Name:Linux Auditd Auditd Daemon Start id:6b0cb0ff-9a7e-4475-a687-43827fdb31d6 version:1 date:2025-06-06 author:Teoderick Contreras, Splunk status:production type:Anomaly Description:The following analytic detects the (re)initialization of the Linux audit daemon (auditd) by identifying log entries of type DAEMON_START. This event indicates that the audit subsystem has resumed logging after being stopped or has started during system boot. While DAEMON_START may be expected during reboots or legitimate configuration changes, it can also signal attempts to re-enable audit logging after evasion, or restarts with modified or reduced rule sets. Monitoring this event in correlation with DAEMON_END, DAEMON_ABORT, and auditctl activity provides visibility into the continuity and integrity of audit logs. Frequent or unexplained DAEMON_START events should be investigated, especially if they are not accompanied by valid administrative or system activity. Data_source:
-Linux Auditd Daemon Start
search:`linux_auditd` type=DAEMON_START | rename host as dest | stats count min(_time) as firstTime max(_time) as lastTime by type op res auid dest pid | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `linux_auditd_auditd_daemon_start_filter`
how_to_implement:To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed known_false_positives:Administrator or network operator can use this application for automation purposes. Please update the filter macros to remove false positives. References: -https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/security_guide/sec-audit_record_types drilldown_searches: name:'View the detection results for - "$dest$"' search:'%original_detection_search% | search dest = "$dest$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$dest$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' tags: analytic_story: - 'Compromised Linux Host' asset_type:Endpoint mitre_attack_id: - 'T1562.012' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' security_domain:endpoint
