Objective: Compromise application using Polars via High-Risk and Critical Vulnerabilities.
Compromise Application via Polars Exploitation [CRITICAL] ├───[AND]─> Exploit Polars Vulnerabilities [CRITICAL] │ ├───[OR]─> Data Injection Attacks [CRITICAL] │ │ ├───> Malicious Input Data (CSV, JSON, Parquet, etc.) [CRITICAL] │ │ │ └───> Malicious File Content (e.g., crafted Parquet to trigger parser bugs) [CRITICAL] │ │ │ └───> Denial of Service via Parser Exploitation [CRITICAL] │ ├───[OR]─> Exploiting Vulnerabilities in Polars Dependencies [CRITICAL] │ │ └───> Exploit vulnerable dependency to compromise Polars or application [CRITICAL] │ ├───[OR]─> Denial of Service (DoS) Attacks against Polars [CRITICAL] │ │ ├───> Resource Exhaustion [CRITICAL] │ │ │ ├───> Large Data Input [CRITICAL] │ │ │ │ ├───> Send extremely large files to be processed by Polars [HIGH-RISK PATH] │ │ │ │ └───> Repeatedly trigger operations on large datasets [HIGH-RISK PATH] │ │ │ ├───> Complex Queries [CRITICAL] │ │ │ │ ├───> Craft computationally expensive Polars queries [HIGH-RISK PATH] │ │ │ │ └───> Trigger these queries repeatedly [HIGH-RISK PATH] │ ├───[OR]─> Error Message Information Leakage [CRITICAL] │ │ └───> Application exposes detailed Polars error messages to users [HIGH-RISK PATH]
Attack Tree Path: Send extremely large files to be processed by Polars [HIGH-RISK PATH]
Attack Vector: Attacker uploads or sends extremely large data files (CSV, Parquet, etc.) to the application, which are then processed by Polars. Impact: Application becomes slow or unresponsive due to memory exhaustion or disk space filling up. Can lead to service unavailability. Mitigation: Implement strict file size limits on uploads. Validate file sizes before processing. Implement resource quotas for Polars processes.
Attack Tree Path: Repeatedly trigger operations on large datasets [HIGH-RISK PATH]
Attack Vector: Attacker repeatedly sends requests that cause Polars to process large datasets, even if individual datasets are not excessively large. Impact: Cumulative resource exhaustion over time, leading to application slowdown or crash. Mitigation: Rate limiting on API endpoints that trigger Polars processing. Implement queueing mechanisms to manage processing load.
Attack Tree Path: Craft computationally expensive Polars queries [HIGH-RISK PATH]
Attack Vector: Attacker crafts and sends complex Polars queries (e.g., involving many joins, aggregations, or custom functions) that are resource-intensive to execute. Impact: CPU exhaustion, slow response times, potential service degradation for other users. Mitigation: Query complexity analysis and limits. Implement timeouts for long-running queries. Optimize Polars query logic where possible.
Attack Tree Path: Trigger these queries repeatedly [HIGH-RISK PATH]
Attack Vector: Attacker repeatedly sends computationally expensive Polars queries to amplify the resource exhaustion impact. Impact: Severe CPU overload, application unresponsiveness, potential service outage. Mitigation: Rate limiting on query execution. Implement request throttling. Use caching mechanisms for frequently executed queries.
Attack Vector: Application's error handling mechanism directly exposes detailed Polars error messages to users, potentially revealing sensitive information. Impact: Information disclosure of internal file paths, data structures, or potentially even snippets of data processed by Polars. Mitigation: Implement generic error messages for users in production. Log detailed errors securely for debugging purposes only. Sanitize error messages before displaying them to users.