Kernel Module Load via insmod

Detects the use of the insmod binary to load a Linux kernel object file. Threat actors can use this binary, given they have root privileges, to load a rootkit on a system providing them with complete control and the ability to hide from security products. Manually loading a kernel module in this manner should not be at all common and can indicate suspcious or malicious behavior.

Elastic rule (View on GitHub)

  1[metadata]
  2creation_date = "2022/07/11"
  3integration = ["endpoint", "auditd_manager", "sentinel_one_cloud_funnel"]
  4maturity = "production"
  5min_stack_version = "8.13.0"
  6min_stack_comments = "Breaking change at 8.13.0 for SentinelOne Integration."
  7updated_date = "2025/01/15"
  8
  9[transform]
 10[[transform.osquery]]
 11label = "Osquery - Retrieve all Kernel Modules"
 12query = "SELECT * FROM kernel_modules"
 13
 14[[transform.osquery]]
 15label = "Osquery - Retrieve Running Processes by User"
 16query = "SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"
 17
 18[[transform.osquery]]
 19label = "Osquery - Retrieve Listening Ports"
 20query = "SELECT pid, address, port, socket, protocol, path FROM listening_ports"
 21
 22[[transform.osquery]]
 23label = "Osquery - Retrieve Open Sockets"
 24query = "SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"
 25
 26[[transform.osquery]]
 27label = "Osquery - Retrieve Information for a Specific User"
 28query = "SELECT * FROM users WHERE username = {{user.name}}"
 29
 30[[transform.osquery]]
 31label = "Osquery - Investigate the Account Authentication Status"
 32query = "SELECT * FROM logged_in_users WHERE user = {{user.name}}"
 33
 34
 35[rule]
 36author = ["Elastic"]
 37description = """
 38Detects the use of the insmod binary to load a Linux kernel object file. Threat actors can use this binary, given they
 39have root privileges, to load a rootkit on a system providing them with complete control and the ability to hide from
 40security products. Manually loading a kernel module in this manner should not be at all common and can indicate
 41suspcious or malicious behavior.
 42"""
 43from = "now-9m"
 44index = ["logs-endpoint.events.*", "endgame-*", "auditbeat-*", "logs-auditd_manager.auditd-*", "logs-sentinel_one_cloud_funnel.*"]
 45language = "eql"
 46license = "Elastic License v2"
 47name = "Kernel Module Load via insmod"
 48note = """## Triage and analysis
 49
 50### Investigating Kernel module load via insmod
 51
 52The insmod binary is a Linux utility that allows users with root privileges to load kernel modules, which are object files that extend the functionality of the kernel. 
 53
 54Threat actors can abuse this utility to load rootkits, granting them full control over the system and the ability to evade security products.
 55
 56The detection rule 'Kernel module load via insmod' is designed to identify instances where the insmod binary is used to load a kernel object file (with a .ko extension) on a Linux system. This activity is uncommon and may indicate suspicious or malicious behavior.
 57
 58> **Note**:
 59> This investigation guide uses the [Osquery Markdown Plugin](https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html) introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
 60> This investigation guide uses [placeholder fields](https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html) to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
 61
 62### Possible investigation steps
 63
 64- Investigate the kernel object file that was loaded via insmod.
 65  - $osquery_1
 66- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
 67  - $osquery_2
 68- Investigate the kernel ring buffer for any warnings or messages, such as tainted or out-of-tree kernel module loads through `dmesg`.
 69- Investigate syslog for any unusual segfaults or other messages. Rootkits may be installed on targets with different architecture as expected, and could potentially cause segmentation faults. 
 70- Investigate other alerts associated with the user/host during the past 48 hours.
 71- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
 72- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
 73  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
 74    - Use a private sandboxed malware analysis system to perform analysis.
 75      - Observe and collect information about the following activities:
 76        - Attempts to contact external domains and addresses.
 77          - Check if the domain is newly registered or unexpected.
 78          - Check the reputation of the domain or IP address.
 79        - File access, modification, and creation activities.
 80- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
 81  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
 82    - $osquery_3
 83    - $osquery_4
 84  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
