Name:Linux Auditd Base64 Decode Files id:5890ba10-4e48-4dc0-8a40-3e1ebe75e737 version:2 date:2024-09-30 author:Teoderick Contreras, Splunk status:production type:Anomaly Description:The following analytic detects suspicious Base64 decode operations that may indicate malicious activity, such as data exfiltration or execution of encoded commands. Base64 is commonly used to encode data for safe transmission, but attackers may abuse it to conceal malicious payloads. This detection focuses on identifying unusual or unexpected Base64 decoding processes, particularly when associated with critical files or directories. By monitoring these activities, the analytic helps uncover potential threats, enabling security teams to respond promptly and mitigate risks associated with encoded malware or unauthorized data access. Data_source:
-Linux Auditd Execve
search:`linux_auditd` `linux_auditd_normalized_execve_process` | rename host as dest | where LIKE(process_exec, "%base64%") AND (LIKE(process_exec, "%-d %") OR LIKE(process_exec, "% --d%")) | stats count min(_time) as firstTime max(_time) as lastTime by argc process_exec dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `linux_auditd_base64_decode_files_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://www.splunk.com/en_us/blog/security/deep-dive-on-persistence-privilege-escalation-technique-and-detection-in-linux-platform.html -https://gtfobins.github.io/gtfobins/dd/ 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: - 'Linux Living Off The Land' - 'Linux Privilege Escalation' - 'Linux Persistence Techniques' - 'Compromised Linux Host' asset_type:Endpoint confidence:50 impact:50 message:A [$process_exec$] event occurred on host - [$dest$] to decode a file using base64. mitre_attack_id: - 'T1140' observable: name:'dest' type:'Endpoint' - role: - 'Victim' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' required_fields: - '_time' - 'argc' - 'process_exec' risk_score:25 security_domain:endpoint
