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Threat Model Analysis for cortexproject/cortex

Threat: Malicious Time Series Data Injection

  • Description: An attacker injects crafted time series data through the Push Gateway or directly to Distributors. This data could exploit parsing vulnerabilities in Ingesters, leading to crashes, resource exhaustion, or potentially remote code execution.
  • Impact: Service disruption (DoS), data corruption, potential remote code execution on Ingesters.
  • Affected Cortex Component: Ingesters (data parsing and processing), Distributors (data ingestion endpoint), Push Gateway (data ingestion endpoint).
  • Risk Severity: High to Critical
  • Mitigation Strategies:
    • Implement strict input validation and sanitization on data ingested by Distributors and Push Gateway.
    • Regularly update Cortex to the latest version to patch known vulnerabilities.
    • Implement resource limits (CPU, memory) for Ingesters to prevent resource exhaustion.
    • Use rate limiting on ingestion endpoints to mitigate DoS attempts.
    • Consider using authentication and authorization for push endpoints to restrict who can inject data.

Threat: Denial of Service via Data Overload

  • Description: An attacker floods the Cortex ingestion pipeline with a massive volume of metrics, overwhelming Distributors and Ingesters. This can cause performance degradation, service unavailability, and potentially cluster instability.
  • Impact: Service disruption (DoS), performance degradation, potential cascading failures.
  • Affected Cortex Component: Distributors (ingestion endpoint), Ingesters (data processing).
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement rate limiting on Distributors and potentially upstream load balancers.
    • Set request size limits on Distributors.
    • Implement resource quotas and capacity planning for Ingesters to handle expected load and bursts.
    • Implement monitoring and alerting for ingestion rates to detect anomalies.
    • Use load balancing to distribute ingestion traffic across Distributors.

Threat: Namespace/Tenant Isolation Breach during Ingestion

  • Description: In a multi-tenant Cortex setup, a vulnerability in tenant isolation during ingestion could allow data from one tenant to be written into another tenant's namespace. An attacker could exploit this to corrupt data or gain unauthorized access to another tenant's metrics.
  • Impact: Data corruption, unauthorized data access, tenant data leakage, compliance violations.
  • Affected Cortex Component: Distributors (tenant identification and routing), Ingesters (tenant data separation).
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Thoroughly test and validate tenant isolation configurations in Distributors and Ingesters.
    • Regularly audit tenant configurations and access controls.
    • Keep Cortex updated to benefit from security patches related to multi-tenancy.
    • Implement end-to-end testing of tenant isolation mechanisms.

Threat: Unauthorized Access to Stored Data

  • Description: An attacker gains unauthorized access to the underlying storage backend (e.g., S3, GCS, Cassandra) due to misconfigured access controls or compromised credentials. This allows them to read or modify sensitive time series data managed by Cortex.
  • Impact: Data breach, data manipulation, data loss, compliance violations.
  • Affected Cortex Component: Storage Backend (S3, GCS, Cassandra, etc.) as used by Cortex, Store-Gateway (data retrieval from storage).
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Implement strong access control policies (IAM roles, ACLs) on the storage backend, following the principle of least privilege.
    • Utilize encryption at rest for stored data in the storage backend.
    • Regularly audit storage access logs for suspicious activity.
    • Securely manage storage credentials (API keys, access keys) using secrets management solutions.
    • Rotate storage credentials periodically.

Threat: Data Corruption or Loss in Storage

  • Description: Vulnerabilities in the Compactor or Store-Gateway, or issues with the storage backend itself, lead to data corruption or loss of Cortex managed data. This could be exploited by an attacker to manipulate or delete data, or occur due to system failures.
  • Impact: Data integrity compromise, data loss, inaccurate monitoring and alerting, service disruption.
  • Affected Cortex Component: Compactor (data compaction and retention), Store-Gateway (data retrieval and merging), Storage Backend as used by Cortex.
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement robust monitoring of storage health and performance.
    • Regularly back up Cortex data and configurations.
    • Utilize storage redundancy features (replication, backups) provided by the storage backend.
    • Ensure proper configuration and monitoring of the Compactor process.
    • Implement data integrity checks (checksums) where possible.

