attack-tree.md

Attack Tree Analysis for ankane/searchkick

Objective: Compromise application data or functionality through vulnerabilities in Searchkick or its interaction with Elasticsearch. (Focused on High-Risk Paths)

Attack Tree Visualization

Attack Goal: Compromise Application via Searchkick (High-Risk Focus)

├── OR [HIGH RISK PATH] 2: Exploit Elasticsearch Server Vulnerabilities (via Searchkick) [HIGH RISK PATH]
│   ├── [CRITICAL NODE] 2.1: Elasticsearch Server Misconfiguration [CRITICAL NODE]
│   │   ├── [CRITICAL NODE] 2.1.1: Unsecured Elasticsearch Access [CRITICAL NODE]
│   │   │   ├── [CRITICAL NODE] 2.1.1.1: Publicly Accessible Elasticsearch Instance [CRITICAL NODE]
│   │   │   │   └── Action: Firewall Elasticsearch, restrict access to application servers only.
│   │   │   │   └── Insight: Never expose Elasticsearch directly to the public internet.
│   │   │   ├── [CRITICAL NODE] 2.1.1.2: Weak or Default Elasticsearch Credentials [CRITICAL NODE]
│   │   │   │   └── Action: Set strong, unique credentials for Elasticsearch users.
│   │   │   │   └── Insight: Implement robust authentication and authorization in Elasticsearch.
│   │   ├── [HIGH RISK NODE] 2.1.2: Elasticsearch Version Vulnerabilities [HIGH RISK NODE]
│   │   │   ├── [HIGH RISK NODE] 2.1.2.1: Exploit Known Elasticsearch CVEs [HIGH RISK NODE]
│   │   │   │   └── Action: Regularly update Elasticsearch to the latest secure version.
│   │   │   │   └── Insight: Subscribe to Elasticsearch security advisories.

├── OR [HIGH RISK PATH] 3: Exploit Application's Misuse of Searchkick Features [HIGH RISK PATH]
│   ├── [CRITICAL NODE] 3.1: Elasticsearch Injection via Unsanitized Search Queries [CRITICAL NODE]
│   │   ├── [CRITICAL NODE] 3.1.1: Construct Malicious Search Queries via User Input [CRITICAL NODE]
│   │   │   ├── [CRITICAL NODE] 3.1.1.1: Direct Parameter Injection in Search Queries [CRITICAL NODE]
│   │   │   │   └── Action: Sanitize and validate all user inputs used in search queries.
│   │   │   │   └── Insight: Treat user input as untrusted and always sanitize.
│   │   ├── [HIGH RISK NODE] 3.3.2: Elasticsearch Cluster Overload [HIGH RISK NODE]
│   │   │   ├── [HIGH RISK NODE] 3.3.2.1: Flooding Elasticsearch with Search Requests [HIGH RISK NODE]
│   │   │   │   └── Action: Implement rate limiting on search requests at the application level.
│   │   │   │   └── Insight: Protect Elasticsearch from excessive search traffic.

Attack Tree Path: High-Risk Path 2: Exploit Elasticsearch Server Vulnerabilities (via Searchkick)

This path focuses on compromising the Elasticsearch server that Searchkick interacts with. Even if the Searchkick gem itself is secure, vulnerabilities in the Elasticsearch server or its configuration can be exploited through the application's Searchkick integration.

• Critical Node 2.1: Elasticsearch Server Misconfiguration
  • This is a broad category encompassing various misconfigurations that can weaken Elasticsearch security. Misconfigurations are often easier to exploit than code vulnerabilities.
    • Critical Node 2.1.1: Unsecured Elasticsearch Access
      • This is a highly critical issue as it directly grants unauthorized access to the Elasticsearch server and its data.
        • Critical Node 2.1.1.1: Publicly Accessible Elasticsearch Instance
          • Attack Vector: An attacker can directly access the Elasticsearch instance over the internet without any authentication or authorization. This is often due to misconfigured firewalls or network settings.
          • Impact: Full read and write access to all data in Elasticsearch. Attackers can steal sensitive data, modify or delete data, or use Elasticsearch as a staging ground for further attacks.
          • Mitigation: Implement strict firewall rules to restrict access to Elasticsearch only from authorized application servers. Never expose Elasticsearch directly to the public internet.
        • Critical Node 2.1.1.2: Weak or Default Elasticsearch Credentials
          • Attack Vector: Elasticsearch is protected by authentication, but weak or default credentials (like elastic:changeme) are used. Attackers can easily guess or brute-force these credentials.
          • Impact: Full read and write access to all data in Elasticsearch, similar to public access.
          • Mitigation: Set strong, unique passwords for all Elasticsearch users, especially the elastic superuser. Enforce password complexity policies. Implement robust authentication mechanisms.
    • High Risk Node 2.1.2: Elasticsearch Version Vulnerabilities
      • Outdated Elasticsearch versions may contain known security vulnerabilities (CVEs).
        • High Risk Node 2.1.2.1: Exploit Known Elasticsearch CVEs
          • Attack Vector: Attackers identify the Elasticsearch version used by the application (often through error messages or fingerprinting). They then search for known CVEs affecting that version and use publicly available exploits to compromise the server.
          • Impact: Depending on the CVE, impact can range from information disclosure and denial of service to remote code execution on the Elasticsearch server, potentially leading to full system compromise and data breaches.
          • Mitigation: Regularly update Elasticsearch to the latest stable and patched version. Subscribe to Elasticsearch security advisories to stay informed about new vulnerabilities.

Attack Tree Path: High-Risk Path 3: Exploit Application's Misuse of Searchkick Features

This path focuses on vulnerabilities arising from how the application code uses Searchkick, even if Searchkick and Elasticsearch themselves are properly configured and updated.

• Critical Node 3.1: Elasticsearch Injection via Unsanitized Search Queries

  • This is a critical vulnerability where user-controlled input is directly incorporated into Elasticsearch queries without proper sanitization or parameterization.
    • Critical Node 3.1.1: Construct Malicious Search Queries via User Input
      • Attackers manipulate user input to inject malicious Elasticsearch query syntax.
        • Critical Node 3.1.1.1: Direct Parameter Injection in Search Queries
          • Attack Vector: The application directly concatenates user input into the Elasticsearch query string or DSL without proper escaping or parameterization. Attackers can inject arbitrary Elasticsearch query clauses, operators, or functions.
          • Impact: Attackers can bypass intended search logic, retrieve unauthorized data, modify or delete data in Elasticsearch, or potentially trigger denial of service or even remote code execution (in rare cases, depending on Elasticsearch configuration and vulnerabilities).
          • Mitigation: Crucially sanitize and validate all user inputs used in search queries. Use parameterized queries or query builders provided by Searchkick in a safe manner. Avoid raw string interpolation when constructing queries. Treat all user input as untrusted.

• High Risk Node 3.3.2: Elasticsearch Cluster Overload

  • Attackers can intentionally overload the Elasticsearch cluster, causing denial of service.
    • High Risk Node 3.3.2.1: Flooding Elasticsearch with Search Requests
      • Attack Vector: Attackers send a large volume of search requests to the application, overwhelming the Elasticsearch cluster's resources (CPU, memory, network). This can be done using botnets or simple scripts.
      • Impact: Denial of service, making the application and search functionality unavailable to legitimate users. Performance degradation for all users. Potential for Elasticsearch cluster instability or crashes.
      • Mitigation: Implement rate limiting on search requests at the application level. Use techniques like CAPTCHA to differentiate between legitimate users and bots. Monitor Elasticsearch performance and implement resource limits within Elasticsearch.