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attack-surface.md

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Attack Surface Analysis for myclabs/deepcopy

Attack Surface: Deserialization Vulnerabilities via pickle

  • Description: Exploiting vulnerabilities in Python's pickle module, which deepcopy might use internally for complex object copying, to achieve arbitrary code execution.
  • Deepcopy Contribution: deepcopy can trigger pickle serialization and deserialization when handling custom classes or objects it cannot directly copy. This reliance on pickle introduces the risk of deserializing malicious payloads if deepcopy is used on untrusted data.
  • Example: An application receives user-provided data intended to be cloned. The application uses deepcopy to create a copy of this data before processing. If an attacker provides a malicious pickle payload as input, the deepcopy operation might trigger deserialization of this payload, leading to code execution on the server.
  • Impact: Remote Code Execution (RCE). Complete compromise of the application server and potential data breaches.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Avoid Deepcopy on Untrusted Data: Do not use deepcopy on data originating from untrusted sources, especially when dealing with complex objects or custom classes that might trigger pickle usage internally by deepcopy.
    • Strict Input Validation and Sanitization: If deep copying untrusted data is absolutely necessary, implement rigorous input validation and sanitization to detect and reject potential malicious pickle payloads. Consider alternative, safer data handling methods.
    • Restrict or Disable pickle Usage: Where feasible, limit or completely disable the use of pickle within the application, particularly for handling external or user-provided data. Explore safer serialization formats.
    • Security Audits and Code Review: Conduct regular security audits and code reviews to identify and eliminate instances where deepcopy is used on potentially untrusted data, and assess the associated risks.

Attack Surface: Resource Exhaustion (Denial of Service - DoS)

  • Description: Overloading the application by triggering deep copies of extremely large, deeply nested, or computationally expensive objects, leading to excessive resource consumption and denial of service.
  • Deepcopy Contribution: deepcopy's recursive nature can be resource-intensive, especially when copying complex data structures. Using deepcopy on attacker-controlled inputs allows them to craft objects specifically designed to maximize CPU and memory usage during the deep copy process.
  • Example: An API endpoint allows users to upload configuration files which are parsed into Python objects. The application uses deepcopy to create a backup copy of the configuration object before applying changes. An attacker uploads a maliciously crafted configuration file that, when parsed, results in an extremely large and deeply nested object. The subsequent deepcopy operation consumes excessive resources, potentially causing the application to become unresponsive or crash, denying service to legitimate users.
  • Impact: Denial of Service (DoS). Application unavailability, service disruption, and potential reputational damage.
  • Risk Severity: High
  • Mitigation Strategies:
    • Input Size and Complexity Limits: Implement strict limits on the size and nesting depth of input data processed by the application. Reject requests that exceed these limits before attempting to deep copy.
    • Resource Monitoring and Alerting: Implement robust resource monitoring for CPU and memory usage. Set up alerts to detect unusual spikes that might indicate a DoS attack targeting deepcopy operations.
    • Rate Limiting and Request Throttling: Implement rate limiting on API endpoints or functionalities that involve deep copying to prevent attackers from overwhelming the application with malicious requests designed to trigger resource exhaustion.
    • Object Size and Complexity Checks in Code: Within the application logic, add checks to assess the size and complexity of objects before attempting to deep copy them. If an object exceeds predefined thresholds, avoid deep copying or handle it with alternative, less resource-intensive methods.
    • Timeouts for Deepcopy Operations: Implement timeouts for deep copy operations to prevent them from running indefinitely and consuming resources in case of extremely complex or malicious objects.