Elastic Defend and Email Alerts Correlation

[metadata]
creation_date = "2025/11/19"
integration = ["endpoint", "checkpoint_email"]
maturity = "production"
updated_date = "2026/04/10"

[rule]
author = ["Elastic"]
description = """
This rule correlates any Elastic Defend alert with an email security related alert by target user name. This may indicate
the successful execution of a phishing attack.
"""
from = "now-1h"
interval = "45m"
language = "esql"
license = "Elastic License v2"
name = "Elastic Defend and Email Alerts Correlation"
risk_score = 73
rule_id = "c562a800-cf97-464e-9d6f-84db91e86e10"
severity = "high"
tags = [
    "Use Case: Threat Detection",
    "Rule Type: Higher-Order Rule",
    "Resources: Investigation Guide",
    "Data Source: Elastic Defend",
    "Data Source: Check Point Harmony Email & Collaboration",
    "Domain: Email",
    "Domain: Endpoint"
]
timestamp_override = "event.ingested"
type = "esql"

query = '''
from logs-endpoint.alerts-*, logs-checkpoint_email.event-* metadata _id
// Email or Elastic Defend alerts where user name is populated
| where
  (event.category == "email" and event.kind == "alert" and destination.user.name is not null) or
  (event.module == "endpoint" and data_stream.dataset == "endpoint.alerts" and user.name is not null)

// extract target user name from email and endpoint alerts
| eval email_alert_target_user_name = CASE(event.category == "email", destination.user.name, null),
       elastic_defend_alert_user_name = CASE(event.module == "endpoint" and data_stream.dataset == "endpoint.alerts", user.name, null)
| eval Esql.target_user_name = COALESCE(email_alert_target_user_name, elastic_defend_alert_user_name)
| where Esql.target_user_name is not null

// group by Esql.target_user_name
| stats Esql.alerts_count = COUNT(*),
        Esql.event_module_distinct_count = COUNT_DISTINCT(event.module),
        Esql.event_module_values = VALUES(event.module),
        Esql.message_values = VALUES(message),
        Esql.event_action_values = VALUES(event.action),
        Esql.process_executable_values = VALUES(process.executable),
        Esql.host_id_values = VALUES(host.id),
        Esql.source_user_name = VALUES(source.user.name),
        Esql.rule_name_values = VALUES(rule.name)
        by Esql.target_user_name
// alert when same user is observed in an endpoint and email alert
| where Esql.event_module_distinct_count >= 2
| keep Esql.alerts_count, Esql.event_module_values, Esql.host_id_values, Esql.source_user_name, Esql.target_user_name, Esql.message_values, Esql.rule_name_values, Esql.event_action_values
'''
note = """## Triage and analysis
### Investigating Elastic Defend and Email Alerts Correlation

This rule correlates any Elastic Defend alert with an email security related alert by target user name.

### Possible investigation steps
- Review the alert details to identify the specific host and users involved.
- Investigate the individual alerts for the target user name and see if they are related.
- Review all emails received from Esql.source_user_name and if there are other impacted users.
- Correlate the alert data with other logs and telemetry from the host, such as process creation, network connections, and file modifications, to gather additional context.
- Assess the impact and scope of the potential compromise by determining if other hosts or systems have similar alerts or related activity.

### False positive analysis
- Legitimate email marked as suspicious.
- Legitimate file or behavior marked as suspicious by Elastic Defend.
- Unrelated alerts where the target user name is too generic.

### Response and remediation
- Isolate the affected host from the network immediately to prevent further lateral movement by the adversary.
- Conduct a thorough forensic analysis of the host.
- Remove any identified malicious software or unauthorized access tools from the host, ensuring all persistence mechanisms are eradicated.
- Restore the host from a known good backup if necessary, ensuring that the backup is free from compromise.
- Monitor the host and network for any signs of re-infection or further suspicious activity, using enhanced logging and alerting based on the identified attack patterns.
- Escalate the incident to the appropriate internal or external cybersecurity teams for further investigation and potential legal action if the attack is part of a larger campaign."""