✄𐘗
text code block:
✄𐘗from .alerts-security.*

// any alerts excluding low severity and the noisy ones
| where kibana.alert.rule.name is not null and source.ip is not null and kibana.alert.risk_score > 21 and
        not kibana.alert.rule.type in ("threat_match", "machine_learning")

// group alerts by source.ip 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.destination_ip_values = VALUES(destination.ip),
        Esql.host_id_values = VALUES(host.id),
        Esql.agent_id_values = VALUES(agent.id),
        Esql.user_name_values = VALUES(user.name),
        Esql.rule_severity_values = VALUES(kibana.alert.risk_score) by source.ip

// filter for alerts from same source.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 source.ip, Esql.*