apytypes

v0.5.1 suspicious
4.0
Medium Risk

Python package for custom fixed-point and floating-point formats

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits signs of potential obfuscation techniques that could be used for malicious purposes, while other risks remain low.

  • Unusual use of bit manipulation and eval function suggesting possible obfuscation.
  • Incomplete author information and potentially inactive account.
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external API interactions.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command injection or privilege escalation.
  • Obfuscation: The code patterns suggest potential obfuscation through unusual usage of bit manipulation and eval function, which could be used for malicious purposes.
  • Credentials: No clear evidence of credential harvesting detected.
  • Metadata: The author's information is incomplete and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (7.8/10)

✦ High Test Suite 9.0

Test suite present — 23 test file(s) found

  • Test runner config found: pyproject.toml
  • 23 test file(s) detected (e.g. test_fp8_mul.py)
✦ High Documentation 9.0

Well-documented package

  • Documentation URL: "Documentation" -> https://apytypes.org/
  • 8 documentation file(s) (e.g. innerproductscale.py)
  • Detailed PyPI description (1691 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

  • Type checker (mypy / pyright / pytype) referenced in project
  • 216 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 6 unique contributor(s) across 100 commits in apytypes/apytypes
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 10.0

Found 5 obfuscation pattern(s)

  • bits=1, frac_bits=3, overflow=eval(mode)) aiqfx = aifx.cast(int_bits=1, frac_bits=3, overfl
  • bits=1, frac_bits=3, overflow=eval(mode)) ax.set_aspect("equal") ax.plot((-3, 2.875), (
  • =4, frac_bits=0, quantization=eval(q)) aiqfx = aifx.cast(int_bits=4, frac_bits=0, quantizat
  • =4, frac_bits=0, quantization=eval(q)) ahqfx = ahfx.cast(int_bits=4, frac_bits=0, quantizat
  • =4, frac_bits=0, quantization=eval(q)) ax = axs[2 * (i // 3), i % 3] ax.set_aspect("equ
✓ 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: liu.se>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository apytypes/apytypes appears legitimate

⚠ 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 apytypes 
Create a financial calculator application named 'FixedFloatFinance' using Python, which leverages the 'apytypes' package for precise arithmetic operations with custom fixed-point and floating-point formats. This tool will be particularly useful for scenarios requiring high precision, such as financial calculations where rounding errors can have significant impacts. The application should include the following functionalities:

1. **Interest Calculation**: Implement a feature that calculates simple and compound interest. Users should be able to input principal amount, rate of interest, and time period. The application should use apytypes to handle these values with custom precision to avoid common floating-point inaccuracies.

2. **Currency Conversion**: Add a currency converter that supports at least five major world currencies (USD, EUR, GBP, JPY, CHF). Utilize apytypes to ensure that exchange rates and converted amounts are handled with the highest precision possible.

3. **Budget Planner**: Include a basic budget planner that allows users to input monthly income and expenses across various categories (rent, groceries, entertainment, etc.). Use apytypes to manage these financial figures accurately, especially when calculating remaining balance after expenses.

4. **Financial Goals Tracker**: Allow users to set financial goals (e.g., saving for a car, vacation, or education). Track progress towards these goals based on monthly contributions and display it graphically using matplotlib or similar plotting library. Ensure that all calculations involved in tracking progress are performed using apytypes for accuracy.

5. **User Interface**: Develop a user-friendly command-line interface for interacting with the application. Each feature should be accessible through simple commands, making it easy for users to navigate and utilize the tool effectively.

In each of these functionalities, the 'apytypes' package should be utilized to define custom numeric types that enforce specific precision requirements. For example, you might create a custom type for currency values that ensures two decimal places of precision. Additionally, demonstrate how apytypes can help in avoiding common pitfalls associated with floating-point arithmetic in financial applications.

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