Threat: Storage Exhaustion leading to Denial of Service

  • Description: Insufficient storage capacity or a sudden surge in data volume (potentially from a data injection attack) leads to storage exhaustion. Cortex becomes unable to ingest or query data, causing a DoS.
  • Impact: Service disruption (DoS), inability to monitor and alert, data loss if retention policies are not properly enforced.
  • Affected Cortex Component: Storage Backend as used by Cortex, Ingesters (if they rely on local storage), Query Frontend and Queriers (if storage unavailability impacts queries).
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement capacity planning and monitoring for storage usage.
    • Set up alerts for approaching storage limits.
    • Implement and enforce data retention policies to manage data volume.
    • Utilize compaction strategies to optimize storage usage.
    • Implement rate limiting on ingestion to prevent sudden data surges.

Threat: Denial of Service via Resource-Intensive Queries

  • Description: An attacker crafts complex or inefficient PromQL queries that consume excessive resources (CPU, memory) on Queriers and Query Frontend. This can degrade performance or cause service unavailability for all users of Cortex.
  • Impact: Service disruption (DoS), performance degradation, impact on other users sharing the Cortex cluster.
  • Affected Cortex Component: Queriers (query execution), Query Frontend (query processing and caching).
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement query analysis and optimization techniques (e.g., query linters, performance testing).
    • Set query timeouts to prevent long-running queries from consuming resources indefinitely.
    • Implement resource limits (memory, CPU) for queries.
    • Implement rate limiting on query requests.
    • Utilize the Query Frontend's caching mechanisms to reduce load on Queriers.
    • Consider query cost estimation and limiting based on estimated cost.

Threat: Information Disclosure via Query Results

  • Description: Insufficient authorization at the query level allows an attacker to query and access time series data they are not authorized to see, especially in multi-tenant Cortex environments.
  • Impact: Unauthorized data access, data breach, privacy violations, compliance violations.
  • Affected Cortex Component: Query Frontend (authorization enforcement), Queriers (data retrieval).
  • Risk Severity: High to Critical
  • Mitigation Strategies:
    • Implement robust authorization mechanisms for queries, ensuring tenant isolation is enforced in Query Frontend.
    • Validate user permissions before executing queries.
    • Audit query logs for suspicious activity and unauthorized access attempts.
    • Implement fine-grained access control policies based on tenants or users.

Threat: Authentication Bypass

  • Description: Vulnerabilities in Cortex's authentication mechanisms (API key, OAuth 2.0) allow an attacker to bypass authentication and gain unauthorized access to Cortex components and APIs.
  • Impact: Unauthorized access to Cortex data and functionality, potential for data breaches, data manipulation, and service disruption.
  • Affected Cortex Component: All components with API endpoints (Distributors, Query Frontend, Admin API, etc.).
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Implement strong authentication mechanisms and enforce them across all Cortex components.
    • Regularly audit authentication configurations and access logs.
    • Keep Cortex updated to patch authentication-related vulnerabilities.
    • Use strong and unique API keys or leverage robust authentication providers like OAuth 2.0.
    • Enforce multi-factor authentication where possible.

Threat: Authorization Bypass or Privilege Escalation

  • Description: Even with authentication, vulnerabilities in Cortex's authorization mechanisms allow an attacker to bypass authorization checks or escalate their privileges within Cortex. They could perform actions they are not authorized for, like accessing other tenants' data or modifying configurations.
  • Impact: Unauthorized access to data and functionality, potential for data breaches, data manipulation, service disruption, and administrative control compromise.
  • Affected Cortex Component: Query Frontend (authorization enforcement), Admin API (authorization enforcement), Distributors (authorization for push operations), other components with authorization checks.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Implement fine-grained authorization policies based on the principle of least privilege.
    • Regularly audit authorization configurations and access controls.
    • Thoroughly test and validate authorization mechanisms.
    • Use role-based access control (RBAC) where appropriate.
    • Minimize the number of users with administrative privileges.

