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attack-surface.md

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Attack Surface Analysis for plotly/dash

Attack Surface: Cross-Site Scripting (XSS) via Unsanitized User Input in Component Properties

  • Description: Attackers inject malicious scripts into web pages through user-provided data rendered by Dash components, leading to script execution in users' browsers.

    • Dash Contribution: Dash's component-based architecture and dynamic property updates, especially the use of children in html components and dcc.Markdown, directly render content. If user input is not sanitized before being used as component properties, Dash facilitates the injection point for XSS. dangerously_allow_html=True explicitly exacerbates this.

    • Example: A Dash app uses dcc.Input to get user text and displays it in html.Div using children. Entering <img src=x onerror=alert('XSS')> in the input results in the script executing when the html.Div updates.

    • Impact: Account compromise, data theft, website defacement, malware distribution.

    • Risk Severity: High to Critical.

    • Mitigation Strategies:

      • Strict Input Sanitization: Sanitize all user inputs before setting them as component properties. Use libraries to escape HTML entities and remove or neutralize JavaScript.
      • Content Security Policy (CSP): Implement a restrictive CSP header to limit script execution sources, mitigating XSS impact.
      • Minimize dangerously_allow_html=True: Avoid using dangerously_allow_html=True in dcc.Markdown unless absolutely necessary and with extreme input sanitization.
      • Output Encoding: Ensure proper output encoding to prevent browsers from interpreting user data as code.

Attack Surface: Server-Side Command Injection via Unvalidated Callback Inputs

  • Description: Attackers inject malicious operating system commands through user inputs processed by Dash callbacks, leading to arbitrary command execution on the server.

    • Dash Contribution: Dash callbacks are the primary server-side logic execution points. They receive user input from client-side components. If callbacks use this input to construct and execute system commands (e.g., via os.system, subprocess) without validation, Dash's callback mechanism becomes the direct vector for command injection.

    • Example: A Dash callback takes user input for a filename and uses os.system(f"grep {user_input} file.txt"). An attacker could input "; cat /etc/passwd #" to execute cat /etc/passwd on the server.

    • Impact: Full server compromise, data breach, denial of service, data manipulation, privilege escalation.

    • Risk Severity: Critical.

    • Mitigation Strategies:

      • Rigorous Input Validation: Validate all callback inputs. Use whitelists for allowed characters and patterns.
      • Avoid System Commands: Minimize or eliminate direct system command execution in callbacks. Use safer alternatives or parameterized execution if necessary.
      • Principle of Least Privilege: Run the Dash application with minimal server privileges to limit command injection impact.
      • Input Validation Libraries: Utilize dedicated input validation libraries for robust protection.

Attack Surface: Debug Mode Enabled in Production

  • Description: Running Dash (or Flask) applications in debug mode in production exposes sensitive information and can create code execution risks.

    • Dash Contribution: Dash applications inherit Flask's debug mode functionality, enabled via debug=True in app.run_server(). Dash deployment simplicity can lead to accidentally leaving debug mode on in production.

    • Example: With debug mode enabled, Dash displays detailed stack traces in the browser upon errors, revealing server file paths, code structure, and potentially sensitive configuration details to attackers.

    • Impact: Information disclosure, easier exploitation of other vulnerabilities, potential code execution.

    • Risk Severity: High.

    • Mitigation Strategies:

      • Disable Debug Mode: Never run Dash applications in production with debug=True. Ensure debug=False or omit the argument for production deployments.
      • Proper Error Handling & Logging: Implement robust error handling and logging to manage errors without exposing sensitive details to users.
      • Environment Variables: Use environment variables to manage configuration, ensuring debug mode is easily disabled in production.