Linux Auditd Preload Hijack Via Preload File
Description
The following analytic detects suspicious preload hijacking via the preload file, which may indicate an attacker's attempt to intercept or manipulate library loading processes.
The preload file can be used to force the loading of specific libraries before others, potentially allowing malicious code to execute or alter application behavior.
By monitoring for unusual or unauthorized modifications to the preload file, this analytic helps identify attempts to hijack preload mechanisms, enabling security teams to investigate and address potential threats to system integrity and security.
Correlate this with related EXECVE or PROCTITLE events to identify the process or user responsible for the access or modification.
Query · spl
`linux_auditd`
(type=PATH OR type=CWD)
| rex "msg=audit\([^)]*:(?<audit_id>\d+)\)"
| stats
values(type) as types
values(name) as names
values(nametype) as nametype
values(cwd) as cwd_list
values(_time) as event_times
by audit_id, host
| eval current_working_directory = coalesce(mvindex(cwd_list, 0), "N/A")
| eval candidate_paths = mvmap(names, if(match(names, "^/"), names, current_working_directory + "/" + names))
| eval matched_paths = mvfilter(match(candidate_paths, "/etc/ld.so.preload.*"))
| eval match_count = mvcount(matched_paths)
| eval reconstructed_path = mvindex(matched_paths, 0)
| eval e_time = mvindex(event_times, 0)
| where match_count > 0
| rename host as dest
| stats count min(e_time) as firstTime max(e_time) as lastTime
values(nametype) as nametype
by current_working_directory
reconstructed_path
match_count
dest
audit_id
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `linux_auditd_preload_hijack_via_preload_file_filter`
Implementation guide
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 and make sure the type=CWD record type is activate in your auditd configuration. 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.
Analyst notes
Known false positives: Administrator or network operator can use this application for automation purposes. Please update the filter macros to remove false positives.