attack-tree.md

Attack Tree Analysis for apache/airflow

Objective: Compromise the Application and its Data via Airflow Exploitation (Focus on High-Risk Paths)

Attack Tree Visualization

Compromise Application via Airflow
├─── OR ─ Exploit Airflow Webserver Vulnerabilities **[CRITICAL NODE - Entry Point]**
│   ├─── AND ─ Gain Unauthorized Access to Webserver **[CRITICAL NODE - Entry Point]**
│   │   ├─── OR ─ Exploit Authentication Bypass **[HIGH-RISK PATH START]**
│   │   │   ├─── Default Credentials (if not changed) **[CRITICAL NODE - Default Credentials]**
│   │   └─── AND ─ Execute Arbitrary Code via Webserver **[HIGH-RISK PATH CONTINUES]**
│   │   └─── AND ─ Access Sensitive Information via Webserver **[HIGH-RISK PATH ENDS - Webserver Compromise]**
├─── OR ─ Exploit Airflow Scheduler Vulnerabilities
│   └─── AND ─ Manipulate DAG Scheduling
│       ├─── OR ─ Modify DAG Definitions (if attacker gains access to DAG storage or version control) **[HIGH-RISK PATH START]**
│       │   ├─── Inject malicious tasks into existing DAGs **[HIGH-RISK PATH CONTINUES]**
│       │   └─── Replace legitimate DAGs with malicious ones **[HIGH-RISK PATH CONTINUES]**
├─── OR ─ Exploit Airflow Executor Vulnerabilities
│   ├─── AND ─ Execute Arbitrary Code via Executor **[HIGH-RISK PATH START]**
│   │   ├─── OR ─ Task Code Injection **[HIGH-RISK PATH CONTINUES]**
│   │   │   ├─── Vulnerabilities in DAG Code (if DAGs are written insecurely and attacker can influence DAG creation/modification) **[CRITICAL NODE - Insecure DAG Code]**
│   │   │   ├─── Exploiting Jinja Templating Vulnerabilities in DAGs (if used insecurely) **[CRITICAL NODE - Insecure Jinja Usage]**
│   │   │   └─── Command Injection in Operators (if operators are used insecurely and attacker can control parameters) **[CRITICAL NODE - Insecure Operator Usage]**
│   └─── AND ─ Access Sensitive Data via Executor **[HIGH-RISK PATH ENDS - Executor Compromise]**
├─── OR ─ Exploit Airflow Database (Metadata DB) Vulnerabilities **[CRITICAL NODE - Metadata DB]**
│   ├─── AND ─ Gain Unauthorized Access to Database **[HIGH-RISK PATH START]**
│   │   ├─── OR ─ Credential Theft **[HIGH-RISK PATH CONTINUES]**
│   │   │   ├─── Exploiting insecure configuration files or environment variables **[CRITICAL NODE - Insecure DB Credential Storage]**
│   │   └─── AND ─ Manipulate Data in Database **[HIGH-RISK PATH CONTINUES]**
│   │   └─── AND ─ Data Exfiltration **[HIGH-RISK PATH ENDS - Database Compromise]**
├─── OR ─ Exploit Airflow Connections and Variables **[CRITICAL NODE - Connections & Variables]**
│   ├─── AND ─ Steal Connection Credentials **[HIGH-RISK PATH START]**
│   │   ├─── OR ─ Unencrypted Storage of Connections **[CRITICAL NODE - Unencrypted Connections]**
│   │   │   ├─── Connections stored in plaintext in database (if not using Fernet key or secrets backend) **[HIGH-RISK PATH CONTINUES]**
│   │   │   └─── Connections exposed in configuration files or environment variables **[HIGH-RISK PATH CONTINUES]**
│   └─── AND ─ Manipulate Connections and Variables **[HIGH-RISK PATH ENDS - Credential Theft & Manipulation]**
└─── OR ─ Supply Chain Attacks on Airflow Dependencies/Plugins **[CRITICAL NODE - Supply Chain]**
    ├─── AND ─ Compromise Airflow Dependencies **[HIGH-RISK PATH START]**
    │   ├─── OR ─ Vulnerable Python Packages **[HIGH-RISK PATH CONTINUES]**
    │   │   ├─── Exploiting known vulnerabilities in Airflow's Python dependencies (e.g., via `pip install -r requirements.txt` with compromised requirements) **[HIGH-RISK PATH CONTINUES]**
    │   │   └─── Dependency Confusion attacks (if using private PyPI repositories) **[HIGH-RISK PATH CONTINUES]**
    │   └─── OR ─ Malicious Python Packages **[HIGH-RISK PATH CONTINUES]**
    │       ├─── Installing backdoored or malicious Python packages that Airflow depends on **[HIGH-RISK PATH CONTINUES]**
    │       └─── Typosquatting attacks during dependency installation **[HIGH-RISK PATH ENDS - Dependency Compromise]**
    └─── AND ─ Compromise Airflow Plugins **[HIGH-RISK PATH START]**
        ├─── OR ─ Malicious Plugins **[HIGH-RISK PATH CONTINUES]**
        │   ├─── Installing untrusted or malicious Airflow plugins **[HIGH-RISK PATH CONTINUES]**
        │   └─── Plugins containing backdoors or vulnerabilities **[HIGH-RISK PATH CONTINUES]**
        └─── OR ─ Vulnerable Plugins **[HIGH-RISK PATH ENDS - Plugin Compromise]**