 85    - $osquery_5
 86- Investigate whether the user is currently logged in and active.
 87    - $osquery_6
 88
 89### False positive analysis
 90
 91- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
 92- If this activity is related to a system administrator who uses cron jobs for administrative purposes, consider adding exceptions for this specific administrator user account. 
 93- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
 94
 95### Related Rules
 96
 97- Kernel Driver Load - 3e12a439-d002-4944-bc42-171c0dcb9b96
 98- Tainted Out-Of-Tree Kernel Module Load - 51a09737-80f7-4551-a3be-dac8ef5d181a
 99- Tainted Kernel Module Load - 05cad2fb-200c-407f-b472-02ea8c9e5e4a
100- Attempt to Clear Kernel Ring Buffer - 2724808c-ba5d-48b2-86d2-0002103df753
101- Enumeration of Kernel Modules via Proc - 80084fa9-8677-4453-8680-b891d3c0c778
102- Suspicious Modprobe File Event - 40ddbcc8-6561-44d9-afc8-eefdbfe0cccd
103- Kernel Module Removal - cd66a5af-e34b-4bb0-8931-57d0a043f2ef
104- Enumeration of Kernel Modules - 2d8043ed-5bda-4caf-801c-c1feb7410504
105
106### Response and Remediation
107
108- Initiate the incident response process based on the outcome of the triage.
109- Isolate the involved host to prevent further post-compromise behavior.
110- If the triage identified malware, search the environment for additional compromised hosts.
111  - Implement temporary network rules, procedures, and segmentation to contain the malware.
112  - Stop suspicious processes.
113  - Immediately block the identified indicators of compromise (IoCs).
114  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
115- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
116- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
117- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
118- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
119"""
120references = [
121    "https://decoded.avast.io/davidalvarez/linux-threat-hunting-syslogk-a-kernel-rootkit-found-under-development-in-the-wild/",
122]
123risk_score = 47
124rule_id = "2339f03c-f53f-40fa-834b-40c5983fc41f"
125setup = """## Setup
126
127This rule requires data coming in from Elastic Defend.
128
129### Elastic Defend Integration Setup
130Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
131
132#### Prerequisite Requirements:
133- Fleet is required for Elastic Defend.
134- To configure Fleet Server refer to the [documentation](https://www.elastic.co/guide/en/fleet/current/fleet-server.html).
135
136#### The following steps should be executed in order to add the Elastic Defend integration on a Linux System:
137- Go to the Kibana home page and click "Add integrations".
138- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
139- Click "Add Elastic Defend".
140- Configure the integration name and optionally add a description.
141- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
142- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. [Helper guide](https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html).
143- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
144- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
145For more details on Elastic Agent configuration settings, refer to the [helper guide](https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html).
146- Click "Save and Continue".
147- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
148For more details on Elastic Defend refer to the [helper guide](https://www.elastic.co/guide/en/security/current/install-endpoint.html).
149"""
150severity = "medium"
151tags = [
152    "Domain: Endpoint",
153    "OS: Linux",
154    "Use Case: Threat Detection",
155    "Tactic: Persistence",
156    "Threat: Rootkit",
157    "Data Source: Elastic Endgame",
158    "Data Source: Elastic Defend",
159    "Data Source: Auditd Manager",
160    "Data Source: SentinelOne",
161    "Resources: Investigation Guide",
162]
163timestamp_override = "event.ingested"
164type = "eql"
165query = '''
166process where host.os.type == "linux" and event.type == "start" and process.name == "insmod" and process.args : "*.ko" and
167not process.parent.executable like (
168  "/opt/ds_agent/*", "/usr/sbin/veeamsnap-loader", "/opt/TrendMicro/vls_agent/*", "/opt/intel/oneapi/*",
169  "/opt/commvault/Base/linux_drv", "/bin/falcoctl"
170)
171'''
172
173[[rule.threat]]
174framework = "MITRE ATT&CK"
175
176[[rule.threat.technique]]
177id = "T1547"
178name = "Boot or Logon Autostart Execution"
179reference = "https://attack.mitre.org/techniques/T1547/"
180
181[[rule.threat.technique.subtechnique]]
182id = "T1547.006"
183name = "Kernel Modules and Extensions"
184reference = "https://attack.mitre.org/techniques/T1547/006/"
185
186[rule.threat.tactic]
187id = "TA0003"
188name = "Persistence"
189reference = "https://attack.mitre.org/tactics/TA0003/"
...
toml

