Skip to content

Latest commit

 

History

History
44 lines (37 loc) · 4.46 KB

attack-surface.md

File metadata and controls

44 lines (37 loc) · 4.46 KB

Attack Surface Analysis for abi/screenshot-to-code

Attack Surface: Malicious Image Upload - Image Parsing Vulnerabilities

  • Description: Exploiting vulnerabilities within image processing libraries through crafted image files uploaded as screenshots.
  • Screenshot-to-Code Contribution: The application's fundamental function of processing user-uploaded screenshots directly exposes it to risks from image parsing vulnerabilities.
  • Example: An attacker uploads a specially crafted PNG image designed to trigger a buffer overflow in the image processing library used by the application. This could lead to Remote Code Execution (RCE) on the server.
  • Impact: Remote Code Execution, Denial of Service (DoS).
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Developers:
      • Utilize secure and regularly updated image processing libraries.
      • Implement robust input validation to verify file headers and basic image properties before full processing.
      • Consider using sandboxed environments for image processing to isolate potential vulnerabilities.
      • Implement resource limits for image processing to prevent resource exhaustion and DoS.

Attack Surface: Code Injection via Generated Output - Unsanitized Output

  • Description: The generated code (HTML, CSS, JavaScript) might contain malicious scripts if not properly sanitized before being presented to the user or made available for download.
  • Screenshot-to-Code Contribution: The application generates code based on user-provided screenshots. If the AI model or post-processing steps fail to sanitize the output, malicious code could be included in the generated output.
  • Example: The AI model, due to misinterpretation or a flaw, generates JavaScript code that includes a <script> tag with malicious JavaScript. If this generated code is deployed without sanitization, it could lead to Cross-Site Scripting (XSS) vulnerabilities on websites using the generated code.
  • Impact: Cross-Site Scripting (XSS) vulnerabilities in applications built using the generated code.
  • Risk Severity: High
  • Mitigation Strategies:
    • Developers:
      • Implement strict output sanitization on the generated code before presenting it to the user or making it downloadable. This should include escaping HTML entities and removing potentially harmful JavaScript constructs.
      • Use Content Security Policy (CSP) in the application serving the generated code to mitigate potential XSS if any malicious code slips through.
      • Educate users about the importance of reviewing and sanitizing generated code before deployment.

Attack Surface: Vulnerabilities in Dependencies - Image Processing and AI/ML Libraries

  • Description: Exploiting known vulnerabilities in third-party libraries used by the application, specifically image processing and AI/ML libraries which are core to screenshot-to-code functionality.
  • Screenshot-to-Code Contribution: Screenshot-to-code applications inherently rely on image processing and AI/ML libraries to function, making them directly vulnerable to issues in these dependencies.
  • Example: A known vulnerability is discovered in the version of the TensorFlow or PyTorch (AI/ML frameworks) or Pillow (image processing) library used by the application. An attacker exploits this vulnerability by uploading a crafted image or interacting with the application in a way that triggers the vulnerable code path in these libraries, potentially leading to RCE.
  • Impact: Remote Code Execution, Denial of Service, Data Breach, depending on the specific vulnerability in the dependency.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Developers:
      • Maintain a Software Bill of Materials (SBOM) to track all dependencies.
      • Regularly scan dependencies for known vulnerabilities using automated vulnerability scanning tools.
      • Keep all dependencies up-to-date with the latest security patches and stable versions.
      • Implement automated dependency update processes to ensure timely patching.
      • Subscribe to security advisories for used libraries to be informed about new vulnerabilities.