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Detection Alert on a Process Exhibiting CPU Spike

This rule correlates security alerts with processes exhibiting unusually high CPU utilization on the same host and process ID within a short time window. This behavior may indicate malicious activity such as malware execution, cryptomining, exploit payload execution, or abuse of system resources following initial compromise.

Detection Query

FROM metrics-*, .alerts-security.* METADATA _index
| where not KQL("""kibana.alert.rule.tags : "Rule Type: Higher-Order Rule" """)
| eval
       // processes with more than 70% total CPU use
       cpu_metrics_pids = CASE(_index like ".ds-metrics-system.process-*" and system.process.cpu.total.norm.pct >= 0.7, process.pid, null),
       // any security alert with process.name and ID populated excluding low severity ones
       alerts_pids = CASE(_index like ".internal.alerts-security.*" and kibana.alert.rule.name is not null and process.name is not null and process.pid is not null and host.id is not null and kibana.alert.risk_score > 21, process.pid, null)
| stats pid_with_cpu_spike = COUNT_DISTINCT(cpu_metrics_pids), pid_with_alerts = COUNT_DISTINCT(alerts_pids),
        Esql.max_cpu_pct = MAX(system.process.cpu.total.norm.pct),
        Esql.alerts = VALUES(kibana.alert.rule.name),
        Esql.process_hash_sha256 = VALUES(process.hash.sha256),
        process_path = VALUES(process.executable),
        parent_process_path = VALUES(process.parent.executable),
        user_name = VALUES(user.name),
        host_name = VALUES(host.name),
        cmdline = VALUES(process.command_line) by process.pid, process.name, host.id
| where pid_with_cpu_spike > 0 and pid_with_alerts > 0
// populate fields to use in rule exceptions
| eval process.hash.sha256 = MV_FIRST(Esql.process_hash_sha256),
       process.executable = MV_FIRST(process_path),
       process.parent.executable = MV_FIRST(parent_process_path),
       process.command_line = MV_FIRST(cmdline),
       user.name = MV_FIRST(user_name),
       host.name = MV_FIRST(host_name)
| KEEP user.name, host.id, host.name, process.*, Esql.*
| where `process.executable` != "C:\\Program Files\\ESET\\ESET Security\\ekrn.exe" and
        `process.executable` != "C:\\Windows\\System32\\CompatTelRunner.exe" and
        `process.executable` != "C:\\Program Files\\UiPath\\Studio\\UiPath.ActivityCompiler.CommandLine.exe"

Author

Elastic

Created

2026/01/26

Tags

Use Case: Threat DetectionRule Type: Higher-Order RuleResources: Investigation GuideDomain: EndpointTactic: Impact
Raw Content
[metadata]
creation_date = "2026/01/26"
maturity = "production"
updated_date = "2026/03/09"

[rule]
author = ["Elastic"]
description = """
This rule correlates security alerts with processes exhibiting unusually high CPU utilization on the same host and process
ID within a short time window. This behavior may indicate malicious activity such as malware execution, cryptomining, exploit
payload execution, or abuse of system resources following initial compromise.
"""
from = "now-9m"
interval = "5m"
language = "esql"
license = "Elastic License v2"
name = "Detection Alert on a Process Exhibiting CPU Spike"
setup = """## Setup

This rule requires host CPU metrics collected via the Elastic Agent **System** integration.

### System Metrics Integration Setup
The System integration collects host-level metrics such as CPU usage, load, memory, and process statistics and sends them to Elasticsearch using Elastic Agent.

#### Prerequisite Requirements:
- Elastic Agent managed by Fleet
- A Fleet Server configured and reachable
  Refer to the Fleet Server setup guide:
  https://www.elastic.co/guide/en/fleet/current/fleet-server.html

#### The following steps should be executed in order to enable CPU metrics collection:
- Go to the Kibana home page and click **Add integrations**.
- In the search bar, enter **System** and select the **System** integration.
- Click **Add System**.
- Configure an integration name and optionally add a description.
- Under **Metrics**, ensure the following datasets are enabled:
  - `system.cpu`
  - `system.load` (optional but recommended)
  - `system.process` (optional, if process-level CPU is required)
- Review optional and advanced settings as needed.
- Add the integration to an existing agent policy or create a new agent policy.
- Deploy the Elastic Agent to the hosts from which CPU metrics should be collected.
- Click **Save and Continue** to finalize the setup.

