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Jaeger Security Analysis: Deep Dive

1. Objective, Scope, and Methodology

Objective:

The objective of this deep analysis is to conduct a thorough security assessment of the Jaeger distributed tracing system, focusing on its key components, architecture, data flow, and build process. The analysis aims to identify potential security vulnerabilities, assess their impact, and propose actionable mitigation strategies tailored to Jaeger's specific design and implementation. The primary goal is to ensure the confidentiality, integrity, and availability of trace data and the Jaeger system itself, while minimizing the risk of data breaches, unauthorized access, and service disruptions.

Scope:

This analysis covers the following aspects of Jaeger:

  • Core Components: Jaeger Agent, Collector, Query Service, Ingester, and UI.
  • Data Flow: The path of trace data from instrumented applications to storage and retrieval.
  • Communication: Inter-component communication and communication with external systems (storage, alerting).
  • Deployment: Focus on Kubernetes deployment, as outlined in the design review.
  • Build Process: Analysis of the build pipeline and associated security controls.
  • Storage Backends: Consideration of Cassandra and Elasticsearch as primary storage options.
  • Authentication and Authorization: Mechanisms for controlling access to Jaeger.
  • Input Validation: Measures to prevent injection attacks.
  • Cryptography: Use of TLS/SSL and encryption at rest.
  • Risk Assessment: Identification of key threats and vulnerabilities.

Methodology:

The analysis will employ the following methodology:

  1. Architecture Review: Inferring the architecture, components, and data flow from the provided design document, codebase (https://github.com/jaegertracing/jaeger), and official documentation.
  2. Component Analysis: Breaking down each key component and analyzing its security implications.
  3. Threat Modeling: Identifying potential threats based on the architecture, data flow, and business risks. This will leverage the STRIDE model (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege).
  4. Vulnerability Assessment: Identifying potential vulnerabilities based on common security weaknesses and known attack vectors.
  5. Mitigation Strategy Recommendation: Proposing specific, actionable, and tailored mitigation strategies for each identified vulnerability.
  6. Code Review (Targeted): Examining specific code sections related to identified vulnerabilities or critical security controls. This is not a full code audit, but a focused review based on the threat model.

2. Security Implications of Key Components

This section breaks down the security implications of each key Jaeger component, considering potential threats and vulnerabilities.

2.1 Jaeger Agent:

  • Function: Receives spans from the application, batches them, and sends them to the collector.
  • Threats:
    • Spoofing: A malicious application could send fake spans to the agent, potentially polluting trace data or causing denial of service.
    • Tampering: An attacker could intercept and modify spans in transit between the application and the agent (if unencrypted).
    • Denial of Service: The agent could be overwhelmed with a large volume of spans, preventing legitimate spans from being processed.
    • Information Disclosure: If the agent's communication with the collector is not encrypted, an attacker could eavesdrop on the traffic and potentially extract sensitive information from the spans.
  • Vulnerabilities:
    • Lack of input validation on span data.
    • Insufficient rate limiting.
    • Unencrypted communication with the collector.
    • Vulnerabilities in the agent's code itself (e.g., buffer overflows).

2.2 Jaeger Collector:

  • Function: Receives spans from agents, validates them, and stores them in the storage backend.
  • Threats:
    • Spoofing: A malicious agent could send fake spans to the collector.
    • Tampering: An attacker could intercept and modify spans in transit between the agent and the collector (if unencrypted).
    • Denial of Service: The collector could be overwhelmed with a large volume of spans, preventing legitimate spans from being processed.
    • Information Disclosure: Unencrypted communication could expose sensitive data. Unauthorized access to the collector could allow an attacker to retrieve all stored spans.
    • Injection Attacks: Vulnerabilities in the collector's input validation could allow attackers to inject malicious data into the storage backend.
  • Vulnerabilities:
    • Insufficient input validation on span data.
    • Lack of authentication or weak authentication for agents.
    • Unencrypted communication with agents and the storage backend.
    • Vulnerabilities in the collector's code (e.g., SQL injection, NoSQL injection).
    • Insufficient rate limiting.

2.3 Jaeger Query Service:

  • Function: Retrieves traces from the storage backend and provides an API for querying them.
  • Threats:
    • Unauthorized Access: Users without proper authorization could access sensitive trace data.
    • Information Disclosure: Vulnerabilities in the query service could allow attackers to extract data they shouldn't have access to.
    • Denial of Service: The query service could be overwhelmed with a large number of requests, making it unavailable.
    • Injection Attacks: Vulnerabilities in the query service's input validation could allow attackers to inject malicious queries into the storage backend.
  • Vulnerabilities:
    • Weak or missing authentication and authorization mechanisms.
    • Insufficient input validation on query parameters.
    • Unencrypted communication with the storage backend and the UI.
    • Vulnerabilities in the query service's code (e.g., SQL injection, NoSQL injection).
    • Insufficient rate limiting.

