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elastic/detection-rules

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2,508 stars·625 forks·Python·other·22 viewswww.elastic.co/guide/en/security/current/detection-engine-overview.html↗

Detection Rules

This project is a detection-as-code framework providing a library of security monitoring rules and predefined detection content for Elasticsearch data indices. It serves as a threat detection rule library designed to identify malicious activity and attack patterns across diverse data streams in cloud and on-premises environments.

The framework implements a detection engineering workflow where rules are defined in YAML and managed as versioned code. It includes a set of command-line utilities for automated rule deployment, metadata searching, and template generation, supported by a Python-based testing framework to validate rule syntax and accuracy before deployment.

The system covers a broad range of security operations, including threat intelligence integration, cloud posture auditing, and security event correlation. It also provides capabilities for anomaly detection, entity risk analysis, and the coordination of security incidents through case management and alert noise suppression.

Features

  • Threat Detection Rule Repositories - Provides a centralized collection of predefined security rules for detecting threats and anomalies within Elasticsearch indices.
  • API Query Languages - Implements structured query capabilities to retrieve security events and telemetry from Elasticsearch indices.
  • Syntax Validation - Provides a validation utility to ensure rule files are syntactically correct and schema-compliant.
  • Detection Rule Deployment - Ships tools to automate the import and export of detection rules to the security engine.
  • Cloud Security Monitoring - Monitors cloud and Kubernetes workload sessions and audits security posture to detect threats.
  • Prebuilt Detection Rule Packs - Offers a library of prebuilt detection rule packs that can be imported and customized for specific environments.
  • Data Stream Evaluators - Implements a scanning mechanism that evaluates incoming data streams against predefined criteria to generate security alerts.
  • Detection-as-Code Frameworks - Provides a complete framework for managing security detections through version control and automated validation.
  • Runtime Threat Detection - Identifies malicious activity by correlating system events and monitoring runtime behavioral patterns.
  • SIEM Content Repositories - Ships a library of security monitoring rules and detection content designed for SIEM platforms.
  • Rule Lifecycle Management - Provides a programmatic API to manage the full lifecycle of security detection configurations.
  • Security Rule Development - Implements a code-based workflow to create, parse, and validate security rules for consistency.
  • YAML Security Rule Definition - Uses YAML files to define detection logic and metadata, enabling security rules to be managed as versioned code.
  • Metadata Schema Validations - Validates that rule metadata and structural definitions adhere to a predefined schema during the build process.
  • Detection Rule Testing - Provides a Python-based testing framework to validate that security rules trigger correctly and produce expected results.
  • Unit Testing - Includes a Python-based testing framework to validate detection accuracy and rule logic using sample data.
  • Threat Intelligence - Integrates external threat intelligence feeds and indicators to improve detection accuracy.
  • Rule Template Generators - A command line interface in the product that guides the creation of new rule files with required metadata.
  • Security Event Correlation - Analyzes patterns across multiple data sources to uncover complex security threats.
  • Detection Rule Search - Includes a command-line utility to locate specific security rules by querying their metadata.
  • Cloud Security Posture Management - Assesses security posture and workload sessions across cloud and Kubernetes environments.
  • Threat Intelligence Aggregation - Ingests and manages threat intelligence feeds to improve the accuracy of security detections.
  • Entity Risk Analysis - Provides a graph-based system to track risk scores and entity relationships to identify compromised assets.
  • Rule Scaffolding - Provides CLI-based scaffolding to generate new rule files with consistent metadata structures.
  • Alert Suppression Systems - Includes capabilities to reduce alert fatigue through muting, deduplication, and scheduled maintenance windows.
  • Alerting and Incident Management - Manages security alerts through noise suppression and formal incident coordination workflows.
  • Anomaly Detection - Implements machine learning capabilities to analyze time series and logs for identifying rare events.
  • Incident Management - Coordinates security incident response through a formal case management workflow and user assignments.
  • Security Event Monitoring - Provides tools to explore timeline events and analyze host, network, and user activity for attack patterns.
  • Detection Rules and Analytics - Collection of detection rules for security monitoring.
  • Detection Content Libraries - Contains native detection rules designed for the Elastic SIEM platform.
  • Detection Engineering - Official detection rules for the Elastic Stack.

Star history

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Frequently asked questions

What does elastic/detection-rules do?

This project is a detection-as-code framework providing a library of security monitoring rules and predefined detection content for Elasticsearch data indices. It serves as a threat detection rule library designed to identify malicious activity and attack patterns across diverse data streams in cloud and on-premises environments.

What are the main features of elastic/detection-rules?

The main features of elastic/detection-rules are: Threat Detection Rule Repositories, API Query Languages, Syntax Validation, Detection Rule Deployment, Cloud Security Monitoring, Prebuilt Detection Rule Packs, Data Stream Evaluators, Detection-as-Code Frameworks.

What are some open-source alternatives to elastic/detection-rules?

Open-source alternatives to elastic/detection-rules include: falcosecurity/falco — Falco is an eBPF runtime security monitor and cloud native detection engine that identifies abnormal behavior and… sigmahq/sigma — Sigma is a suite of tools for defining generic log signatures and translating them for multiple backends. It provides… azure/azure-sentinel — This repository is a community-driven collection of security content for Azure Sentinel, the cloud-native security… neo23x0/sigma — Sigma is a generic SIEM signature format and log event pattern standard used to describe malicious activity. It… thehive-project/thehive — TheHive is a security incident response platform and multi-tenant case management system. It functions as a Security… crowdsecurity/crowdsec — CrowdSec is a collaborative, distributed security engine designed for threat detection and infrastructure protection.…