AI Analysis
The package shows elevated risks particularly in credential handling and metadata, suggesting potential misuse. However, without concrete evidence of malicious activity, it cannot be conclusively classified as malicious.
- Elevated credential risk
- Single-author with missing repository
Per-check LLM notes
- Network: The use of an HTTP client suggests the package may be designed to fetch resources from the internet, which is not inherently suspicious but should be reviewed for its purpose.
- Shell: No shell execution patterns detected, indicating no immediate risk related to command execution.
- Obfuscation: No clear signs of obfuscation patterns being used maliciously.
- Credentials: Detected patterns suggest potential credential harvesting attempts via file access and URL manipulations.
- Metadata: The author has only one package and the git repository is not found, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Medium (5.6/10)
Test suite present — 27 test file(s) found
Test runner config found: conftest.pyTest runner config found: pyproject.toml27 test file(s) detected (e.g. conftest.py)
Some documentation present
Documentation URL: "Documentation" -> https://github.com/Bigred97/ato-mcp#readmeDetailed PyPI description (11827 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
Classifier: Typing :: Typed114 type-annotated function signatures detected in source
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
Found 1 network call pattern(s)
Cache() self._http = httpx.AsyncClient( timeout=DEFAULT_TIMEOUT, transport=
No obfuscation patterns detected
No shell execution patterns detected
Found 5 credential access pattern(s)
: "Right One", "url": "file:///etc/passwd"}], }, }) ) async with ATOClienscript>", "../../etc/passwd", "../%2e%2e/passwd", "%00", "\x00postcode"]: r = aarametrize("bad_id", [ "../etc/passwd", "CORP/TRANSPARENCY", "CORP%20TRANSPARENCY", "url in ( "file:///etc/passwd", "javascript:alert(1)", "data:textit server.describe_dataset("../etc/passwd") @pytest.mark.asyncio async def test_describe_dataset_em
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Repository not found (deleted or private)
Repository not found (deleted or private)
1 maintainer concern(s) found
Author "Harry Vass" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a web-based dashboard using Flask that integrates with the 'ato-mcp' Python package to provide real-time access to Australian taxation data. This dashboard will serve as a tool for financial analysts, researchers, and policymakers to quickly gather insights into various aspects of Australian taxation, including personal tax by postcode, company tax by industry, corporate tax transparency, GST collections, super contributions, and the ACNC charity register. ### Steps to Build the Application: 1. **Setup Environment**: Install Python, Flask, and the 'ato-mcp' package. 2. **Design Database**: Create a database schema to store and manage the data fetched from the 'ato-mcp' package. Consider using SQLite for simplicity. 3. **API Integration**: Develop API endpoints using Flask that fetch data from the 'ato-mcp' package and store it in the database. 4. **Frontend Development**: Design a user-friendly frontend using HTML, CSS, and JavaScript frameworks like Bootstrap or React.js to display the fetched data in charts, tables, and graphs. 5. **Data Visualization**: Implement visualizations such as line charts for time-series data (e.g., GST collections over years), bar charts for comparisons (e.g., personal tax by postcode), and pie charts for proportions (e.g., super contributions). 6. **User Authentication**: Add basic authentication to secure the dashboard, allowing only authorized users to access the sensitive tax information. 7. **Testing and Deployment**: Test the application thoroughly and deploy it on a cloud platform like Heroku or AWS. ### Suggested Features: - **Interactive Filters**: Allow users to filter data based on specific criteria such as year, industry, or postcode. - **Export Functionality**: Provide options to export data in CSV or PDF formats. - **Real-Time Updates**: Fetch and update data periodically to ensure the dashboard reflects the most current statistics. - **Detailed Reports**: Generate detailed reports based on user queries. - **Customizable Views**: Enable users to customize their view of the data, choosing which metrics to display and how they want them presented. ### Utilizing 'ato-mcp': - Use the 'ato-mcp' package to interact with the Australian Taxation Office's APIs, fetching detailed statistics on personal taxes, company taxes, GST collections, etc. - Store these statistics in your database for quick retrieval and analysis. - Use the fetched data to populate your charts and tables dynamically. - Ensure you handle any rate limits and error responses appropriately to maintain a smooth user experience.
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