attack-tree.md

Attack Tree Analysis for openinterpreter/open-interpreter

Objective: Gain Unauthorized System Access and Control via Open Interpreter Exploitation.

Attack Tree Visualization

[CRITICAL NODE] Compromise Application System via Open Interpreter
└───[AND] [CRITICAL NODE] Exploit Open Interpreter Functionality
    ├───[OR] [HIGH-RISK PATH] Exploit LLM Interaction
    │   └───[AND] [HIGH-RISK PATH] Prompt Injection to Execute Malicious Code
    │       ├───[OR] [HIGH-RISK PATH] Direct Prompt Injection
    │       │   └─── Craft malicious prompt to directly instruct LLM to execute code
    │       └───[OR] Indirect Prompt Injection
    │           └─── Inject malicious content into data sources accessed by LLM, leading to code execution
    ├───[OR] [HIGH-RISK PATH] Exploit Code Execution Feature
    │   └───[AND] [HIGH-RISK PATH] Supply Malicious Code for Execution
    │       ├───[OR] [HIGH-RISK PATH] Via LLM-Generated Code Manipulation
    │       │   └─── Influence LLM to generate malicious code through crafted prompts or input data
    │       └───[OR] [CRITICAL NODE] Via Direct Code Injection (if application allows)
    │           └─── If application allows direct code input to Open Interpreter, inject malicious code directly
    └───[OR] [HIGH-RISK PATH] Exploit Misconfiguration or Insecure Setup
        ├───[AND] [HIGH-RISK PATH] Overly Permissive Permissions
        │   └─── Open Interpreter running with excessive privileges, allowing broader system access
        ├───[AND] [HIGH-RISK PATH] Insecure API Key Management (if applicable)
        │   └─── If Open Interpreter uses API keys, insecure storage or exposure of these keys
        └───[AND] [HIGH-RISK PATH] Lack of Input Validation/Sanitization in Application
            └─── Application fails to properly sanitize input before passing it to Open Interpreter, enabling injection attacks

Attack Tree Path: [CRITICAL NODE] Compromise Application System via Open Interpreter

• Description: This is the root goal of the attacker. Successful exploitation of Open Interpreter's functionalities or misconfigurations leads to compromising the application system.
• Attack Vectors (Sub-nodes):
  • Exploit Open Interpreter Functionality
  • Exploit Misconfiguration or Insecure Setup

Attack Tree Path: [CRITICAL NODE] Exploit Open Interpreter Functionality

• Description: Attackers target the core functionalities of Open Interpreter, specifically its interaction with the LLM and its code execution capabilities, to gain unauthorized access.
• Attack Vectors (Sub-nodes):
  • Exploit LLM Interaction
  • Exploit Code Execution Feature

Attack Tree Path: [HIGH-RISK PATH] Exploit LLM Interaction

• Description: Attackers manipulate the interaction with the underlying Large Language Model (LLM) to achieve malicious goals. This primarily focuses on Prompt Injection attacks.
• Attack Vectors (Sub-nodes):
  • Prompt Injection to Execute Malicious Code
  • Information Leakage via LLM Prompts (While Information Leakage is marked as Medium Impact, Prompt Injection for Code Execution is High Impact and thus included under this High-Risk Path)

Attack Tree Path: [HIGH-RISK PATH] Prompt Injection to Execute Malicious Code

• Description: Attackers aim to inject malicious instructions into prompts provided to the LLM, causing it to generate and execute unintended code that compromises the system.
• Attack Vectors (Sub-nodes):
  • [HIGH-RISK PATH] Direct Prompt Injection:
    • Attack: Crafting prompts that directly instruct the LLM to execute malicious code.
    • Example: "Run this Python code: import os; os.system('...')"
    • Mitigation: Robust input sanitization, prompt filtering, restrictive prompt design, Content Security Policies for prompts.
  • Indirect Prompt Injection:
    • Attack: Injecting malicious content into external data sources that the LLM accesses, leading to the LLM generating and executing malicious code based on this poisoned data.
    • Example: Modifying a file that the LLM reads with malicious code disguised as data.
    • Mitigation: Strict control and sanitization of all data sources accessed by the LLM, input validation for data sources, principle of least privilege for data access.

Attack Tree Path: [HIGH-RISK PATH] Exploit Code Execution Feature

• Description: Attackers directly target the code execution capabilities of Open Interpreter, attempting to supply and execute malicious code.
• Attack Vectors (Sub-nodes):
  • [HIGH-RISK PATH] Supply Malicious Code for Execution:
    • [HIGH-RISK PATH] Via LLM-Generated Code Manipulation:
      • Attack: Influencing the LLM through prompts or input data to generate malicious code as part of its intended output.
      • Example: Crafting prompts that subtly guide the LLM to generate vulnerable or malicious code.
      • Mitigation: Code review and analysis of LLM-generated code before execution, static analysis tools for generated code, runtime monitoring of executed code.
    • [CRITICAL NODE] Via Direct Code Injection (if application allows):
      • Attack: Directly injecting malicious code into the application if it allows users to provide code input that is then executed by Open Interpreter.
      • Example: Application feature: "Enter Python code to execute".
      • Mitigation: Strongly discourage/remove this feature. If unavoidable, implement extremely strict input validation, sandboxing, and code execution monitoring.

Attack Tree Path: [HIGH-RISK PATH] Exploit Misconfiguration or Insecure Setup

• Description: Attackers exploit common misconfigurations or insecure deployment practices to compromise the application.
• Attack Vectors (Sub-nodes):
  • [HIGH-RISK PATH] Overly Permissive Permissions:
    • Attack: Running Open Interpreter with excessive privileges (e.g., root, sudo), allowing broader system access if compromised.
    • Example: Running Open Interpreter as root user.
    • Mitigation: Run Open Interpreter with the minimum necessary privileges, use dedicated user accounts with restricted permissions, principle of least privilege.
  • [HIGH-RISK PATH] Insecure API Key Management (if applicable):
    • Attack: Insecure storage or exposure of API keys used by Open Interpreter or the application, leading to unauthorized access to services or further compromise.
    • Example: Hardcoding API keys in application code, storing keys in plain text configuration files.
    • Mitigation: Secure API key storage and management (environment variables, secrets management systems, encrypted configuration files), avoid hardcoding keys.
  • [HIGH-RISK PATH] Lack of Input Validation/Sanitization in Application:
    • Attack: Application failing to properly validate and sanitize user input before passing it to Open Interpreter, enabling injection attacks (prompt injection, code injection).
    • Example: Directly passing user-provided text to Open Interpreter without any checks.
    • Mitigation: Robust input validation and sanitization on the application side for all data passed to Open Interpreter, use allow-lists and deny-lists for allowed commands and inputs.