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Threat Model Analysis for mxgmn/wavefunctioncollapse

Threat: Malicious Rule Set Injection

Description: An attacker provides a crafted rule set as input to the application. This rule set is specifically designed to exploit vulnerabilities or cause severe unintended behavior within the wavefunctioncollapse algorithm or the application's handling of it. The attacker might upload a malicious rule set file or inject rules through an API. Impact:

  • Denial of Service (DoS) due to rule sets causing infinite loops, excessive computation, or memory exhaustion within the wavefunctioncollapse library, leading to server crash or unresponsiveness.
  • Remote Code Execution (RCE) if vulnerabilities in the rule parsing or processing logic of wavefunctioncollapse can be exploited through a crafted rule set.
  • Generation of severely harmful or policy-violating content at scale, potentially causing significant reputational or legal damage. Affected Component:
  • wavefunctioncollapse library's rule parsing and processing module.
  • Application's input validation and rule set handling logic. Risk Severity: High Mitigation Strategies:
  • Strict Input Validation and Sanitization: Implement robust and rigorous validation of all rule sets against a strict schema. Sanitize input data to prevent injection attacks.
  • Rule Set Sandboxing and Resource Limits: Process rule sets within a secure sandbox environment with enforced resource limits (CPU time, memory) to contain potential exploits and prevent DoS.
  • Code Review and Static Analysis of Rule Processing: Conduct thorough code reviews and static analysis of the application's rule set handling logic and the wavefunctioncollapse library's rule processing code (if feasible) to identify potential vulnerabilities.
  • Principle of Least Privilege: Run the wavefunctioncollapse process with the minimum necessary privileges to limit the impact of potential RCE.

Threat: Parameter Manipulation for Critical Resource Exhaustion

Description: An attacker manipulates input parameters controlling the wavefunctioncollapse algorithm (e.g., output grid size, tile set complexity) to extreme values. This is done to deliberately force the wavefunctioncollapse library to consume an excessive amount of server resources, leading to a critical Denial of Service. The attacker exploits the computational intensity of the algorithm itself. Impact:

  • Critical Denial of Service (DoS) rendering the application and potentially other services on the same server unavailable due to complete resource exhaustion (CPU, memory, potentially I/O).
  • Server crash or instability due to overwhelming resource demands from the wavefunctioncollapse process.
  • Significant financial impact due to service downtime and potential infrastructure scaling costs to mitigate attacks. Affected Component:
  • Application's parameter handling logic when invoking the wavefunctioncollapse library.
  • wavefunctioncollapse library's core algorithm execution. Risk Severity: High Mitigation Strategies:
  • Aggressive Input Validation and Hard Limits: Implement very strict validation and hard, non-configurable limits on all parameters controlling resource consumption (e.g., maximum grid size, tile set complexity). These limits must be based on thorough performance testing and server capacity.
  • Resource Quotas and Monitoring with Automated Response: Implement resource quotas (CPU, memory) for wavefunctioncollapse processes at the OS or container level. Implement real-time monitoring of resource usage and automated responses (e.g., process termination, rate limiting, circuit breaking) when thresholds are exceeded.
  • Rate Limiting and Request Throttling (Aggressive): Implement aggressive rate limiting and request throttling for API endpoints or application features that trigger wavefunctioncollapse generation, especially for requests with potentially large parameter values.
  • Asynchronous Processing with Resource Prioritization: Offload wavefunctioncollapse processing to a dedicated asynchronous queue with resource prioritization. This can help isolate resource consumption and prevent DoS from impacting critical application components.

Threat: Vulnerabilities in wavefunctioncollapse Library Code

Description: The wavefunctioncollapse library itself contains critical security vulnerabilities (e.g., buffer overflows, integer overflows, use-after-free, or other memory corruption issues) in its C++ or Javascript code. An attacker exploits these vulnerabilities by crafting specific inputs (rule sets, parameters) or conditions that trigger vulnerable code paths within the library. Impact:

  • Remote Code Execution (RCE): Successful exploitation allows the attacker to execute arbitrary code on the server with the privileges of the application process running wavefunctioncollapse. This is a critical security breach.
  • Critical Denial of Service (DoS): Vulnerabilities can be exploited to reliably crash the application or the entire server, leading to prolonged downtime.
  • Information Disclosure: Vulnerabilities might allow an attacker to read sensitive data from the server's memory, including application secrets, user data, or internal system information. Affected Component:
  • wavefunctioncollapse library's core C++ or Javascript code. Risk Severity: Critical Mitigation Strategies:
  • Immediate and Regular Library Updates: Prioritize and immediately apply security updates and patches released for the wavefunctioncollapse library. Implement a system for continuous monitoring of library updates.
  • Comprehensive Dependency Scanning and Vulnerability Management: Implement automated dependency scanning tools to continuously monitor for known vulnerabilities in the wavefunctioncollapse library and its dependencies. Establish a vulnerability management process to promptly address identified issues.
  • Security Auditing and Penetration Testing: Conduct regular security audits and penetration testing specifically targeting the integration of the wavefunctioncollapse library and its potential vulnerabilities. Consider engaging security experts for this purpose.
  • Sandboxing and Isolation (Strong): Deploy strong sandboxing or isolation techniques (e.g., containerization, virtual machines, secure computing enclaves) to run the wavefunctioncollapse library in a highly restricted environment. This limits the impact of successful exploits by containing the attacker's access.
  • Web Application Firewall (WAF) with Deep Packet Inspection (Limited Effectiveness): While WAFs are generally less effective against zero-day library vulnerabilities, a WAF with deep packet inspection might detect some exploit attempts based on known attack patterns or anomalous behavior. However, this should not be relied upon as a primary mitigation.
  • Memory Safety Tools and Hardening (Development/Build Pipeline): If possible and if modifying or rebuilding the library is an option, integrate memory safety tools (e.g., AddressSanitizer, MemorySanitizer) into the development and build pipeline to detect memory errors early. Apply compiler-level hardening techniques to mitigate exploitation of memory corruption vulnerabilities.