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attack-surface.md

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Attack Surface Analysis for pola-rs/polars

Attack Surface: Malicious CSV Input Parsing

  • Description: Exploiting vulnerabilities in Polars' CSV parsing logic by providing crafted CSV data.
  • How Polars Contributes: Polars provides functionalities to parse CSV files, making the application vulnerable if it processes user-supplied CSV data without proper validation.
  • Example: A user uploads a CSV file containing specially crafted rows that trigger a buffer overflow in Polars' CSV parser, potentially leading to remote code execution.
  • Impact: Denial of Service (DoS), potential data corruption, Remote Code Execution (RCE).
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Input Validation: Rigorously validate CSV structure and content before parsing. Enforce schema, data types, and acceptable ranges.
    • Resource Limits: Implement strict limits on file size and parsing time to prevent resource exhaustion.
    • Polars Version Updates: Maintain Polars library at the latest version to benefit from security patches and bug fixes.
    • Sandboxing (Advanced): Isolate CSV parsing processes in a sandboxed environment to limit the impact of potential exploits.

Attack Surface: Expression/Query Injection

  • Description: Injecting malicious expressions or queries into Polars operations when the application dynamically constructs Polars code based on user input.
  • How Polars Contributes: If the application exposes Polars' expression language or query capabilities directly or indirectly to users, it becomes vulnerable to injection attacks.
  • Example: A web application constructs a Polars filter expression based on user-provided input. A malicious user injects an expression designed to bypass access controls and exfiltrate sensitive data beyond their authorized scope.
  • Impact: Data Breach (exfiltration of sensitive data), Data Manipulation, Denial of Service (resource intensive queries), Bypass of Access Controls.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Avoid Dynamic Expression Construction: Prefer parameterized queries or pre-defined, safe operations instead of dynamically building Polars expressions from user input.
    • Input Sanitization and Validation (if unavoidable): If dynamic expression construction is absolutely necessary, implement extremely strict input sanitization and validation. Use whitelisting of allowed characters and patterns.
    • Restrict Expression Capabilities: Limit the Polars functions and operations available in user-provided expressions to a safe subset.
    • Principle of Least Privilege: Ensure Polars operations are executed with the minimum necessary data access permissions.

Attack Surface: Resource Exhaustion via Complex Operations

  • Description: Causing Denial of Service by triggering computationally expensive Polars operations through legitimate application functionalities.
  • How Polars Contributes: Polars, while efficient, can still consume significant resources for complex operations, especially on large datasets. Uncontrolled operations can lead to DoS.
  • Example: A user initiates a request that triggers a very large join operation in Polars on massive datasets without appropriate filtering, causing the server to exhaust memory and become unresponsive.
  • Impact: Denial of Service (DoS), application unavailability.
  • Risk Severity: High
  • Mitigation Strategies:
    • Resource Limits: Implement and enforce resource limits (CPU time, memory usage) for all Polars operations.
    • Query Complexity Limits: Define and enforce limits on the complexity of user-initiated queries (e.g., maximum dataset sizes, join complexity, aggregation depth).
    • Rate Limiting: Limit the frequency of resource-intensive operations from individual users or IP addresses.
    • Background Processing: Offload potentially long-running or resource-intensive Polars operations to background queues or dedicated processing services to prevent blocking the main application.

Attack Surface: Dependency Vulnerabilities

  • Description: Exploiting known vulnerabilities in Polars' dependencies.
  • How Polars Contributes: Polars relies on external Rust crates. Vulnerabilities in these dependencies can indirectly compromise applications using Polars.
  • Example: A critical vulnerability is discovered in a compression library used by Polars. If the application uses a Polars version with this vulnerable dependency, it becomes susceptible to exploits targeting this dependency.
  • Impact: Varies depending on the vulnerability. Can range from Denial of Service to Remote Code Execution.
  • Risk Severity: High to Critical (depending on the specific dependency vulnerability).
  • Mitigation Strategies:
    • Dependency Scanning: Regularly scan Polars and its dependencies for known vulnerabilities using security scanning tools and vulnerability databases.
    • Polars Version Updates: Keep Polars and its dependencies updated to the latest versions to incorporate security patches.
    • Dependency Management: Employ robust dependency management practices, including pinning dependency versions and regularly auditing and updating dependencies.