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attack-surface.md

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Attack Surface Analysis for naptha/tesseract.js

Attack Surface: Image Parsing Exploits

  • Description: Vulnerabilities in how Tesseract (the underlying C++ engine) parses and processes image files (JPEG, PNG, TIFF, WebP, etc.).
  • tesseract.js Contribution: tesseract.js bundles and executes the Tesseract engine via WebAssembly, directly exposing these parsing vulnerabilities to web applications. This is the primary attack vector.
  • Example: An attacker crafts a malformed JPEG image with an embedded exploit that triggers a buffer overflow in Tesseract's image decoding library.
  • Impact: Remote Code Execution (RCE) within the WebAssembly sandbox; potential for sandbox escape (though less likely). Denial of Service (DoS) by crashing the worker.
  • Risk Severity: High to Critical (depending on the specific vulnerability and browser security).
  • Mitigation Strategies:
    • Update: Keep tesseract.js updated to the latest version to include the newest Tesseract engine patches. This is the most important mitigation.
    • Pre-Validation: Implement robust image validation before passing to tesseract.js. Check file type, dimensions, and size. Use a dedicated image processing library (e.g., Sharp, Jimp) for sanitization and resizing. This adds a crucial layer of defense.
    • Worker Isolation: Ensure tesseract.js runs in a dedicated Web Worker (default behavior).
    • CSP: Use a Content Security Policy (CSP) to restrict Web Worker capabilities.

Attack Surface: Malicious Trained Data Files

  • Description: Exploitation of vulnerabilities in how Tesseract loads and processes .traineddata files (language models).
  • tesseract.js Contribution: tesseract.js directly loads and uses these .traineddata files, making the application vulnerable if a malicious file is used. This is a direct attack vector.
  • Example: An attacker provides a crafted .traineddata file that, when loaded, triggers a vulnerability in Tesseract's data processing logic.
  • Impact: RCE within the WebAssembly sandbox; potential for sandbox escape (less likely). DoS.
  • Risk Severity: High.
  • Mitigation Strategies:
    • Trusted Sources: Only use .traineddata files from the official Tesseract repository or other highly trusted sources. This is paramount.
    • No User Uploads: Never allow users to upload their own .traineddata files. This is a critical security measure.
    • Integrity Checks: Verify the integrity of .traineddata files (e.g., using checksums) before loading.
    • Secure Hosting: Host .traineddata files yourself and serve them with strong security headers (CSP).

Attack Surface: Supply Chain Attacks

  • Description: Compromise of the tesseract.js package itself or its dependencies.
  • tesseract.js Contribution: The application is directly dependent on the security of tesseract.js and its dependencies. A compromised package directly impacts the application.
  • Example: A malicious actor publishes a compromised version of tesseract.js or one of its dependencies to npm.
  • Impact: RCE, data breaches, complete application compromise.
  • Risk Severity: Critical.
  • Mitigation Strategies:
    • Dependency Locking: Use package-lock.json (npm) or yarn.lock (yarn) to lock dependency versions. This is essential.
    • Dependency Auditing: Regularly audit dependencies for known vulnerabilities.
    • SCA Tools: Use Software Composition Analysis (SCA) tools to identify and manage dependency risks.
    • Version Pinning: Pin dependencies to specific, known-good versions.