Attack Tree Path: 1. Exploit Airflow Webserver Vulnerabilities [CRITICAL NODE - Entry Point]:

• Gain Unauthorized Access to Webserver [CRITICAL NODE - Entry Point]:
  • Exploit Authentication Bypass [HIGH-RISK PATH START]:
    • Default Credentials (if not changed) [CRITICAL NODE - Default Credentials]:
      • Attack Vector: Attacker attempts to log in to the Airflow webserver using default usernames and passwords (e.g., admin/admin, airflow/airflow).
      • Impact: Full administrative access to the Airflow webserver, allowing control over DAGs, connections, variables, and potentially the entire Airflow environment.
      • Mitigation: Immediately change default credentials upon installation. Enforce strong password policies.
  • Execute Arbitrary Code via Webserver [HIGH-RISK PATH CONTINUES]:
    • Attack Vector: After gaining unauthorized access, attacker exploits web application vulnerabilities to execute arbitrary code on the webserver. This could include:
      • XSS (Cross-Site Scripting): Injecting malicious scripts into web pages viewed by other users, potentially leading to session hijacking or further attacks.
      • SSRF (Server-Side Request Forgery): Manipulating the webserver to make requests to internal resources, potentially accessing sensitive data or internal systems.
      • API Injection: Exploiting vulnerabilities in the REST API to inject commands or code.
  • Access Sensitive Information via Webserver [HIGH-RISK PATH ENDS - Webserver Compromise]:
    • Attack Vector: After gaining unauthorized access or executing code, attacker uses the webserver to access sensitive information:
      • Information Disclosure: Exploiting vulnerabilities or misconfigurations to expose sensitive configuration files, logs, DAG definitions, connection details, or variables.
      • IDOR (Insecure Direct Object Reference): Accessing resources (DAGs, logs, connections) without proper authorization checks.

Attack Tree Path: 2. Manipulate DAG Scheduling (via DAG Storage/Version Control) [HIGH-RISK PATH START]:

• Modify DAG Definitions (if attacker gains access to DAG storage or version control) [HIGH-RISK PATH START]:
  • Attack Vector: Attacker gains unauthorized access to the storage location of DAG files (e.g., shared filesystem, Git repository) or the version control system used for DAG management.
  • Inject malicious tasks into existing DAGs [HIGH-RISK PATH CONTINUES]:
    • Attack Vector: Attacker modifies existing DAG files to insert malicious tasks. These tasks can execute arbitrary code within the Airflow environment when the DAG runs.
    • Impact: Remote code execution within the Airflow executor environment, data manipulation, data exfiltration, disruption of workflows.
    • Mitigation: Implement strict access control to DAG storage and version control. Use version control with code review processes for DAG changes.
  • Replace legitimate DAGs with malicious ones [HIGH-RISK PATH CONTINUES]:
    • Attack Vector: Attacker replaces legitimate DAG files with completely malicious DAGs. These malicious DAGs can execute arbitrary code and perform malicious actions when scheduled.
    • Impact: Complete control over Airflow workflows, data manipulation, data exfiltration, disruption of operations.
    • Mitigation: Implement strict access control to DAG storage and version control. Use version control with code review processes for DAG changes. Implement DAG integrity checks.

