attack-surface.md

Attack Surface Analysis for intervention/image

Attack Surface: Image Parsing Vulnerabilities (Memory Corruption)

• Description: Exploiting flaws in image format parsers (JPEG, PNG, GIF, etc.) to cause memory corruption (buffer overflows, heap overflows) when processing malicious image files.
  • How Image Contributes to Attack Surface: intervention/image relies on underlying libraries (GD Library, Imagick, Gmagick) to parse various image formats. Vulnerabilities in these parsers are directly exposed when intervention/image processes images.
  • Example: A user uploads a specially crafted PNG file with a malformed header. When intervention/image (using GD Library) attempts to parse this file, it triggers a buffer overflow in the PNG parsing routine, potentially allowing an attacker to overwrite memory and gain control of the application process.
  • Impact: Denial of Service (application crash), potentially Remote Code Execution (if memory corruption is exploitable).
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Keep underlying image libraries (GD Library, Imagick, Gmagick) updated to the latest versions to patch known parsing vulnerabilities.
    • Use a robust and actively maintained image processing library.
    • Consider using sandboxing or containerization to limit the impact of potential Remote Code Execution.

Attack Surface: Image Parsing Vulnerabilities (Integer Overflows/Underflows)

• Description: Manipulating image parameters (dimensions, color depth) within image files to cause integer overflows or underflows during parsing, leading to unexpected behavior and potential vulnerabilities.
  • How Image Contributes to Attack Surface: intervention/image uses image dimensions and other parameters extracted during parsing for processing. Integer overflows/underflows during parsing can lead to incorrect memory allocation or processing logic within intervention/image or underlying libraries.
  • Example: An attacker crafts a TIFF image with extremely large dimensions specified in its header. When intervention/image (using Imagick) parses this image, an integer overflow occurs when calculating memory allocation size, potentially leading to a heap overflow or other memory corruption issues.
  • Impact: Denial of Service, potentially Memory Corruption, potentially unexpected application behavior.
  • Risk Severity: High
  • Mitigation Strategies:
    • Keep underlying image libraries updated.
    • Implement resource limits: Limit the maximum allowed image dimensions and file sizes to prevent processing of excessively large images.
    • Use secure coding practices in underlying libraries and ensure intervention/image handles integer operations safely.

Attack Surface: Denial of Service (DoS) through Resource Exhaustion (Image Processing)

• Description: Exploiting computationally intensive image processing operations to consume excessive server resources (CPU, memory, disk I/O), leading to denial of service.
  • How Image Contributes to Attack Surface: intervention/image provides functions for various image manipulations (resize, filters, etc.). Processing very large or complex images, or applying computationally expensive operations, can be resource-intensive and triggered by user-uploaded images.
  • Example: An attacker uploads a very large image file (e.g., a multi-megapixel TIFF) and triggers a complex image resizing and filtering operation using intervention/image. This operation consumes significant CPU and memory, potentially slowing down or crashing the server if multiple such requests are made concurrently.
  • Impact: Denial of Service (application unavailability, server slowdown).
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement resource limits:
      • File size limits: Restrict the maximum allowed image file size.
      • Image dimension limits: Limit the maximum allowed image width and height.
      • Processing time limits: Set timeouts for image processing operations.
    • Queue image processing tasks: Offload image processing to background queues to prevent blocking the main application thread.
    • Rate limiting: Limit the number of image processing requests from a single user or IP address.

Attack Surface: Server-Side Request Forgery (SSRF) via Imagick (Driver Specific)

• Description: Exploiting vulnerabilities in Imagick's handling of image formats (especially SVG) to make the server initiate requests to internal or external resources, potentially bypassing firewalls or accessing internal services.
  • How Image Contributes to Attack Surface: If intervention/image is configured to use Imagick as the driver, and the application processes SVG images, vulnerabilities in Imagick's SVG parsing (or related features like URL handling within SVG) can be exploited for SSRF through malicious image uploads.
  • Example: An attacker uploads a malicious SVG image that contains an external entity declaration referencing an internal service (e.g., http://localhost:1699/latest/meta-data for AWS metadata). When intervention/image (using Imagick) processes this SVG, Imagick might attempt to fetch the external entity, resulting in an SSRF attack that can expose internal information or interact with internal services.
  • Impact: Information Disclosure (accessing internal resources, metadata), potentially Remote Code Execution (if internal services are vulnerable), bypassing security controls.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Configure Imagick's policy file: Restrict or disable potentially dangerous features like URL handling, remote image fetching, and delegate functionality in Imagick's policy file (policy.xml).
    • Disable or restrict SVG processing if not necessary.
    • Input validation: Sanitize or reject SVG images containing external entity declarations or URLs.
    • Network segmentation: Isolate the web server from sensitive internal networks.
    • Web Application Firewall (WAF): Use a WAF to detect and block SSRF attempts.