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Attack Tree Analysis for pola-rs/polars

Objective: Compromise the application using Polars to achieve one or more of the following: Data Exfiltration, Denial of Service (DoS), or Arbitrary Code Execution (ACE).

Attack Tree Visualization

Compromise Application via Polars
├── 1. Data Exfiltration
│   ├── 1.1 Exploit Polars' Data Serialization/Deserialization [HIGH-RISK]
│   │   └── 1.1.3 CSV Format Vulnerability
│   │       ├── 1.1.3.1 Inject malicious CSV data (M/M/L/I/E)
│   │       └── 1.1.3.2 Craft CSV metadata (M/M/L/I/E)
│   ├── 1.2  Bypass Access Controls via Polars Queries [HIGH-RISK]
│   │   ├── 1.2.1  SQL Injection (if Polars interacts with a database)
│   │   │   └── 1.2.1.1  Inject malicious SQL [CRITICAL] (M/H/L/I/E)
│   │   └── 1.2.2  Expression Language Injection
│   │       └── 1.2.2.1  Inject malicious expressions (M/H/M/A/M)
├── 2. Denial of Service (DoS) [HIGH-RISK]
│   ├── 2.1  Resource Exhaustion [HIGH-RISK]
│   │   ├── 2.1.1  Large Data Input
│   │   │   └── 2.1.1.1  Submit extremely large datasets [CRITICAL] (H/M/VL/N/VE)
│   │   ├── 2.1.2  Complex Query Input
│   │   │   └── 2.1.2.1  Craft highly complex queries (M/M/L/I/E)
│   │   └── 2.1.4  Trigger Excessive Disk I/O
│   │       └── 2.1.4.1  Force data spilling to disk (M/M/L/I/E)
└── 3. Arbitrary Code Execution (ACE)
    ├── 3.3  Deserialization Vulnerabilities [HIGH-RISK]
        └── 3.3.1  Unsafe deserialization (e.g., Pickle)
            └── 3.3.1.1  Inject malicious serialized objects [CRITICAL] (M/VH/M/A/M)

Attack Tree Path: 1. Data Exfiltration

  • 1.1 Exploit Polars' Data Serialization/Deserialization (CSV Format Vulnerability) [HIGH-RISK]

    • 1.1.3.1 Inject malicious CSV data:
      • Description: The attacker provides a specially crafted CSV file or input stream that contains malicious data designed to exploit vulnerabilities in Polars' CSV parsing logic. This could involve overflowing buffers, injecting control characters, or manipulating data types.
      • Likelihood: Medium
      • Impact: Medium
      • Effort: Low
      • Skill Level: Intermediate
      • Detection Difficulty: Easy
    • 1.1.3.2 Craft CSV metadata:
      • Description: The attacker manipulates the metadata associated with the CSV data (e.g., column names, data types, delimiters) to cause Polars to misinterpret the data or trigger unexpected behavior. This could lead to information disclosure or other security issues.
      • Likelihood: Medium
      • Impact: Medium
      • Effort: Low
      • Skill Level: Intermediate
      • Detection Difficulty: Easy

  • 1.2 Bypass Access Controls via Polars Queries [HIGH-RISK]

    • 1.2.1.1 Inject malicious SQL [CRITICAL]
      • Description: If Polars interacts with a database and the application doesn't use parameterized queries, the attacker can inject malicious SQL code through Polars' query interface. This allows the attacker to bypass authentication, authorization, or directly access and exfiltrate sensitive data from the database.
      • Likelihood: Medium (depends on application configuration)
      • Impact: High
      • Effort: Low
      • Skill Level: Intermediate
      • Detection Difficulty: Easy (with proper logging and intrusion detection)
    • 1.2.2.1 Inject malicious expressions
      • Description: If Polars uses a custom expression language and the application doesn't properly sanitize user input, the attacker can inject malicious expressions to access unauthorized data or perform unauthorized actions.
      • Likelihood: Medium
      • Impact: High
      • Effort: Medium
      • Skill Level: Advanced
      • Detection Difficulty: Medium

Attack Tree Path: 2. Denial of Service (DoS)

  • 2.1 Resource Exhaustion [HIGH-RISK]

    • 2.1.1.1 Submit extremely large datasets [CRITICAL]
      • Description: The attacker sends an extremely large dataset to Polars, exceeding the available memory and causing the application to crash or become unresponsive (Out-of-Memory error).
      • Likelihood: High
      • Impact: Medium
      • Effort: Very Low
      • Skill Level: Novice
      • Detection Difficulty: Very Easy
    • 2.1.2.1 Craft highly complex queries
      • Description: The attacker submits a Polars query that is intentionally designed to be computationally expensive, consuming excessive CPU time and potentially causing the application to become unresponsive.
      • Likelihood: Medium
      • Impact: Medium
      • Effort: Low
      • Skill Level: Intermediate
      • Detection Difficulty: Easy
    • 2.1.4.1 Force data spilling to disk
      • Description: The attacker crafts input or queries that force Polars to spill large amounts of intermediate data to disk, overwhelming the storage system and causing performance degradation or denial of service.
      • Likelihood: Medium
      • Impact: Medium
      • Effort: Low
      • Skill Level: Intermediate
      • Detection Difficulty: Easy

Attack Tree Path: 3. Arbitrary Code Execution (ACE)

  • 3.3 Deserialization Vulnerabilities [HIGH-RISK]

    • 3.3.1.1 Inject malicious serialized objects [CRITICAL]
      • Description: If the application uses unsafe deserialization mechanisms (like Python's pickle module) with user-provided data, the attacker can inject a malicious serialized object that, when deserialized, executes arbitrary code on the server. This gives the attacker full control over the application.
      • Likelihood: Medium (depends on application configuration)
      • Impact: Very High
      • Effort: Medium
      • Skill Level: Advanced
      • Detection Difficulty: Medium