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Attack Surface Analysis for mxgmn/wavefunctioncollapse

Attack Surface: Key Attack Surface: Wave Function Collapse (mxgmn/wavefunctioncollapse) - High & Critical Risks

This list focuses on the most serious attack vectors directly related to the library's functionality.

Attack Surface: Attack Surface Element: Malicious Input Patterns

  • Description: Attackers craft specific input images, tile sets, or rule sets to trigger unexpected behavior, resource exhaustion, or exploit vulnerabilities within the wavefunctioncollapse algorithm itself.
    • Wavefunctioncollapse Contribution: The library's core function is to process these inputs. The algorithm's complexity and reliance on user-defined data create this vulnerability.
    • Example: An attacker provides a tile set with inconsistent dimensions, a rule set with contradictory rules, or an image designed to trigger edge-case behavior in the constraint solver.
    • Impact: Denial of Service (DoS), application crashes, potentially exploitable unexpected behavior.
    • Risk Severity: High
    • Mitigation Strategies:
      • Strict Input Validation: Enforce rigorous checks on all input data: image dimensions, color palettes, tile consistency (dimensions, data types), and rule set validity (well-formedness, no contradictions).
      • Input Fuzzing: Use fuzzing tools to test the library with a wide range of malformed and unexpected inputs to identify vulnerabilities.
      • Sandboxing: Consider processing untrusted inputs in an isolated environment (separate process or container) to limit the impact of exploits.

Attack Surface: Attack Surface Element: Resource Exhaustion (Denial of Service)

  • Description: Attackers provide inputs designed to consume excessive CPU, memory, or processing time, causing a denial-of-service.
    • Wavefunctioncollapse Contribution: The algorithm's computational complexity can be high, especially with complex inputs and rule sets. Large output dimensions directly impact memory usage.
    • Example: An attacker requests an extremely large output image (e.g., 100,000 x 100,000 pixels) or provides a rule set that causes extensive backtracking and long processing times.
    • Impact: Application unavailability, system instability, potential for complete system crash.
    • Risk Severity: High
    • Mitigation Strategies:
      • Output Size Limits: Enforce strict, hard-coded limits on the maximum output dimensions (width, height, and depth for 3D).
      • Timeouts: Implement strict timeouts for the generation process. Terminate if a solution isn't found within a reasonable time.
      • Resource Monitoring: Continuously monitor CPU and memory usage during generation. Terminate the process if usage exceeds predefined thresholds.
      • Progressive Generation (if applicable): Generate output in chunks to avoid allocating the entire output buffer at once.
      • Complexity Analysis (Advanced): Analyze input complexity before processing to reject inputs predicted to be too computationally expensive.

Attack Surface: Attack Surface Element: Infinite Loops / Non-Termination

  • Description: The wavefunctioncollapse algorithm gets stuck in an infinite loop or fails to terminate due to contradictory rules or internal logic errors.
    • Wavefunctioncollapse Contribution: The core of the library is a constraint satisfaction algorithm. Poorly defined constraints or bugs in the implementation can lead directly to non-termination.
    • Example: An attacker provides a rule set where no valid solution is possible, or a combination of tiles and rules that create an unsolvable constraint.
    • Impact: Denial of Service (DoS), application hangs indefinitely.
    • Risk Severity: High
    • Mitigation Strategies:
      • Maximum Iteration Limits: Implement a hard limit on the number of iterations the algorithm can perform.
      • Contradiction Detection: Implement robust checks for contradictions in the rule set before starting the generation process. This is crucial.
      • Stagnation Detection: Monitor the algorithm's progress. If the output is not changing significantly over a period, it may be stuck.

Attack Surface: Attack Surface Element: Code Injection

  • Description: Attacker is able to inject and execute arbitrary code through crafted input.
    • Wavefunctioncollapse Contribution: Highly unlikely, but if the library has a vulnerability that allows interpreting parts of the input (e.g., the rule set) as executable code, this would be a direct and critical vulnerability.
    • Example: The library has a hidden, undocumented feature or a severe bug that allows executing code embedded within a specially crafted rule set (extremely unlikely, but the impact necessitates inclusion).
    • Impact: Complete system compromise.
    • Risk Severity: Critical
    • Mitigation Strategies:
      • No Dynamic Code Execution: Ensure the library never executes arbitrary code based on user-provided input. The rule sets and other inputs should be treated strictly as data, never as executable code.
      • Rigorous Input Validation: This is the primary defense. Even seemingly harmless data should be thoroughly validated to prevent any unexpected interpretation.