2.4 Jaeger Ingester:

  • Function: Reads trace data from a Kafka topic and writes it to the storage backend (optional, used with Kafka).
  • Threats:
    • Tampering: An attacker could modify data in the Kafka topic before it's ingested.
    • Denial of Service: The ingester could be overwhelmed, preventing data from being written to storage.
    • Information Disclosure: If communication with Kafka or the storage backend is unencrypted, data could be exposed.
    • Injection Attacks: Vulnerabilities in the ingester's input validation could allow attackers to inject malicious data into the storage backend.
  • Vulnerabilities:
    • Weak authentication with Kafka.
    • Unencrypted communication with Kafka and the storage backend.
    • Insufficient input validation.
    • Vulnerabilities in the ingester's code.

2.5 Jaeger UI:

  • Function: Provides a web-based interface for visualizing and analyzing traces.
  • Threats:
    • Cross-Site Scripting (XSS): An attacker could inject malicious scripts into the UI, potentially stealing user credentials or performing other actions on behalf of the user.
    • Cross-Site Request Forgery (CSRF): An attacker could trick a user into performing actions they didn't intend to, such as modifying Jaeger settings.
    • Unauthorized Access: Users without proper authorization could access the UI and view sensitive trace data.
    • Information Disclosure: Vulnerabilities in the UI could expose sensitive information to unauthorized users.
  • Vulnerabilities:
    • Lack of proper output encoding to prevent XSS.
    • Missing or weak CSRF protection.
    • Weak or missing authentication and authorization.
    • Unencrypted communication with the query service.
    • Vulnerabilities in the UI's JavaScript code.

2.6 Storage Backend (Cassandra/Elasticsearch):

  • Function: Stores and retrieves trace data.
  • Threats:
    • Unauthorized Access: Direct access to the storage backend could bypass Jaeger's security controls.
    • Data Breach: Vulnerabilities in the storage backend could lead to data breaches.
    • Data Corruption/Loss: Misconfiguration or failures in the storage backend could lead to data loss or corruption.
  • Vulnerabilities:
    • Weak or default credentials.
    • Unencrypted data at rest.
    • Lack of proper access controls.
    • Vulnerabilities in the storage backend software itself.

3. Architecture, Components, and Data Flow (Inferred)

Based on the design document, codebase, and documentation, the following architecture, components, and data flow are inferred:

Architecture: Microservices-based, with distinct components for data collection, processing, storage, and querying. Designed for scalability and resilience.

Components: As described in the design document (Agent, Collector, Query Service, Ingester, UI).

Data Flow:

  1. Instrumentation: Applications are instrumented with Jaeger client libraries, which generate spans representing individual operations.
  2. Span Emission: Spans are emitted from the application to the Jaeger Agent, typically over UDP.
  3. Agent Batching: The Jaeger Agent batches spans and sends them to the Jaeger Collector, usually over gRPC (with TLS).
  4. Collector Processing: The Jaeger Collector receives spans, validates them, and writes them to the storage backend (Cassandra or Elasticsearch). If Kafka is used, the Collector writes to a Kafka topic.
  5. Ingester Processing (Optional): If Kafka is used, the Jaeger Ingester reads spans from the Kafka topic and writes them to the storage backend.
  6. Query Service Retrieval: The Jaeger Query Service retrieves traces from the storage backend based on user queries.
  7. UI Display: The Jaeger UI interacts with the Query Service to display traces to the user.

Communication:

  • Application <-> Agent: Typically UDP (configurable).
  • Agent <-> Collector: Typically gRPC (with TLS).
  • Collector <-> Storage: Depends on the storage backend (e.g., Cassandra Query Language (CQL), Elasticsearch REST API). Should use TLS.
  • Collector <-> Kafka (Optional): Kafka protocol (with TLS and authentication).
  • Ingester <-> Kafka (Optional): Kafka protocol (with TLS and authentication).
  • Ingester <-> Storage: Depends on the storage backend (e.g., CQL, Elasticsearch REST API). Should use TLS.
  • Query Service <-> Storage: Depends on the storage backend. Should use TLS.
  • UI <-> Query Service: HTTP/HTTPS (with TLS).

4. Specific Security Considerations and Mitigation Strategies

This section provides specific security considerations and actionable mitigation strategies, tailored to Jaeger, based on the identified threats and vulnerabilities.

| Component | Threat | Vulnerability | Mitigation Strategy | | Component | Threat | Vulnerability | Mitigation Strategy