Skip to content

Latest commit

 

History

History
152 lines (123 loc) · 9.06 KB

mitigations.md

File metadata and controls

152 lines (123 loc) · 9.06 KB

Mitigation Strategies Analysis for humanizr/humanizer

Mitigation Strategy: Input Validation (Pre-Humanization)

  • Description:

    1. Identify Input Points: Determine all points in your application where data is passed directly to Humanizer methods.
    2. Define Expected Input: For each input point, clearly define the expected data type, range, format, and any other relevant constraints that are relevant to the specific Humanizer method being called.
    3. Implement Validation Logic: Before calling the Humanizer method, implement validation checks based on the defined expectations.
    4. Handle Invalid Input: If the input fails validation, do not pass it to Humanizer. Handle the invalid input appropriately (error message, logging, default value, or exception).
    5. Example (C#): 
      string userInput = GetUserInput();

if (int.TryParse(userInput, out int number) && number >= 0 && number <= 1000)
{
    // Input is valid for .ToWords() within a reasonable range
    string humanized = number.ToWords();
    // ... use humanized ...
}
else
{
    // Handle invalid input
}

  • Threats Mitigated:

    • Unexpected Input Crashes (Severity: Medium): Prevents Humanizer from crashing or throwing exceptions due to unexpected input types or values for the specific method being called.
    • ReDoS (Regular Expression Denial of Service) (Severity: Low): Adds a layer of defense against crafted inputs that might trigger ReDoS within Humanizer's internal regexes (though this is unlikely).
    • Logic Errors (Severity: Low to Medium): Prevents unexpected application behavior caused by Humanizer processing data outside its intended range or format for the specific method.

  • Impact:

    • Unexpected Input Crashes: Risk reduced to near zero.
    • ReDoS: Risk remains extremely low, but this adds a small additional layer of protection.
    • Logic Errors: Risk significantly reduced, depending on the thoroughness of the validation.

  • Currently Implemented: (Example - Needs to be filled in based on your project)

    • Partially implemented in UserController for UpdateUserAge. Input is checked to be a number, but range is not validated specifically for Humanizer.
    • Implemented in ReportGenerator for date inputs, relevant to DateTime.Humanize().

  • Missing Implementation: (Example - Needs to be filled in based on your project)

    • Missing in ProductController where product quantities are handled. Input validation should be tailored to the expected input of the specific Humanizer method used.
    • Missing in AdminPanel for numerical settings.

Mitigation Strategy: Locale Awareness and Control (Humanizer-Specific)

  • Description:

    1. Identify Locale-Sensitive Methods: Determine all places where Humanizer methods that are locale-aware are used (e.g., ToWords, ToOrdinalWords, DateTime.Humanize, TimeSpan.Humanize).
    2. Choose a Strategy: Decide on a strategy: User-specific locale, application-wide default, or explicitly set locale for each Humanizer call.
    3. Implement the Strategy: Use the overloads of Humanizer methods that accept a CultureInfo object consistently.
    4. Example (C#): 
      // User-specific (assuming GetUserCulture() is available)
CultureInfo userCulture = GetUserCulture();
string humanizedDate = DateTime.Now.Humanize(culture: userCulture);

// Explicit locale
string humanizedNumber = 1234.ToWords(CultureInfo.GetCultureInfo("fr-FR")); // French

  • Threats Mitigated:

    • Unexpected Output (Severity: Low): Prevents unexpected variations in output due to different cultural formatting rules.
    • Misinterpretation (Severity: Low): Avoids misinterpretations of Humanized strings due to cultural differences.
    • Logic Errors (Severity: Low): Prevents logic errors from incorrect assumptions about the format of Humanizer's output.

  • Impact:

    • All listed threats: Risk significantly reduced by ensuring consistent and predictable locale handling within Humanizer.

  • Currently Implemented: (Example - Needs to be filled in based on your project)

    • The application uses the system's default locale, which is not ideal.

  • Missing Implementation: (Example - Needs to be filled in based on your project)

    • Need to implement a strategy for explicitly setting the locale in every call to a locale-aware Humanizer method.

Mitigation Strategy: Ordinal Numbers Handling (Humanizer-Specific)

  • Description:

    1. Identify Usage: Find all instances where ToOrdinalWords or similar ordinal methods are used.
    2. Validate Input: Before calling the method, ensure the input is a valid integer using int.TryParse or similar.
    3. Handle Invalid Input: If invalid, handle the error appropriately (don't call Humanizer).
    4. Specify Culture: Always explicitly specify the culture using the CultureInfo overload to ensure consistent results.
    5. Example: 
      string input = GetInput();
if (int.TryParse(input, out int number))
{
    string ordinal = number.ToOrdinalWords(CultureInfo.GetCultureInfo("en-US")); // Explicit culture
    // Use the ordinal string
}
else
{
    // Handle invalid input
}

  • Threats Mitigated:

    • Unexpected Output (Severity: Low): Prevents unexpected output if the input is not a valid number.
    • Logic Errors (Severity: Low): Prevents logic errors from incorrect assumptions about the format.
    • Locale-Specific Issues (Severity: Low): Avoids unexpected behavior due to different cultural rules for ordinal numbers.

  • Impact:

    • All listed threats: Risk significantly reduced.

  • Currently Implemented: (Example - Needs to be filled in based on your project)

    • Not implemented.

  • Missing Implementation: (Example - Needs to be filled in based on your project)

    • Need to add input validation and explicit culture specification to all uses of ordinal methods.

Mitigation Strategy: Unit and Integration Testing (Humanizer-Specific Calls)

  • Description:

    1. Create Test Cases: Write unit tests specifically for how your code calls Humanizer methods.
    2. Cover Edge Cases: Include test cases for valid inputs, boundary values, invalid inputs, and different locales, focusing on the specific Humanizer methods you use.
    3. Integration Tests: Write integration tests to verify Humanizer works correctly with other parts of your application, paying attention to the data flow into and out of Humanizer.
    4. Automate Tests: Integrate the tests into your build process.
    5. Example: 
      [TestMethod]
public void TestToWords_ValidInput_SpecificCulture() // Test specific culture
{
    Assert.AreEqual("one hundred twenty-three", 123.ToWords(CultureInfo.GetCultureInfo("en-US")));
}

[TestMethod]
public void TestToWords_NegativeInput_SpecificCulture()
{
    Assert.AreEqual("minus einhundertdreiundzwanzig", (-123).ToWords(CultureInfo.GetCultureInfo("de-DE"))); // German
}

[TestMethod]
[ExpectedException(typeof(ArgumentOutOfRangeException))] // Or handle in the test
public void TestToWords_OutOfRangeInput() // Test input validation *before* Humanizer
{
    // Assuming you have a validation check; this tests that it works
    long.MaxValue.ToWords(CultureInfo.GetCultureInfo("en-US"));
}

  • Threats Mitigated:

    • Unexpected Output (Severity: Low to Medium): Catches unexpected behavior due to various inputs and locales in your specific usage.
    • Logic Errors (Severity: Low to Medium): Identifies logic errors caused by incorrect assumptions about Humanizer's output in your code.
    • Regressions (Severity: Low to Medium): Prevents regressions when Humanizer or your code is updated.

  • Impact:

    • All listed threats: Risk significantly reduced by catching errors early.

  • Currently Implemented: (Example - Needs to be filled in based on your project)

    • Basic unit tests exist, but coverage is incomplete, especially for different locales and edge cases related to how Humanizer is called.

  • Missing Implementation: (Example - Needs to be filled in based on your project)

    • Expand test coverage to include edge cases, different locales, and integration tests, specifically focusing on the interaction between your code and Humanizer.