Elastic Security Rule Developer-AI-powered Elastic security rules generator

Example

Creating a detection rule for identifying brute-force login attempts from multiple failed logins within a short period using event correlation.

Scenario

A security operations team wants to detect brute-force attacks on their Active Directory environment. By using Elastic Security Rule Developer, they can write a correlation rule to alert when more than 10 failed login attempts occur within 5 minutes from the same IP address. The rule can be enhanced to reduce false positives by excluding internal IP addresses or service accounts.

Example

Reviewing a user’s KQL query for detecting suspicious PowerShell executions on Windows hosts and optimizing it for efficiency and accuracy.

Scenario

A security engineer submits a rule designed to detect PowerShell scripts executing commands from an unknown source. Elastic Security Rule Developer reviews the query and recommends improvements by narrowing down the conditions, such as adding filters for uncommon script execution paths and excluding known benign sources like internal IT scripts. This ensures the rule performs effectively with fewer false positives.

Example

Mapping a custom rule that detects unauthorized AWS S3 bucket access attempts to the MITRE ATT&CK framework tactics and techniques.

Scenario

An organization detects a spike in AWS S3 bucket access from unfamiliar IP ranges. By using Elastic Security Rule Developer, they can build a custom detection rule and automatically map the activity to the MITRE ATT&CK technique 'T1078: Valid Accounts' and tactic 'Initial Access'. This helps in organizing detections within a known framework for consistent incident reporting and response.