mitigations.md

Mitigation Strategies Analysis for textualize/rich

Mitigation Strategy: Input Sanitization and Whitelisting for rich Markup

1. Input Sanitization and Whitelisting for rich Markup

• Mitigation Strategy: Input Sanitization and Whitelisting for rich Markup.

• Description:

  1. Identify rich Input Points: Pinpoint all locations in your code where data (especially user-supplied or untrusted data) is passed to rich functions that interpret markup. This includes, but is not limited to: Console.print(), Text(), Markdown(), Panel(), and any custom classes or functions that utilize rich's rendering engine.
  2. Define a Strict Whitelist: Create a very specific list (whitelist) of allowed rich markup tags and attributes. This whitelist should be as restrictive as possible, containing only the absolutely essential tags for your application's needs. For example: ['bold', 'italic', 'underline', 'color=red', 'color=blue']. Explicitly exclude any tags that could allow for arbitrary code execution, escape sequences, or complex styling that isn't strictly required.
  3. Implement a rich-Specific Sanitizer: Before passing any input to rich, use a dedicated sanitization function or library. While general-purpose HTML sanitizers (like bleach) can be used, they must be configured specifically for the rich whitelist. A custom sanitizer tailored to rich's markup syntax might be necessary for maximum security. The sanitizer should:
     • Remove all tags and attributes not present in the whitelist.
     • Properly escape any special characters within allowed tags to prevent them from being misinterpreted as markup. This is crucial, as rich's markup syntax might differ from standard HTML.
     • Handle nested markup carefully, potentially limiting the nesting depth to prevent resource exhaustion.
  4. Context-Aware Sanitization: If different parts of your application require different levels of rich markup, implement separate sanitization rules for each context. For example, user comments might allow limited formatting, while log messages might disallow all markup.
  5. Testing with rich-Specific Payloads: Thoroughly test the sanitization logic with a wide range of inputs, including specifically crafted payloads designed to exploit potential vulnerabilities in rich's markup parsing. This is different from general HTML/XSS testing.

• Threats Mitigated:

  • Arbitrary Code Execution (ACE) via Console Markup: (Severity: Critical) - Prevents attackers from injecting malicious control sequences or escape codes that could lead to arbitrary code execution through rich's rendering engine.
  • Log Spoofing/Injection (via rich formatting): (Severity: High) - Reduces the risk of attackers injecting misleading log entries by manipulating the formatting of log messages rendered by rich.
  • Information Disclosure (Indirect, via rich styling): (Severity: Medium) - By limiting the available markup, it reduces the potential for attackers to use styling (colors, emphasis) to subtly leak information or mislead users.

• Impact:

  • ACE: Risk reduction: Very High (near elimination if implemented correctly and comprehensively).
  • Log Spoofing/Injection: Risk reduction: High (specifically for injection via rich formatting).
  • Information Disclosure: Risk reduction: Medium.

• Currently Implemented:

  • Example: UserInputHandler.sanitize_rich_input() function uses a custom sanitizer with a predefined whitelist for user-provided text displayed with rich.panel.Panel. Found in modules/user_input.py.

• Missing Implementation:

  • Example: Log formatting in modules/logging.py uses rich.console.Console to style log output, but does not sanitize user-provided data before applying formatting. This is a critical vulnerability.
  • Example: The error reporting module (modules/errors.py) uses rich.traceback.Traceback to display exceptions, and input sanitization is inconsistent.

Mitigation Strategy: Input and Output Length Limits (Specifically for rich)

2. Input and Output Length Limits (Specifically for rich)

• Mitigation Strategy: Impose Strict Input and Output Length Limits for rich-Processed Data.

• Description:

