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Mitigation Strategies Analysis for kitao/pyxel

Mitigation Strategy: Strict Asset Validation (Pyxel-Specific Aspects)

1. Strict Asset Validation (Pyxel-Specific Aspects)

  • Mitigation Strategy: Strict Asset Validation (Pyxel-Specific Aspects)

  • Description:

    1. .pyxel File Validation: This is the most crucial Pyxel-specific aspect. Since .pyxel is a custom format, Pyxel's internal parser is the only line of defense.
      • No Schema (Likely): Assume there's no official schema. Therefore, implement a very rigorous custom parser in your asset loading code. This parser must:
        • Byte-Level Verification: Understand the exact byte structure of the .pyxel format. Verify every header, section marker, and data field. Do not rely on simple string parsing or assumptions.
        • Data Type Validation: Enforce strict data types for each field. If a field is supposed to be a 16-bit integer, ensure it is a 16-bit integer and not something else.
        • Bounds Checking: If the .pyxel file defines image dimensions, tilemap sizes, or other arrays, strictly check that all data accesses within those arrays are within bounds. This is critical to prevent buffer overflows.
        • Cross-Reference Validation: If the .pyxel file contains references between sections (e.g., an image index used in a tilemap), validate that these references are valid and point to existing data.
        • Rejection on Any Error: If any part of the .pyxel file doesn't match the expected format, reject the entire file. Do not attempt to "recover" or "fix" the data.
      • Example (Conceptual): 
        def load_pyxel_file(filename):
    with open(filename, "rb") as f:  # Open in binary mode
        data = f.read()

    # --- Header Verification ---
    header = data[:4]
    if header != b"PYXL":  # Example magic number
        raise ValueError("Invalid .pyxel file: Incorrect header")

    # --- Version Check ---
    version = int.from_bytes(data[4:6], byteorder='little')
    if version != 1:  # Example version
        raise ValueError("Unsupported .pyxel version")

    # --- Image Section ---
    image_count = int.from_bytes(data[6:8], byteorder='little')
    offset = 8
    for _ in range(image_count):
        width = int.from_bytes(data[offset:offset+2], byteorder='little')
        height = int.from_bytes(data[offset+2:offset+4], byteorder='little')
        # ... Validate width/height against limits ...
        offset += 4
        # ... Read and validate pixel data ...
        pixel_data_size = width * height * bytes_per_pixel  # Calculate expected size
        pixel_data = data[offset:offset + pixel_data_size]
        # ... Validate pixel_data (e.g., color indices) ...
        offset += pixel_data_size

    # --- Tilemap Section ---
    # ... Similar rigorous parsing and validation ...

    # --- Sound Section ---
    # ... Similar rigorous parsing and validation ...

    return parsed_data # Return only if ALL checks pass
    2. Image/Audio Format Validation (Within Pyxel's Capabilities): While Pyxel likely uses underlying libraries for image/audio decoding, check if Pyxel exposes any information about the loaded assets before fully processing them. If it does, use this information:
      • pyxel.image(img).width and pyxel.image(img).height: Always check these immediately after loading an image. Reject images that are too large before attempting to draw them.
      • Sound Duration (If Available): If Pyxel provides a way to get the duration of a loaded sound without playing it, use this to enforce duration limits.

  • Threats Mitigated:

    • Malicious .pyxel Files (Code Execution): Severity: Critical. A crafted .pyxel file is the most direct way to attack Pyxel itself.
    • Malicious .pyxel Files (Denial of Service): Severity: High. A .pyxel file could specify huge image dimensions or other data that leads to excessive memory allocation.
    • Malicious Image/Audio Files (Code Execution/DoS - Indirectly): Severity: High/Critical. By validating dimensions/duration before Pyxel's internal drawing/playing routines are used, you reduce the chance of triggering vulnerabilities in those routines.

  • Impact:

    • Code Execution: Risk significantly reduced (from Critical to Low/Medium, depending on the rigor of the .pyxel parser).
    • Denial of Service: Risk significantly reduced (from High to Low/Medium).

  • Currently Implemented:

    • Example: Basic image dimension checks using pyxel.image(img).width and pyxel.image(img).height are implemented.

  • Missing Implementation:

    • Example: A robust, byte-level .pyxel file parser is completely missing. This is the highest priority. Checks for sound duration (if possible within Pyxel) are also missing.

