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Attack Tree Analysis for cortexproject/cortex

Objective: Compromise application using Cortex by exploiting weaknesses or vulnerabilities within Cortex to gain unauthorized access, data manipulation, or denial of service.

Attack Tree Visualization

Attack Goal: Compromise Application Using Cortex [CRITICAL NODE - PRIMARY GOAL] ├─── 1. Exploit Data Ingestion Vulnerabilities [HIGH RISK PATH] [CRITICAL NODE - INGESTION] │ └─── 1.1.1.3. Inject metrics with excessive cardinality to cause performance issues (DoS) [HIGH RISK PATH] │ └─── 1.2. Resource Exhaustion via Ingestion [HIGH RISK PATH] │ ├─── 1.2.1. High Volume Metric Injection [HIGH RISK PATH] │ │ └─── 1.2.1.1. Flood Ingesters with excessive metrics to cause DoS [HIGH RISK PATH] │ └─── 1.2.2. High Cardinality Metric Injection [HIGH RISK PATH] │ └─── 1.2.2.1. Inject metrics with rapidly changing labels to overwhelm Ingesters and storage [HIGH RISK PATH] ├─── 2. Exploit Querying Vulnerabilities [HIGH RISK PATH] [CRITICAL NODE - QUERYING] │ └─── 2.2. Query-Based Denial of Service [HIGH RISK PATH] │ ├─── 2.2.1. Resource Intensive Queries [HIGH RISK PATH] │ │ └─── 2.2.1.1. Craft complex PromQL queries that consume excessive CPU, memory, or I/O on Queriers [HIGH RISK PATH] │ └─── 2.2.1.2. Send a high volume of legitimate but resource-intensive queries to overwhelm Queriers [HIGH RISK PATH] ├─── 3. Exploit Storage Layer Vulnerabilities (Indirectly via Cortex) [HIGH RISK PATH] [CRITICAL NODE - STORAGE] │ └─── 3.1. Storage Access Control Bypass (Misconfiguration) [HIGH RISK PATH] │ ├─── 3.1.1. Misconfigured Backend Storage Permissions [HIGH RISK PATH] [CRITICAL NODE - STORAGE MISCONFIGURATION] │ │ └─── 3.1.1.1. If backend storage (S3, GCS, etc.) is misconfigured, attacker might directly access and manipulate data, bypassing Cortex access controls. [HIGH RISK PATH] │ └─── 3.2.2. Direct Storage Manipulation (if access gained via 3.1) [HIGH RISK PATH] │ └─── 3.2.2.1. Directly modify or delete data in backend storage if access is gained through misconfiguration or Store Gateway exploit. [HIGH RISK PATH] ├─── 6. Exploit Dependencies and Infrastructure [HIGH RISK PATH] [CRITICAL NODE - INFRASTRUCTURE] │ └─── 6.1. Vulnerabilities in Dependencies [HIGH RISK PATH] │ └─── 6.1.1. Outdated Dependencies [HIGH RISK PATH] │ └─── 6.1.1.1. Exploit known vulnerabilities in outdated libraries or components used by Cortex (Go libraries, Prometheus, etc.). [HIGH RISK PATH] │ └─── 6.2. Infrastructure Misconfigurations [HIGH RISK PATH] │ └─── 6.2.1. Unsecured Network Configuration [HIGH RISK PATH] [CRITICAL NODE - NETWORK MISCONFIGURATION] │ └─── 6.2.1.1. Exploit open ports or insecure network configurations to access Cortex components directly. [HIGH RISK PATH]

Attack Tree Path: 1. Exploit Data Ingestion Vulnerabilities [HIGH RISK PATH] [CRITICAL NODE - INGESTION]

  • Attack Vectors:
    • 1.1.1.3. Inject metrics with excessive cardinality to cause performance issues (DoS):
      • Description: Attacker sends metrics with a large number of unique label combinations.
      • Mechanism: High cardinality metrics increase memory usage, indexing load, and storage requirements in Ingesters and backend storage, leading to performance degradation and potential DoS.
      • Impact: Ingester overload, slow queries, system instability, potential service outage.
    • 1.2. Resource Exhaustion via Ingestion [HIGH RISK PATH]:
      • Description: Attacker floods the Ingesters with a massive volume of metrics.
      • Mechanism: Overwhelms Ingesters' processing capacity, network bandwidth, and resource limits (CPU, memory).
      • Impact: Ingester overload, dropped metrics, slow ingestion, system instability, potential service outage.
      • Sub-Vectors:
        • 1.2.1. High Volume Metric Injection [HIGH RISK PATH]:
          • 1.2.1.1. Flood Ingesters with excessive metrics to cause DoS [HIGH RISK PATH]: Simple flooding attack using high volume of metrics.
        • 1.2.2. High Cardinality Metric Injection [HIGH RISK PATH]:
          • 1.2.2.1. Inject metrics with rapidly changing labels to overwhelm Ingesters and storage [HIGH RISK PATH]: Combines high volume with high cardinality for amplified resource exhaustion.