The insmod binary is a Linux utility that allows users with root privileges to load kernel modules, which are object files that extend the functionality of the kernel.

Threat actors can abuse this utility to load rootkits, granting them full control over the system and the ability to evade security products.

The detection rule 'Kernel module load via insmod' is designed to identify instances where the insmod binary is used to load a kernel object file (with a .ko extension) on a Linux system. This activity is uncommon and may indicate suspicious or malicious behavior.

Note: This investigation guide uses the Osquery Markdown Plugin introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide. This investigation guide uses placeholder fields to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.

  • Investigate the kernel object file that was loaded via insmod.
    • $osquery_1
  • Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
    • $osquery_2
  • Investigate the kernel ring buffer for any warnings or messages, such as tainted or out-of-tree kernel module loads through dmesg.
  • Investigate syslog for any unusual segfaults or other messages. Rootkits may be installed on targets with different architecture as expected, and could potentially cause segmentation faults.
  • Investigate other alerts associated with the user/host during the past 48 hours.
  • Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
  • Investigate whether the altered scripts call other malicious scripts elsewhere on the file system.
    • If scripts or executables were dropped, retrieve the files and determine if they are malicious:
      • Use a private sandboxed malware analysis system to perform analysis.
        • Observe and collect information about the following activities:
          • Attempts to contact external domains and addresses.
            • Check if the domain is newly registered or unexpected.
            • Check the reputation of the domain or IP address.
          • File access, modification, and creation activities.
  • Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
    • Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
      • $osquery_3
      • $osquery_4
    • Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
      • $osquery_5
  • Investigate whether the user is currently logged in and active.
    • $osquery_6
  • If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
  • If this activity is related to a system administrator who uses cron jobs for administrative purposes, consider adding exceptions for this specific administrator user account.
  • Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
  • Kernel Driver Load - 3e12a439-d002-4944-bc42-171c0dcb9b96
  • Tainted Out-Of-Tree Kernel Module Load - 51a09737-80f7-4551-a3be-dac8ef5d181a
  • Tainted Kernel Module Load - 05cad2fb-200c-407f-b472-02ea8c9e5e4a
  • Attempt to Clear Kernel Ring Buffer - 2724808c-ba5d-48b2-86d2-0002103df753
  • Enumeration of Kernel Modules via Proc - 80084fa9-8677-4453-8680-b891d3c0c778
  • Suspicious Modprobe File Event - 40ddbcc8-6561-44d9-afc8-eefdbfe0cccd
  • Kernel Module Removal - cd66a5af-e34b-4bb0-8931-57d0a043f2ef
  • Enumeration of Kernel Modules - 2d8043ed-5bda-4caf-801c-c1feb7410504
  • Initiate the incident response process based on the outcome of the triage.
  • Isolate the involved host to prevent further post-compromise behavior.
  • If the triage identified malware, search the environment for additional compromised hosts.
    • Implement temporary network rules, procedures, and segmentation to contain the malware.
    • Stop suspicious processes.
    • Immediately block the identified indicators of compromise (IoCs).
    • Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
  • Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
  • Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
  • Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
  • Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).

References

Related rules

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