Elastic high stable kql
Alerts From Multiple Integrations by User Name
This rule uses alert data to determine when multiple alerts from different integrations with unique event categories and involving the same user.name are triggered. Analysts can use this to prioritize triage and response, as these users are more likely to be compromised.
Detection Logic
from .alerts-security.*
// any alerts excluding low severity and the noisy ones
| where kibana.alert.rule.name is not null and user.name is not null and kibana.alert.risk_score > 21 and
not kibana.alert.rule.type in ("threat_match", "machine_learning") and
not user.id in ("S-1-5-18", "S-1-5-19", "S-1-5-20", "0") and
not KQL("""kibana.alert.rule.tags : "Rule Type: Higher-Order Rule" """) and
// Top noisy influencing rules
// Agent Spoofing - Mismatched Agent ID
// Compression DLL Loaded by Unusual Process
// Process Termination followed by Deletion
// Suspicious PrintSpooler Service Executable File Creation
// Potential PrintNightmare File Modification
// Multiple Vault Web Credentials Read
// Machine Learning Detected a Suspicious Windows Event with a High Malicious Probability Score
not kibana.alert.rule.rule_id in ("3115bd2c-0baa-4df0-80ea-45e474b5ef93", "d197478e-39f0-4347-a22f-ba654718b148", "09443c92-46b3-45a4-8f25-383b028b258d", "5bb4a95d-5a08-48eb-80db-4c3a63ec78a8", "5e87f165-45c2-4b80-bfa5-52822552c997", "44fc462c-1159-4fa8-b1b7-9b6296ab4f96", "994e40aa-8c85-43de-825e-15f665375ee8")
// group alerts by user.name and extract values of interest for alert triage
| stats Esql.event_module_distinct_count = COUNT_DISTINCT(event.module),
Esql.rule_name_distinct_count = COUNT_DISTINCT(kibana.alert.rule.name),
Esql.event_category_distinct_count = COUNT_DISTINCT(event.category),
Esql.rule_risk_score_distinct_count = COUNT_DISTINCT(kibana.alert.risk_score),
Esql.event_module_values = VALUES(event.module),
Esql.rule_name_values = VALUES(kibana.alert.rule.name),
Esql.message_values = VALUES(message),
Esql.event_category_values = VALUES(event.category),
Esql.event_action_values = VALUES(event.action),
Esql.source_ip_values = VALUES(source.ip),
Esql.destination_ip_values = VALUES(destination.ip),
Esql.host_id_values = VALUES(host.id),
Esql.agent_id_values = VALUES(agent.id),
Esql.rule_severity_values = VALUES(kibana.alert.risk_score) by user.name, user.id
// filter for alerts from same destination.ip reported by different integrations with unique categories and with different severity levels
| where Esql.event_module_distinct_count >= 2 and Esql.event_category_distinct_count >= 2 and (Esql.rule_risk_score_distinct_count >= 2 or Esql.rule_severity_values == 73 or Esql.rule_severity_values == 99)
| keep user.name, Esql.* Field Validations
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