Threat: Man-in-the-Middle (MITM) Attacks on Inter-Component Communication

  • Description: Unencrypted communication between Cortex components allows an attacker to intercept and potentially manipulate data in transit within the Cortex cluster. This could lead to data breaches, data corruption, or DoS.
  • Impact: Data breach, data corruption, service disruption, loss of confidentiality and integrity of Cortex internal communication.
  • Affected Cortex Component: All components communicating with each other (Distributor <-> Ingester, Querier <-> Store-Gateway, etc.).
  • Risk Severity: High
  • Mitigation Strategies:
    • Enforce TLS encryption for all inter-component communication within the Cortex cluster.
    • Implement mutual TLS (mTLS) for stronger authentication between components.
    • Ensure proper TLS certificate management and rotation.

Threat: Component Spoofing

  • Description: Weak or absent inter-component authentication allows an attacker to spoof a legitimate Cortex component within the cluster. They could inject malicious data, intercept queries, or disrupt service by impersonating a trusted component.
  • Impact: Data corruption, service disruption, unauthorized data injection, potential for further attacks by impersonating trusted Cortex components.
  • Affected Cortex Component: All components relying on inter-component communication and authentication.
  • Risk Severity: High
  • Mitigation Strategies:
    • Implement strong authentication for inter-component communication, ideally using mTLS.
    • Regularly audit component configurations and network security.
    • Use network segmentation to isolate Cortex components.

Threat: Insecure Configuration

  • Description: Misconfigurations of Cortex components, such as weak authentication, permissive access controls, or insecure defaults, create vulnerabilities that attackers can exploit.
  • Impact: Wide range of impacts depending on the specific misconfiguration, including unauthorized access, data breaches, service disruption, and privilege escalation within Cortex.
  • Affected Cortex Component: All components, as configuration affects all aspects of Cortex security.
  • Risk Severity: High to Critical
  • Mitigation Strategies:
    • Follow security best practices for Cortex configuration as documented in the official documentation.
    • Use secure defaults where possible.
    • Regularly review and audit Cortex configurations.
    • Implement configuration management tools (e.g., Ansible, Terraform) to ensure consistent and secure configurations.
    • Use infrastructure-as-code to manage and version control Cortex configurations.

Threat: Unauthorized Access to Configuration

  • Description: Insufficient access control to Cortex configuration files or management interfaces allows unauthorized users to modify configurations, potentially compromising the Cortex system.
  • Impact: System compromise, data breaches, service disruption, privilege escalation, backdoors within Cortex.
  • Affected Cortex Component: Configuration files, management interfaces (e.g., command-line tools, configuration APIs).
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Restrict access to Cortex configuration files and management interfaces to authorized personnel only.
    • Implement strong authentication and authorization for management interfaces.
    • Use secure methods for storing and managing configuration secrets (e.g., Vault, HashiCorp Vault).
    • Audit access to configuration files and management interfaces.

Threat: Vulnerabilities in Dependencies

  • Description: Cortex relies on various dependencies (Go libraries, storage client libraries). Vulnerabilities in these dependencies could be exploited to compromise Cortex.
  • Impact: Wide range of impacts depending on the vulnerability, including remote code execution, DoS, information disclosure, and privilege escalation within Cortex.
  • Affected Cortex Component: All components, as dependencies are used throughout Cortex.
  • Risk Severity: High
  • Mitigation Strategies:
    • Regularly update Cortex and its dependencies to patch known vulnerabilities.
    • Implement vulnerability scanning for Cortex and its dependencies using tools like Trivy or Grype.
    • Monitor security advisories for Cortex and its dependencies.
    • Use dependency management tools to track and update dependencies.

Threat: Supply Chain Attacks

  • Description: An attacker compromises the Cortex supply chain by injecting malicious code into Cortex releases or dependencies. This could be through compromised build pipelines, dependency repositories, or maintainer accounts, leading to compromised Cortex software.
  • Impact: System compromise, widespread malware distribution within Cortex deployments, data breaches, long-term persistent access.
  • Affected Cortex Component: All components, as compromised releases or dependencies would affect the entire system.
  • Risk Severity: High
  • Mitigation Strategies:
    • Use official Cortex releases and verify their integrity using checksums and signatures.
    • Implement security checks on downloaded dependencies.
    • Use trusted and reputable dependency repositories.
    • Consider using software bill of materials (SBOM) to track dependencies and their origins.
    • Implement code signing and verification processes.