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Threat Model Analysis for pola-rs/polars

Threat: Expression Injection

  • Description: Attacker provides malicious input directly incorporated into Polars expressions (e.g., filter conditions). By crafting expressions, they can bypass security checks, access unauthorized data, or cause errors.
  • Impact: Data breach, unauthorized access, data manipulation, denial of service.
  • Polars Component Affected: Polars expression engine, functions like filter, select, groupby, agg.
  • Risk Severity: High
  • Mitigation Strategies:
    • Avoid direct user input in Polars expressions.
    • Use parameterized queries or safe expression building methods.
    • Sanitize and validate user input before expression incorporation.
    • Enforce strict input validation and whitelisting for expression components.

Threat: File Format Deserialization Vulnerabilities (e.g., Parquet, Arrow IPC)

  • Description: Attacker provides malicious files in formats like Parquet or Arrow IPC. Exploiting vulnerabilities in Polars' deserialization libraries can lead to remote code execution or denial of service.
  • Impact: Remote code execution, denial of service, data corruption.
  • Polars Component Affected: polars.read_parquet, polars.read_ipc, underlying deserialization libraries (e.g., arrow2).
  • Risk Severity: High to Critical
  • Mitigation Strategies:
    • Keep Polars and deserialization libraries updated.
    • Sanitize and validate file inputs before processing.
    • Implement file type validation and restrict allowed formats.
    • Consider sandboxing Polars processing.

Threat: Memory Exhaustion via Large Datasets

  • Description: Attacker causes the application to process excessively large datasets, leading to memory exhaustion and denial of service.
  • Impact: Denial of service, application instability.
  • Polars Component Affected: Polars core data processing engine, memory management.
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement resource limits and quotas for data processing.
    • Use Polars' chunking and streaming capabilities.
    • Monitor memory usage and implement alerts.
    • Design applications to handle large datasets gracefully.
    • Implement input size limits and validation.

Threat: apply and map_elements Code Injection

  • Description: Attacker injects malicious code into custom functions used with apply or map_elements if these functions are dynamically generated or accept unsanitized user input.
  • Impact: Code execution, data manipulation, privilege escalation.
  • Polars Component Affected: apply and map_elements functions, custom function execution.
  • Risk Severity: High to Critical
  • Mitigation Strategies:
    • Avoid dynamic generation of custom functions based on user input.
    • Strictly sanitize and validate user input if dynamic functions are necessary.
    • Thoroughly review and test custom functions.
    • Limit usage of apply and map_elements to trusted code paths.

Threat: Logic Errors in Custom Functions (apply, map_elements)

  • Description: Bugs in custom functions used with apply or map_elements can lead to data corruption or unexpected behavior, potentially causing security breaches.
  • Impact: Data corruption, unexpected application behavior, potential security breaches.
  • Polars Component Affected: apply and map_elements functions, custom function logic.
  • Risk Severity: High
  • Mitigation Strategies:
    • Thoroughly test and review custom functions.
    • Implement unit and integration tests for custom functions.
    • Follow secure coding practices in custom functions.
    • Consider code reviews for custom functions.

Threat: Unforeseen Bugs in Polars Core Logic

  • Description: Undiscovered bugs in Polars core logic could be exploited to cause data corruption, unexpected behavior, or security breaches.
  • Impact: Data corruption, unexpected application behavior, potential security breaches.
  • Polars Component Affected: Polars core data processing engine, various modules and functions.
  • Risk Severity: High to Critical (potential depending on bug nature)
  • Mitigation Strategies:
    • Stay updated with Polars releases and security advisories.
    • Report suspected bugs to the Polars team.
    • Implement robust error handling and input validation in the application.
    • Consider fuzzing or other testing techniques.