Attack Tree Path: 3. Execute Arbitrary Code via Executor [HIGH-RISK PATH START]:

• Task Code Injection [HIGH-RISK PATH CONTINUES]:
  • Vulnerabilities in DAG Code (if DAGs are written insecurely and attacker can influence DAG creation/modification) [CRITICAL NODE - Insecure DAG Code]:
    • Attack Vector: DAGs are written with insecure coding practices, such as:
      • Command Injection: DAG code directly executes system commands using user-controlled inputs without proper sanitization.
      • SQL Injection: DAG code constructs SQL queries using user-controlled inputs without proper parameterization.
      • Insecure Deserialization: DAG code deserializes untrusted data, leading to code execution.
    • Impact: Remote code execution within the Airflow executor environment.
    • Mitigation: Educate developers on secure coding practices for DAGs. Implement code review and static analysis for DAGs. Sanitize inputs and outputs in DAG code.
  • Exploiting Jinja Templating Vulnerabilities in DAGs (if used insecurely) [CRITICAL NODE - Insecure Jinja Usage]:
    • Attack Vector: DAGs use Jinja templating insecurely, especially when incorporating user-controlled inputs into Jinja templates without proper sanitization. This can lead to Jinja template injection vulnerabilities.
    • Impact: Remote code execution within the Airflow executor environment.
    • Mitigation: Avoid using user-controlled inputs directly in Jinja templates. Sanitize inputs before using them in Jinja templates. Use secure Jinja templating practices.
  • Command Injection in Operators (if operators are used insecurely and attacker can control parameters) [CRITICAL NODE - Insecure Operator Usage]:
    • Attack Vector: DAGs use operators in an insecure manner, where operator parameters are directly controlled by attackers (e.g., via manipulated variables or connections) and lead to command injection vulnerabilities within the operator execution.
    • Impact: Remote code execution within the Airflow executor environment.
    • Mitigation: Validate and sanitize operator parameters, especially when derived from external sources. Use secure operators and avoid writing custom operators that introduce vulnerabilities.

Attack Tree Path: 4. Exploit Airflow Database (Metadata DB) Vulnerabilities [CRITICAL NODE - Metadata DB]:

• Gain Unauthorized Access to Database [HIGH-RISK PATH START]:
  • Credential Theft [HIGH-RISK PATH CONTINUES]:
    • Exploiting insecure configuration files or environment variables [CRITICAL NODE - Insecure DB Credential Storage]:
      • Attack Vector: Database credentials (username, password) for the Airflow metadata database are stored in plaintext in configuration files or environment variables accessible to attackers.
      • Impact: Full unauthorized access to the Airflow metadata database.
      • Mitigation: Never store database credentials in plaintext in configuration files or environment variables. Use secure secrets management solutions (Airflow secrets backends, Vault, cloud provider secrets managers).
  • Manipulate Data in Database [HIGH-RISK PATH CONTINUES]:
    • Attack Vector: After gaining database access, attacker directly manipulates data in the metadata database using SQL queries.
    • Data Modification [HIGH-RISK PATH CONTINUES]:
      • Attack Vector: Modify DAG definitions, task states, connections, variables, users, roles, etc., in the database to disrupt operations, inject malicious code, or gain further access.
      • Impact: Disruption of workflows, injection of malicious code into DAGs, manipulation of application logic, privilege escalation.
    • Data Exfiltration [HIGH-RISK PATH ENDS - Database Compromise]:
      • Attack Vector: Steal sensitive data from the database, including connection details, variables, DAG definitions, task metadata, user information, and audit logs.
      • Impact: Credential compromise, sensitive data leakage, reconnaissance for further attacks, understanding application workflows and data flows.

Attack Tree Path: 5. Exploit Airflow Connections and Variables [CRITICAL NODE - Connections & Variables]:

• Steal Connection Credentials [HIGH-RISK PATH START]:
  • Unencrypted Storage of Connections [CRITICAL NODE - Unencrypted Connections]:
    • Connections stored in plaintext in database (if not using Fernet key or secrets backend) [HIGH-RISK PATH CONTINUES]:
      • Attack Vector: Airflow connections are stored in the metadata database in plaintext without encryption (e.g., if Fernet key is not configured or secrets backend is not used).
      • Impact: Direct exposure of credentials for external systems connected to Airflow (databases, APIs, cloud services).
      • Mitigation: Always encrypt connections at rest using Fernet key or a secure secrets backend.
    • Connections exposed in configuration files or environment variables [HIGH-RISK PATH CONTINUES]:
      • Attack Vector: Airflow connection details are mistakenly or intentionally stored in plaintext in configuration files or environment variables.
      • Impact: Direct exposure of credentials for external systems connected to Airflow.
      • Mitigation: Never store connection details in plaintext in configuration files or environment variables. Use Airflow's connection management features and secrets backends.
  • Manipulate Connections and Variables [HIGH-RISK PATH ENDS - Credential Theft & Manipulation]:
    • Attack Vector: After gaining access to modify connections and variables (e.g., via webserver access or database access), attacker manipulates them for malicious purposes.
    • Modify Connection Details:
      • Attack Vector: Redirect connections to attacker-controlled systems (e.g., malicious database, API endpoint) to intercept data or perform man-in-the-middle attacks. Inject malicious credentials into connections to gain persistent access to downstream systems.
      • Impact: Data interception, man-in-the-middle attacks, compromise of downstream systems, persistent access to external resources.
    • Modify Variables:
      • Attack Vector: Inject malicious variables or modify existing variables to alter DAG behavior, disrupt application logic, or gain unauthorized access to sensitive resources.
      • Impact: Altered DAG logic, data manipulation, disruption of application workflows, potential unauthorized access.

