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.

Elastic rule (View on GitHub)

  1[metadata]
  2creation_date = "2026/01/26"
  3maturity = "production"
  4updated_date = "2026/01/26"
  5
  6[rule]
  7author = ["Elastic"]
  8description = """
  9This rule correlates security alerts with processes exhibiting unusually high CPU utilization on the same host and process
 10ID within a short time window. This behavior may indicate malicious activity such as malware execution, cryptomining, exploit
 11payload execution, or abuse of system resources following initial compromise.
 12"""
 13from = "now-9m"
 14interval = "5m"
 15language = "esql"
 16license = "Elastic License v2"
 17name = "Detection Alert on a Process Exhibiting CPU Spike"
 18setup = """## Setup
 19
 20This rule requires host CPU metrics collected via the Elastic Agent **System** integration.
 21
 22### System Metrics Integration Setup
 23The System integration collects host-level metrics such as CPU usage, load, memory, and process statistics and sends them to Elasticsearch using Elastic Agent.
 24
 25#### Prerequisite Requirements:
 26- Elastic Agent managed by Fleet
 27- A Fleet Server configured and reachable
 28  Refer to the Fleet Server setup guide:
 29  https://www.elastic.co/guide/en/fleet/current/fleet-server.html
 30
 31#### The following steps should be executed in order to enable CPU metrics collection:
 32- Go to the Kibana home page and click **Add integrations**.
 33- In the search bar, enter **System** and select the **System** integration.
 34- Click **Add System**.
 35- Configure an integration name and optionally add a description.
 36- Under **Metrics**, ensure the following datasets are enabled:
 37  - `system.cpu`
 38  - `system.load` (optional but recommended)
 39  - `system.process` (optional, if process-level CPU is required)
 40- Review optional and advanced settings as needed.
 41- Add the integration to an existing agent policy or create a new agent policy.
 42- Deploy the Elastic Agent to the hosts from which CPU metrics should be collected.
 43- Click **Save and Continue** to finalize the setup.
 44
 45#### Validation
 46After deployment, verify CPU metrics ingestion by confirming the presence of documents in:
 47- `metrics-system.cpu-*`
 48- `metrics-system.load-*` (if enabled)
 49
 50For more details on the System integration and available metrics, refer to the documentation:
 51https://docs.elastic.co/integrations/system
 52"""
 53risk_score = 73
 54rule_id = "df9c0e92-5dee-4f1d-a760-3a5c039e4382"
 55severity = "high"
 56tags = [
 57    "Use Case: Threat Detection",
 58    "Rule Type: Higher-Order Rule",
 59    "Resources: Investigation Guide",
 60    "Domain: Endpoint", 
 61    "Tactic: Impact"
 62]
 63timestamp_override = "event.ingested"
 64type = "esql"
 65
 66query = '''
 67FROM metrics-*, .alerts-security.* METADATA _index
 68| eval
 69       // processes with more than 70% total CPU use
 70       cpu_metrics_pids = CASE(_index like ".ds-metrics-system.process-*" and system.process.cpu.total.norm.pct >= 0.7, process.pid, null),
 71       // any security alert with process.name and ID populated excluding low severity ones
 72       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)
 73| stats pid_with_cpu_spike = COUNT_DISTINCT(cpu_metrics_pids), pid_with_alerts = COUNT_DISTINCT(alerts_pids),
 74        Esql.max_cpu_pct = MAX(system.process.cpu.total.norm.pct),
 75        Esql.alerts = VALUES(kibana.alert.rule.name),
 76        Esql.process_hash_sha256 = VALUES(process.hash.sha256),
 77        process_path = VALUES(process.executable),
 78        parent_process_path = VALUES(process.parent.executable),
 79        user_name = VALUES(user.name),
 80        cmdline = VALUES(process.command_line) by process.pid, process.name, host.id
 81| where pid_with_cpu_spike > 0 and pid_with_alerts > 0
 82// populate fields to use in rule exceptions
 83| eval process.hash.sha256 = MV_FIRST(Esql.process_hash_sha256),
 84       process.executable = MV_FIRST(process_path),
 85       process.parent.executable = MV_FIRST(parent_process_path),
 86       process.command_line = MV_FIRST(cmdline),
 87       user.name = MV_FIRST(user_name)
 88| KEEP user.name, host.id, process.*, Esql.*
 89'''
 90note = """## Triage and analysis
 91
 92### Investigating Detection Alert on a Process Exhibiting CPU Spike
 93
 94This rule identifies processes that both triggered a security alert and exhibited unusually high CPU utilization on the
 95same host and process ID within a short time window. This combination may indicate malicious execution, resource abuse, or
 96post-compromise activity.
 97
 98### Possible investigation steps
 99- Review the correlated alert(s) to understand why the process was flagged by Elastic Defend.
100- Examine the process name, command line, and SHA-256 hash to determine whether the process is expected or known to be malicious.
101- Validate the observed CPU usage and duration to determine whether the spike is abnormal for this process and host.
102- Check for related process activity such as parent/child processes, suspicious process spawning, or privilege escalation attempts.
103- Review additional host telemetry including:
104  - Network connections initiated by the process
105  - File creation or modification events
106  - Persistence mechanisms (services, scheduled tasks, registry keys)
107- Determine whether similar activity is observed on other hosts, which may indicate a broader compromise.
108
109### False positive analysis
110- Legitimate high-CPU processes such as software updates, backup agents, security scans, or system maintenance tasks.
111- Resource-intensive but benign applications (e.g., compilers, video encoding, data processing jobs).
112- Security tools or monitoring agents temporarily consuming high CPU.
113
114### Response and remediation
115- If malicious activity is confirmed, isolate the affected host to prevent further impact.
116- Terminate the offending process if safe to do so.
117- Remove any identified malicious binaries or artifacts and eliminate persistence mechanisms.
118- Apply relevant patches or configuration changes to remediate the root cause.
119- Monitor the environment for recurrence of similar high-CPU processes combined with security alerts.
120- Escalate the incident if multiple hosts or indicators suggest coordinated or widespread activity."""
121
122[[rule.threat]]
123framework = "MITRE ATT&CK"
124
125[rule.threat.tactic]
126id = "TA0040"
127name = "Impact"
128reference = "https://attack.mitre.org/tactics/TA0040/"

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.

Related rules

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