

💬 Discussion Feed

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