Attack Tree Path: 6. Supply Chain Attacks on Airflow Dependencies/Plugins [CRITICAL NODE - Supply Chain]:

• Compromise Airflow Dependencies [HIGH-RISK PATH START]:

  • Vulnerable Python Packages [HIGH-RISK PATH CONTINUES]:
    • Exploiting known vulnerabilities in Airflow's Python dependencies [HIGH-RISK PATH CONTINUES]:
      • Attack Vector: Airflow relies on numerous Python packages. Attackers exploit known vulnerabilities in these dependencies (e.g., via CVEs) to compromise the Airflow environment.
      • Impact: Remote code execution, denial of service, other vulnerabilities depending on the specific dependency.
      • Mitigation: Regularly scan dependencies for vulnerabilities using dependency scanning tools. Keep dependencies up-to-date with security patches.
    • Dependency Confusion attacks [HIGH-RISK PATH CONTINUES]:
      • Attack Vector: If using private PyPI repositories, attackers can perform dependency confusion attacks by registering packages with the same name (but malicious content) on public PyPI. If the private PyPI is not correctly prioritized, Airflow might install the malicious public package.
      • Impact: Installation of malicious packages, potential code execution, backdoor access.
      • Mitigation: Properly configure PyPI repository priorities. Use private PyPI indexes securely. Implement dependency verification and integrity checks.
  • Malicious Python Packages [HIGH-RISK PATH CONTINUES]:
    • Installing backdoored or malicious Python packages [HIGH-RISK PATH CONTINUES]:
      • Attack Vector: Attackers create and distribute backdoored or malicious Python packages that Airflow might depend on or that administrators might mistakenly install.
      • Impact: Backdoor access, data theft, complete compromise of the Airflow environment.
      • Mitigation: Only install packages from trusted sources. Perform code review and security audits of packages before installation. Use software composition analysis (SCA) tools.
    • Typosquatting attacks during dependency installation [HIGH-RISK PATH ENDS - Dependency Compromise]:
      • Attack Vector: Attackers register package names that are similar to legitimate Airflow dependencies (typosquatting). If users make typos during installation, they might install the malicious typosquatted package instead.
      • Impact: Installation of malicious packages, potential code execution, backdoor access.
      • Mitigation: Double-check package names during installation. Use dependency management tools that verify package integrity.

• Compromise Airflow Plugins [HIGH-RISK PATH START]:

  • Malicious Plugins [HIGH-RISK PATH CONTINUES]:
    • Installing untrusted or malicious Airflow plugins [HIGH-RISK PATH CONTINUES]:
      • Attack Vector: Administrators install Airflow plugins from untrusted sources or plugins that are intentionally malicious.
      • Impact: Backdoor access, code execution, complete compromise of the Airflow environment, plugin-specific vulnerabilities.
      • Mitigation: Only install plugins from trusted and vetted sources. Perform code review and security audits of plugins before installation. Implement plugin integrity checks.
    • Plugins containing backdoors or vulnerabilities [HIGH-RISK PATH CONTINUES]:
      • Attack Vector: Legitimate-looking plugins might contain unintentional vulnerabilities or intentionally introduced backdoors.
      • Impact: Remote code execution, data access, plugin-specific vulnerabilities.
      • Mitigation: Perform security audits and vulnerability scanning of plugins. Keep plugins up-to-date with security patches.
  • Vulnerable Plugins [HIGH-RISK PATH ENDS - Plugin Compromise]:
    • Exploiting known vulnerabilities in installed Airflow plugins:
      • Attack Vector: Attackers exploit known vulnerabilities (CVEs) in installed Airflow plugins.
      • Impact: Remote code execution, data access, plugin-specific vulnerabilities.
      • Mitigation: Regularly scan plugins for vulnerabilities. Keep plugins up-to-date with security patches. Implement plugin security audits.
    • Plugins with insecure code that introduces vulnerabilities:
      • Attack Vector: Plugins are developed with insecure coding practices, introducing vulnerabilities (e.g., command injection, SQL injection, XSS) into the Airflow environment.
      • Impact: Remote code execution, data access, plugin-specific vulnerabilities.
      • Mitigation: Perform code review and static analysis of plugins. Educate plugin developers on secure coding practices.