Attack Tree Path: 2. Exploit Querying Vulnerabilities [HIGH RISK PATH] [CRITICAL NODE - QUERYING]

  • Attack Vectors:
    • 2.2. Query-Based Denial of Service [HIGH RISK PATH]:
      • Description: Attacker crafts or sends queries that consume excessive resources on Queriers.
      • Mechanism: Exploits PromQL's expressiveness to create complex queries or sends a high volume of resource-intensive queries, overloading Queriers' CPU, memory, and I/O.
      • Impact: Querier overload, slow queries, query timeouts, system instability, potential service outage.
      • Sub-Vectors:
        • 2.2.1. Resource Intensive Queries [HIGH RISK PATH]:
          • 2.2.1.1. Craft complex PromQL queries that consume excessive CPU, memory, or I/O on Queriers [HIGH RISK PATH]: Focuses on crafting single, highly complex queries.
          • 2.2.1.2. Send a high volume of legitimate but resource-intensive queries to overwhelm Queriers [HIGH RISK PATH]: Focuses on sending many moderately complex queries in rapid succession.

Attack Tree Path: 3. Exploit Storage Layer Vulnerabilities (Indirectly via Cortex) [HIGH RISK PATH] [CRITICAL NODE - STORAGE]

  • Attack Vectors:
    • 3.1. Storage Access Control Bypass (Misconfiguration) [HIGH RISK PATH]:
      • Description: Attacker exploits misconfigured permissions on the backend storage (e.g., S3, GCS, Azure Blob).
      • Mechanism: Cloud storage services often rely on IAM policies. Misconfigurations can grant unintended public or cross-tenant access to the storage buckets used by Cortex.
      • Impact: Direct access to all metrics data, data breach, data manipulation, data deletion, complete compromise of metrics data.
      • Sub-Vectors:
        • 3.1.1. Misconfigured Backend Storage Permissions [HIGH RISK PATH] [CRITICAL NODE - STORAGE MISCONFIGURATION]:
          • 3.1.1.1. If backend storage (S3, GCS, etc.) is misconfigured, attacker might directly access and manipulate data, bypassing Cortex access controls. [HIGH RISK PATH]: Direct exploitation of storage misconfiguration.
    • 3.2.2. Direct Storage Manipulation (if access gained via 3.1) [HIGH RISK PATH]:
      • Description: Once storage access is gained via misconfiguration (3.1), attacker directly manipulates data in the storage backend.
      • Mechanism: Using cloud provider's CLI or SDKs, attacker can read, modify, or delete objects (chunks, indexes) in the storage buckets.
      • Impact: Data corruption, data loss, data deletion, injection of malicious data, complete compromise of metrics data integrity and availability.
      • Sub-Vectors:
        • 3.2.2.1. Directly modify or delete data in backend storage if access is gained through misconfiguration or Store Gateway exploit. [HIGH RISK PATH]: Direct manipulation of storage content.

Attack Tree Path: 6. Exploit Dependencies and Infrastructure [HIGH RISK PATH] [CRITICAL NODE - INFRASTRUCTURE]

  • Attack Vectors:
    • 6.1. Vulnerabilities in Dependencies [HIGH RISK PATH]:
      • Description: Attacker exploits known vulnerabilities in outdated dependencies used by Cortex.
      • Mechanism: Cortex relies on various Go libraries and potentially other components. Outdated dependencies may contain known security vulnerabilities (e.g., RCE, DoS).
      • Impact: Depends on the vulnerability, can range from DoS to Remote Code Execution (RCE), potentially leading to full server compromise and control over Cortex components.
      • Sub-Vectors:
        • 6.1.1. Outdated Dependencies [HIGH RISK PATH]:
          • 6.1.1.1. Exploit known vulnerabilities in outdated libraries or components used by Cortex (Go libraries, Prometheus, etc.). [HIGH RISK PATH]: Exploiting known vulnerabilities in dependencies.
    • 6.2. Infrastructure Misconfigurations [HIGH RISK PATH]:
      • Description: Attacker exploits misconfigurations in the underlying infrastructure where Cortex is deployed (network, OS, etc.).
      • Mechanism: Common misconfigurations include open ports, weak firewall rules, insecure network segmentation, and unpatched operating systems.
      • Impact: Direct access to Cortex components, potential for lateral movement, OS compromise, full server compromise, data breaches, DoS.
      • Sub-Vectors:
        • 6.2.1. Unsecured Network Configuration [HIGH RISK PATH] [CRITICAL NODE - NETWORK MISCONFIGURATION]:
          • 6.2.1.1. Exploit open ports or insecure network configurations to access Cortex components directly. [HIGH RISK PATH]: Exploiting network misconfigurations for direct component access.