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attack-surface.md

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Attack Surface Analysis for elastic/elasticsearch

Attack Surface: 1. Network Exposure

  • Description: Unauthorized access to Elasticsearch's network ports (typically 9200 for HTTP and 9300 for transport).
    • Elasticsearch Contribution: Elasticsearch, by default, listens on network ports for communication. Misconfiguration or lack of network security can expose these ports directly to attackers.
    • Example: An attacker scans for open port 9200 on public IP addresses and finds an exposed Elasticsearch instance without authentication.
    • Impact: Complete data compromise (read, write, delete), cluster takeover, potential for remote code execution.
    • Risk Severity: Critical
    • Mitigation Strategies:
      • Firewall: Configure firewalls (host-based and network-based) to strictly limit access to ports 9200 and 9300 to only authorized IP addresses/networks.
      • Network Binding: Configure Elasticsearch to bind to a specific, internal network interface (e.g., network.host: 192.168.1.10) instead of 0.0.0.0.
      • Reverse Proxy: Use a reverse proxy (Nginx, Apache) with TLS encryption and authentication in front of Elasticsearch. This adds a layer of security and allows for more complex access control.
      • Elasticsearch Security: Enable and enforce Elasticsearch's built-in security features (X-Pack/Security). This is mandatory for production.

Attack Surface: 2. Authentication Bypass/Weak Authentication

  • Description: Accessing Elasticsearch without proper authentication or using weak/default credentials.
    • Elasticsearch Contribution: Older versions of Elasticsearch did not enable security by default. Even with security enabled, weak or default passwords can be exploited directly against the Elasticsearch API.
    • Example: An attacker uses the default elastic user with a well-known default password (or no password) to gain administrative access.
    • Impact: Complete data compromise, cluster takeover, potential for remote code execution.
    • Risk Severity: Critical
    • Mitigation Strategies:
      • Enable Security: Always enable Elasticsearch Security (X-Pack/Security).
      • Strong Passwords: Enforce strong, unique passwords for all users, including built-in accounts. Use a password manager.
      • Centralized Authentication: Integrate with external identity providers (LDAP, Active Directory, SAML, OpenID Connect) for centralized user management and stronger authentication policies, which then control access to Elasticsearch.
      • API Key Management: If using API keys, store them securely, rotate them regularly, and use restricted keys with limited privileges, all managed within Elasticsearch.

Attack Surface: 3. Authorization Failures (RBAC Issues)

  • Description: Users having excessive privileges within Elasticsearch, allowing them to access or modify data they shouldn't.
    • Elasticsearch Contribution: Elasticsearch provides Role-Based Access Control (RBAC), but it must be configured correctly within Elasticsearch. Misconfigured roles or overly permissive defaults can lead to privilege escalation.
    • Example: A user with read-only access to a specific index is able to delete documents or access other indices due to a misconfigured role within Elasticsearch.
    • Impact: Data breaches, data modification, potential for denial of service.
    • Risk Severity: High
    • Mitigation Strategies:
      • Principle of Least Privilege: Implement RBAC within Elasticsearch with the least privilege necessary. Grant only the specific permissions required.
      • Granular Roles: Define granular roles within Elasticsearch with specific index, document, and field-level permissions.
      • Regular Audits: Regularly audit user roles and permissions within Elasticsearch to ensure they are still appropriate.

Attack Surface: 4. Scripting Vulnerabilities (RCE)

