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Threat Model Analysis for graphite-project/graphite-web

Threat: Unauthorized Metric Data Access

  • Description: An attacker crafts HTTP requests directly to the Graphite-Web rendering API (e.g., /render/) or the web interface, bypassing any intended authentication or authorization. They exploit the lack of built-in, robust access control within Graphite-Web to retrieve sensitive data by guessing metric names or using brute-force techniques.
    • Impact: Exposure of confidential system metrics, potentially revealing internal infrastructure details, performance data, business-sensitive information, or security-relevant data. This could lead to further attacks, competitive disadvantage, or reputational damage.
    • Affected Component:
      • graphite.render.views.renderView: The primary view function handling rendering requests.
      • graphite.browser.views: Views related to the web interface for browsing metrics.
      • Any URL patterns configured to expose metric data without authentication.
    • Risk Severity: Critical
    • Mitigation Strategies:
      • Mandatory: Implement a robust reverse proxy (Nginx, Apache, etc.) in front of Graphite-Web, handling all authentication and authorization. Configure the proxy to deny access to Graphite-Web URLs without valid credentials. Graphite-Web's built-in authentication is insufficient on its own.
      • Strongly Recommended: Integrate with an existing identity provider (LDAP, OAuth2, SSO) via the reverse proxy or a dedicated, well-vetted authentication plugin.

Threat: Denial of Service via Complex Queries

  • Description: An attacker sends crafted requests to the Graphite-Web rendering API (/render/) with extremely complex queries, using functions like groupByNode, summarize, or nested functions with large time ranges or wildcard patterns. These queries are designed to consume excessive CPU, memory, or I/O resources within Graphite-Web's processing logic.
    • Impact: The Graphite-Web server becomes unresponsive, preventing legitimate users from accessing metric data. This disrupts monitoring, alerting, and operational dashboards, potentially leading to delayed incident response or service outages.
    • Affected Component:
      • graphite.render.views.renderView: The core rendering function.
      • graphite.render.functions: The functions used to process and aggregate data (e.g., summarize, groupByNode, derivative, hitcount, and any custom functions). The attacker exploits the computational complexity of these functions.
    • Risk Severity: High
    • Mitigation Strategies:
      • Mandatory: Implement strict query timeouts within Graphite-Web itself (e.g., DEFAULT_CACHE_DURATION, MAX_FETCH_STEP, and potentially custom timeout logic within the rendering views). These settings directly control how long Graphite-Web will spend processing a query.
      • Strongly Recommended: Implement a query analysis mechanism (potentially a custom middleware or a separate service) to detect and block potentially malicious queries before they are fully processed by Graphite-Web. This could involve analyzing the query structure, the number of data points requested, or the use of expensive functions.
      • Recommended: Implement caching (Memcached, Redis) to reduce load for frequently accessed queries.

Threat: Arbitrary Code Execution via Pickle Deserialization

  • Description: An attacker sends a crafted malicious payload using the pickle protocol to a Graphite-Web endpoint that accepts and processes pickle data (e.g., a rendering endpoint configured to accept pickle input or a custom endpoint). The attacker leverages the inherent insecurity of Python's pickle module to execute arbitrary code within the Graphite-Web process.
    • Impact: Complete system compromise. The attacker gains full control over the Graphite-Web server and potentially the underlying host, allowing them to steal data, install malware, or launch further attacks.
    • Affected Component:
      • graphite.render.evaluator.evaluateTarget (if pickle is enabled for rendering).
      • graphite.protocols.PickleReceiver (if used, but this is less directly Graphite-Web and more Carbon). The vulnerability lies in any Graphite-Web component that uses pickle.loads on untrusted data.
    • Risk Severity: Critical
    • Mitigation Strategies:
      • Mandatory: Disable the use of the pickle protocol entirely within Graphite-Web. This is the most effective mitigation. Use JSON or other safe serialization formats for all data exchange.
      • If Pickle is Absolutely Necessary (Strongly Discouraged and should be avoided):
        • Ensure that no Graphite-Web endpoint accepts pickle data from untrusted sources. This is extremely difficult to guarantee in practice and is not a reliable mitigation.
        • Implement strict network-level access controls (firewalls) to prevent any external access to potential pickle endpoints. This is a defense-in-depth measure, not a primary solution.
      • Strongly Recommended: Use alternative protocols like the Carbon plaintext protocol or the Graphite HTTP API with JSON for data ingestion and rendering.