Mitigation Strategy: Wrapper Functions (Pyxel API)

2. Wrapper Functions (Pyxel API)

  • Mitigation Strategy: Wrapper Functions (Pyxel API)

  • Description:

    1. Focus on Drawing and Resource Access: Prioritize wrapping functions that:
      • Draw to the screen (e.g., pyxel.blt, pyxel.rect, pyxel.circ, pyxel.text).
      • Access image or tilemap data (e.g., pyxel.image(img).get, pyxel.tilemap(tm).get).
    2. Input Validation: Within the wrappers, always validate:
      • Coordinates (x, y): Ensure they are within the screen bounds (0 <= x < pyxel.width, 0 <= y < pyxel.height).
      • Image/Tilemap Indices (img, tm): Ensure they are valid indices for loaded images/tilemaps.
      • Source Coordinates (u, v, w, h for pyxel.blt): Ensure they are within the bounds of the source image.
      • Color Keys (colkey): Ensure they are valid color indices.
      • Text Input (for pyxel.text): While not a direct Pyxel vulnerability, always sanitize any user-provided text before displaying it. This prevents potential cross-site scripting (XSS)-like attacks if the text is ever displayed in a web context (e.g., if Pyxel is compiled to Wasm).
    3. Example (Wrapper for pyxel.blt): 
      def safe_blt(x, y, img, u, v, w, h, colkey=-1):
    if not (0 <= x < pyxel.width and 0 <= y < pyxel.height):
        print(f"Error: blt coordinates out of bounds: ({x}, {y})")
        return  # Or raise an exception

    if not (0 <= img < len(loaded_images)): # Assuming loaded_images is a list
        print(f"Error: Invalid image index: {img}")
        return

    image = loaded_images[img]
    if not (0 <= u < image.width and 0 <= v < image.height and
            0 <= u + w <= image.width and 0 <= v + h <= image.height):
        print(f"Error: Source coordinates out of bounds for image {img}")
        return

    if colkey != -1 and not (0 <= colkey <= 15):  # Assuming 16 colors
         print(f"Error: Invalid color key: {colkey}")
         return

    pyxel.blt(x, y, img, u, v, w, h, colkey)
    4. Example (Wrapper for pyxel.image(img).get): 
      def safe_image_get(img_index, x, y):
    if not (0 <= img_index < len(loaded_images)):
        print(f"Error: Invalid image index: {img_index}")
        return 0 # Return a default value

    image = loaded_images[img_index]

    if not (0 <= x < image.width and 0 <= y < image.height):
        print(f"Error: Image get coordinates out of bounds: ({x}, {y})")
        return 0

    return pyxel.image(img_index).get(x,y)

  • Threats Mitigated:

    • Pyxel API Misuse (Out-of-Bounds Access): Severity: High. Prevents drawing outside the screen or accessing invalid image/tilemap data, which could lead to crashes or undefined behavior.
    • Pyxel API Misuse (Invalid Input): Severity: Medium. Prevents passing invalid parameters to Pyxel functions, which could trigger unexpected behavior.

  • Impact:

    • Out-of-Bounds Access: Risk significantly reduced (from High to Low).
    • Invalid Input: Risk reduced (from Medium to Low).

  • Currently Implemented:

    • Example: A basic wrapper for pyxel.blt exists, but it doesn't perform all the necessary checks (e.g., source coordinate validation).

  • Missing Implementation:

    • Example: Wrappers are needed for all drawing functions (pyxel.rect, pyxel.circ, pyxel.text, etc.) and for image/tilemap data access functions (pyxel.image(img).get, pyxel.tilemap(tm).get). The existing pyxel.blt wrapper needs to be improved.

Mitigation Strategy: Resource Limits (Enforced Before Pyxel Calls)

3. Resource Limits (Enforced Before Pyxel Calls)

  • Mitigation Strategy: Resource Limits (Enforced Before Pyxel Calls)

  • Description:

    1. Pre-emptive Checks: Before calling any Pyxel function that allocates resources (e.g., loading an image, creating a tilemap), check if the operation would exceed predefined limits.
    2. Image Dimensions: Before calling pyxel.image.load, check the image file's dimensions (using a separate image library if necessary) and reject it if it's too large.
    3. Audio Duration/Size: Before calling pyxel.sound.load, check the audio file's duration and size (using a separate audio library if necessary) and reject it if it's too large.
    4. Tilemap Size: Before creating a tilemap (or loading it from a .pyxel file), ensure its dimensions are within reasonable limits.
    5. Memory Allocation (Indirect): While you can't directly control Pyxel's internal memory allocation, by limiting the size of assets before they are loaded, you indirectly limit memory usage.

  • Threats Mitigated:

    • Malicious Asset Files (Denial of Service): Severity: High. Prevents loading excessively large assets that could cause Pyxel to consume too much memory or CPU time.

  • Impact:

    • Denial of Service: Risk significantly reduced (from High to Low/Medium).

  • Currently Implemented:

    • Example: Image dimension checks are performed after loading the image using pyxel.image(img).width, but before drawing.

  • Missing Implementation:

    • Example: Image dimension checks should be performed before calling pyxel.image.load. Checks for audio duration/size (before loading) are missing. Tilemap size limits are not explicitly enforced before creation.