  • Description: Exploitation of Elasticsearch's scripting capabilities to execute arbitrary code on the Elasticsearch server.
    • Elasticsearch Contribution: Elasticsearch allows scripting (Painless, etc.) for advanced functionality. If user-supplied input is used in scripts within Elasticsearch without proper sanitization, it can lead to Remote Code Execution (RCE) on the Elasticsearch nodes.
    • Example: An attacker injects malicious code into a search query parameter that is used directly in a Painless script within Elasticsearch, allowing them to execute commands on the Elasticsearch server.
    • Impact: Complete server compromise, data exfiltration, lateral movement within the network.
    • Risk Severity: Critical
    • Mitigation Strategies:
      • Disable Dynamic Scripting (If Possible): If dynamic scripting is not absolutely required, disable it entirely (script.allowed_types: none in elasticsearch.yml).
      • Use Painless (and Sanitize): If dynamic scripting is needed, use Painless. Crucially, sanitize and validate all user-supplied input before using it in any script within Elasticsearch. Never directly embed user input.
      • Parameterized Queries: Use parameterized queries and avoid string concatenation when building queries that include user input, specifically within the context of Elasticsearch queries.
      • Context Restrictions: Restrict the contexts in which scripts can be used (e.g., only allow scripts in specific Elasticsearch APIs).
      • Regex Limits: Use script.painless.regex.enabled: false in elasticsearch.yml or carefully control regex complexity in Painless scripts.

Attack Surface: 5. Search Query Injection

  • Description: Manipulating Elasticsearch search queries to bypass security controls or access unauthorized data.
    • Elasticsearch Contribution: Elasticsearch uses a query language (Query DSL) that can be vulnerable to injection if user input is not handled correctly when constructing queries to Elasticsearch.
    • Example: An attacker crafts a search query sent to Elasticsearch that bypasses a filter intended to restrict access to certain documents.
    • Impact: Data breaches, unauthorized data access, potential for denial of service.
    • Risk Severity: High
    • Mitigation Strategies:
      • Query DSL: Use the Elasticsearch Query DSL (structured JSON) instead of raw string queries whenever possible.
      • Input Validation: Thoroughly validate and sanitize all user-supplied input used in search queries before sending them to Elasticsearch. Escape special characters appropriately.
      • Parameterized Queries: Use parameterized queries where available to prevent injection, specifically within the context of Elasticsearch queries.

Attack Surface: 6. Denial of Service (DoS) via Resource Exhaustion

  • Description: Overwhelming Elasticsearch with requests that consume excessive resources (CPU, memory, disk), making it unavailable.
    • Elasticsearch Contribution: Elasticsearch is a distributed system, but it can be vulnerable to DoS attacks if not configured properly within Elasticsearch itself. Complex queries, large result sets, and excessive indexing can all contribute.
    • Example: An attacker sends a large number of complex aggregation queries to Elasticsearch with deeply nested structures, causing the Elasticsearch cluster to become unresponsive.
    • Impact: Service unavailability, data loss (if writes are blocked), potential for cascading failures.
    • Risk Severity: High
    • Mitigation Strategies:
      • Circuit Breakers: Configure Elasticsearch's circuit breakers (indices.breaker.* settings in elasticsearch.yml) to limit resources.
      • Query Limits: Limit the size parameter in search requests and the complexity of aggregations (e.g., search.max_buckets in elasticsearch.yml).
      • Resource Monitoring: Monitor cluster resource usage (CPU, memory, disk I/O) and set alerts for unusual activity within Elasticsearch.
      • Dedicated Nodes: Consider using dedicated coordinating-only nodes to handle search requests and offload processing from data nodes within the Elasticsearch cluster.
      • Avoid Leading Wildcards: Minimize or avoid leading wildcard queries (*value) in Elasticsearch queries, as they are very expensive.

Attack Surface: 7. Unpatched Vulnerabilities

  • Description: Failure to apply security patches for known vulnerabilities in the Elasticsearch software itself.
    • Elasticsearch Contribution: Like all software, Elasticsearch has vulnerabilities that are discovered and patched over time. The vulnerability exists within Elasticsearch.
    • Example: An attacker exploits a known vulnerability in an older version of the Elasticsearch software to gain access to the cluster.
    • Impact: Varies depending on the vulnerability, but can range from data breaches to complete system compromise.
    • Risk Severity: High to Critical (depending on the vulnerability)
    • Mitigation Strategies:
      • Regular Updates: Update the Elasticsearch software to the latest stable version promptly after releases. Subscribe to security announcements from Elastic.
      • Patching Process: Implement a robust and timely patching process for Elasticsearch.