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attack-surface.md

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Attack Surface Analysis for grafana/loki

Attack Surface: Log Injection

  • Description: Injecting malicious data within log messages that can be interpreted as commands or exploits by downstream systems or Loki itself.
  • Loki Contribution: Loki ingests and stores logs without inherent sanitization of log content. It provides a platform for these potentially malicious logs to be stored and queried, making them accessible to downstream consumers.
  • Example: An attacker injects a log line containing Javascript code. A Grafana dashboard displaying these logs executes the Javascript in a user's browser, leading to Cross-Site Scripting (XSS).
  • Impact: Cross-Site Scripting (XSS), Remote Code Execution (RCE) in downstream systems, data corruption, or denial of service in log processing pipelines.
  • Risk Severity: High
  • Mitigation Strategies:
    • Input Sanitization: Sanitize log data at the application level before sending it to Loki. Escape special characters and remove potentially harmful code.
    • Contextual Output Encoding: When displaying logs in dashboards or consuming them in other applications, use context-aware output encoding to prevent interpretation of malicious content.
    • Content Security Policy (CSP): Implement CSP in web applications displaying logs to mitigate XSS risks.

Attack Surface: Denial of Service (DoS) via Log Volume

  • Description: Overwhelming Loki components with a massive volume of log data to exhaust resources and cause service disruption.
  • Loki Contribution: Loki's push-based ingestion model can be targeted by attackers to flood the system with logs. Lack of proper rate limiting and resource controls within Loki itself can make it vulnerable.
  • Example: An attacker scripts a bot to send a continuous stream of high-volume, low-value logs to the Loki Distributor, saturating network bandwidth and CPU resources, making Loki unresponsive to legitimate log ingestion and queries.
  • Impact: Loki service unavailability, delayed log ingestion, query performance degradation, and potential cascading failures in dependent systems.
  • Risk Severity: High
  • Mitigation Strategies:
    • Rate Limiting: Implement rate limiting at the Distributor and Ingester levels within Loki configuration to restrict the number of log requests.
    • Resource Quotas: Configure resource quotas (CPU, memory) for Loki components to prevent resource exhaustion.
    • Ingress Filtering (Network Level): Implement network-level filtering to block or rate limit traffic from suspicious sources before it reaches Loki.
    • Monitoring and Alerting: Monitor Loki component resource usage and set up alerts for unusual spikes in log ingestion rates to detect and respond to DoS attacks quickly.

Attack Surface: LogQL Injection

  • Description: Injecting malicious LogQL code when user input is directly incorporated into queries, allowing attackers to manipulate queries and potentially gain unauthorized access to data or cause denial of service.
  • Loki Contribution: Loki's query language, LogQL, if not handled carefully, can be vulnerable to injection attacks when constructing queries dynamically based on user input.
  • Example: A web application allows users to filter logs based on a user-provided string. If this string is directly inserted into a LogQL query without sanitization, an attacker could input } | line_format "{{.Entry}}"} | __error__ = "" or {namespace="malicious"} to bypass intended filters and potentially access logs from other namespaces.
  • Impact: Unauthorized data access, data exfiltration, denial of service via resource-intensive queries, and potential bypass of access control mechanisms within Loki.
  • Risk Severity: High
  • Mitigation Strategies:
    • Input Sanitization and Validation: Sanitize and validate user input before incorporating it into LogQL queries. Use allowlists for allowed characters and patterns.
    • Parameterized Queries (Conceptual): While LogQL doesn't have direct parameterized queries, carefully construct queries to minimize direct string concatenation of user input. Focus on using label matchers and filters instead of string manipulation where possible.
    • Principle of Least Privilege (Query Access): Grant users only the necessary permissions to query logs. Implement granular access control based on namespaces, labels, or other relevant criteria within Loki's authorization framework.
    • Query Limits and Resource Controls: Implement query limits (e.g., time limits, data limits) and resource controls within Loki to prevent resource-intensive queries from causing DoS.

Attack Surface: Authentication and Authorization Bypass

  • Description: Circumventing authentication and authorization mechanisms to gain unauthorized access to Loki's APIs (push or query) or components.
  • Loki Contribution: Loki relies on external authentication and authorization mechanisms (e.g., basic auth, OAuth 2.0, mTLS, Grafana's auth proxy). Misconfiguration or vulnerabilities in these mechanisms directly impact Loki's security. Loki's configuration dictates how these mechanisms are enforced.
  • Example: Basic authentication is enabled in Loki configuration but uses default credentials. An attacker gains access using these default credentials and can push malicious logs or query sensitive data.
  • Impact: Unauthorized log ingestion, data access, data manipulation, denial of service, and potential compromise of the entire logging system.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Strong Authentication: Enforce strong authentication mechanisms such as OAuth 2.0, mTLS, or secure API keys configured within Loki or its gateway. Avoid default credentials and basic authentication in production environments.
    • Robust Authorization: Implement fine-grained authorization policies to control access to Loki's APIs and data based on user roles and permissions using Loki's authorization features or external authorization proxies.
    • Regular Security Audits: Conduct regular security audits of authentication and authorization configurations related to Loki to identify and remediate misconfigurations or vulnerabilities.
    • Principle of Least Privilege (Access Control): Grant users and applications only the necessary permissions to interact with Loki through proper authorization configuration.

Attack Surface: Insecure Configuration

  • Description: Misconfigurations in Loki's settings that weaken security posture and expose vulnerabilities.
  • Loki Contribution: Loki's security depends heavily on proper configuration. Insecure defaults or misconfigurations within Loki's configuration files or deployment manifests can create significant attack vectors.
  • Example: Running Loki with default ports exposed to the public internet without proper firewall rules due to misconfiguration. Or, disabling TLS encryption for inter-component communication in Loki's configuration. Or, storing sensitive credentials in plain text in configuration files used by Loki.
  • Impact: Unauthorized access, data breaches, denial of service, and compromise of Loki components.
  • Risk Severity: High
  • Mitigation Strategies:
    • Secure Configuration Practices: Follow security best practices for configuring Loki, including:
      • Changing default ports in Loki configuration.
      • Enabling TLS encryption for all communication (client-server and inter-component) via Loki configuration.
      • Using strong authentication and authorization configured in Loki.
      • Storing sensitive credentials securely (e.g., using secrets management systems) and referencing them securely in Loki configuration.
      • Disabling unnecessary features or APIs in Loki configuration.
    • Configuration Management: Use configuration management tools to ensure consistent and secure configurations across Loki deployments.
    • Regular Security Reviews: Regularly review Loki configurations to identify and remediate potential security weaknesses.
    • Principle of Least Privilege (Configuration): Configure Loki components with the minimum necessary privileges and access rights through configuration settings.