  1. Identify rich Processing Points: Determine all locations where user input or data from external sources is processed by rich for rendering.
  2. Define Input Length Limits (Pre-rich): Establish reasonable maximum lengths for input strings before they are passed to rich. These limits should be based on the expected data and application requirements, and they should be as short as is practical. Consider different limits for different input fields or contexts.
  3. Enforce Input Limits (Pre-rich): Before passing any input to rich, rigorously check its length. If it exceeds the limit:
     • Reject the input entirely (with a clear error message).
     • Truncate the input to the maximum allowed length (and inform the user, if appropriate).
  4. Define Output Length Limits (Post-rich): Determine a maximum size for the output generated by rich. This could be based on the number of characters, lines, or bytes in the rendered output. This is distinct from the input length.
  5. Enforce Output Limits (Post-rich): After rich has processed the input and generated the output, check the size of the resulting output. If it exceeds the limit:
     • Truncate the output (and clearly indicate this to the user, perhaps with a "Show More" option if feasible).
     • Consider alternative rendering strategies (e.g., pagination, lazy loading) for very large outputs that are legitimately expected.
  6. Limit Nested rich Markup Depth: Specifically limit the depth of nested rich markup allowed. Deeply nested markup can lead to exponential growth in output size, even with relatively short input. This might require custom parsing of the input before passing it to rich, potentially rejecting input with excessive nesting.
  7. rich-Specific Testing: Test with inputs of varying lengths, including very long inputs and deeply nested rich markup, to ensure the limits are enforced correctly and that rich itself doesn't introduce unexpected behavior.

• Threats Mitigated:

  • Denial of Service (DoS) via Resource Exhaustion (Targeting rich): (Severity: High) - Prevents attackers from consuming excessive resources (CPU, memory, terminal buffer) by providing overly long or complex inputs specifically designed to exploit rich's rendering capabilities.

• Impact:

  • DoS: Risk reduction: High (specifically for DoS attacks leveraging rich).

• Currently Implemented:

  • Example: Input fields in the user profile editor (forms/profile.py) have character limits enforced, and these limits are checked before the data is passed to rich for display.

• Missing Implementation:

  • Example: The search results display (modules/search.py), which uses rich to format results, does not currently limit the length of the displayed snippets, potentially leading to DoS if search results contain very long text.
  • Example: There are no output size limits for rich-generated tables in modules/data_display.py. Large datasets could cause excessive resource consumption.

Mitigation Strategy: Secure Log Handling with rich Formatting

3. Secure Log Handling with rich Formatting

• Mitigation Strategy: Secure Log Handling with rich Formatting (Sanitization and Separation).

• Description:

  1. Identify Log Inputs for rich: Determine all sources of data that are included in log messages that are subsequently formatted using rich. This is crucial if any part of the log message includes user-provided input or data from untrusted sources.
  2. Escape Before rich Formatting: Before passing any data to rich functions for log formatting, always escape special characters that could be interpreted as rich markup or control sequences. Use a dedicated escaping function (e.g., html.escape(), but be aware of rich's specific syntax) or a sanitization library configured specifically for rich's allowed markup (if any formatting is desired in logs). This escaping must happen before any rich processing.
  3. Separate Logging and rich Formatting: Use a robust logging library (e.g., Python's logging module) to handle the core logging process (writing to files, sending to remote servers, etc.). Apply rich formatting only for displaying logs to the console or a specific, controlled output, not for the primary logging mechanism. This separation is critical.
  4. Structured Logging with rich for Display Only: Ideally, use structured logging (e.g., JSON format) to store log data. This makes logs easier to parse and analyze, and it significantly reduces the risk of misinterpreting malicious input. Apply rich formatting only for the display of these structured logs, never for their storage.
  5. Testing with rich-Specific Injection Attempts: Include tests that specifically attempt to inject malicious rich markup or control sequences into log messages to verify the effectiveness of the sanitization and separation.

• Threats Mitigated:

  • Log Spoofing/Injection (via rich formatting): (Severity: High) - Prevents attackers from injecting misleading or malicious content into log files by manipulating the rich formatting applied to log messages. This is distinct from general log injection; it focuses on the rich aspect.
  • Information Disclosure (Indirect, via rich in logs): (Severity: Medium) - Reduces the risk of sensitive information being inadvertently leaked through log messages due to rich styling (e.g., highlighting certain data).

• Impact:

  • Log Spoofing/Injection: Risk reduction: High (specifically for injection through rich formatting).
  • Information Disclosure: Risk reduction: Medium.

• Currently Implemented:

  • Example: The application uses Python's logging module to write logs to files, and rich is used only for console output.

• Missing Implementation:

  • Example: Log messages that include user input are not consistently escaped before being passed to rich for console formatting. This is a critical vulnerability that needs to be addressed in modules/logging.py and any other modules that generate logs displayed with rich.
  • Example: The application does not use structured logging; it uses plain text logs, even for the underlying log data. This makes it harder to analyze and potentially more vulnerable to injection, even with rich formatting applied only for display.