#### Validation
After deployment, verify CPU metrics ingestion by confirming the presence of documents in:
- `metrics-system.cpu-*`
- `metrics-system.load-*` (if enabled)

For more details on the System integration and available metrics, refer to the documentation:
https://docs.elastic.co/integrations/system
"""
risk_score = 73
rule_id = "df9c0e92-5dee-4f1d-a760-3a5c039e4382"
severity = "high"
tags = [
    "Use Case: Threat Detection",
    "Rule Type: Higher-Order Rule",
    "Resources: Investigation Guide",
    "Domain: Endpoint", 
    "Tactic: Impact"
]
timestamp_override = "event.ingested"
type = "esql"

query = '''
FROM metrics-*, .alerts-security.* METADATA _index
| where not KQL("""kibana.alert.rule.tags : "Rule Type: Higher-Order Rule" """)
| eval
       // processes with more than 70% total CPU use
       cpu_metrics_pids = CASE(_index like ".ds-metrics-system.process-*" and system.process.cpu.total.norm.pct >= 0.7, process.pid, null),
       // any security alert with process.name and ID populated excluding low severity ones
       alerts_pids = CASE(_index like ".internal.alerts-security.*" and kibana.alert.rule.name is not null and process.name is not null and process.pid is not null and host.id is not null and kibana.alert.risk_score > 21, process.pid, null)
| stats pid_with_cpu_spike = COUNT_DISTINCT(cpu_metrics_pids), pid_with_alerts = COUNT_DISTINCT(alerts_pids),
        Esql.max_cpu_pct = MAX(system.process.cpu.total.norm.pct),
        Esql.alerts = VALUES(kibana.alert.rule.name),
        Esql.process_hash_sha256 = VALUES(process.hash.sha256),
        process_path = VALUES(process.executable),
        parent_process_path = VALUES(process.parent.executable),
        user_name = VALUES(user.name),
        host_name = VALUES(host.name),
        cmdline = VALUES(process.command_line) by process.pid, process.name, host.id
| where pid_with_cpu_spike > 0 and pid_with_alerts > 0
// populate fields to use in rule exceptions
| eval process.hash.sha256 = MV_FIRST(Esql.process_hash_sha256),
       process.executable = MV_FIRST(process_path),
       process.parent.executable = MV_FIRST(parent_process_path),
       process.command_line = MV_FIRST(cmdline),
       user.name = MV_FIRST(user_name),
       host.name = MV_FIRST(host_name)
| KEEP user.name, host.id, host.name, process.*, Esql.*
| where `process.executable` != "C:\\Program Files\\ESET\\ESET Security\\ekrn.exe" and
        `process.executable` != "C:\\Windows\\System32\\CompatTelRunner.exe" and
        `process.executable` != "C:\\Program Files\\UiPath\\Studio\\UiPath.ActivityCompiler.CommandLine.exe"
'''
note = """## Triage and analysis

### Investigating Detection Alert on a Process Exhibiting CPU Spike

This rule identifies processes that both triggered a security alert and exhibited unusually high CPU utilization on the
same host and process ID within a short time window. This combination may indicate malicious execution, resource abuse, or
post-compromise activity.

### Possible investigation steps
- Review the correlated alert(s) to understand why the process was flagged by Elastic Defend.
- Examine the process name, command line, and SHA-256 hash to determine whether the process is expected or known to be malicious.
- Validate the observed CPU usage and duration to determine whether the spike is abnormal for this process and host.
- Check for related process activity such as parent/child processes, suspicious process spawning, or privilege escalation attempts.
- Review additional host telemetry including:
  - Network connections initiated by the process
  - File creation or modification events
  - Persistence mechanisms (services, scheduled tasks, registry keys)
- Determine whether similar activity is observed on other hosts, which may indicate a broader compromise.

### False positive analysis
- Legitimate high-CPU processes such as software updates, backup agents, security scans, or system maintenance tasks.
- Resource-intensive but benign applications (e.g., compilers, video encoding, data processing jobs).
- Security tools or monitoring agents temporarily consuming high CPU.

### Response and remediation
- If malicious activity is confirmed, isolate the affected host to prevent further impact.
- Terminate the offending process if safe to do so.
- Remove any identified malicious binaries or artifacts and eliminate persistence mechanisms.
- Apply relevant patches or configuration changes to remediate the root cause.
- Monitor the environment for recurrence of similar high-CPU processes combined with security alerts.
- Escalate the incident if multiple hosts or indicators suggest coordinated or widespread activity."""

[[rule.threat]]
framework = "MITRE ATT&CK"

[rule.threat.tactic]
id = "TA0040"
name = "Impact"
reference = "https://attack.mitre.org/tactics/TA0040/"