Unusual Child Processes of RunDLL32

Identifies child processes of unusual instances of RunDLL32 where the command line parameters were suspicious. Misuse of RunDLL32 could indicate malicious activity.

Elastic rule (View on GitHub)

  1[metadata]
  2creation_date = "2020/09/02"
  3integration = ["endpoint", "windows"]
  4maturity = "production"
  5updated_date = "2024/05/21"
  6
  7[transform]
  8[[transform.osquery]]
  9label = "Osquery - Retrieve DNS Cache"
 10query = "SELECT * FROM dns_cache"
 11
 12[[transform.osquery]]
 13label = "Osquery - Retrieve All Services"
 14query = "SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"
 15
 16[[transform.osquery]]
 17label = "Osquery - Retrieve Services Running on User Accounts"
 18query = """
 19SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE
 20NOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR
 21user_account == null)
 22"""
 23
 24[[transform.osquery]]
 25label = "Osquery - Retrieve Service Unsigned Executables with Virustotal Link"
 26query = """
 27SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,
 28services.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =
 29authenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'
 30"""
 31
 32
 33[rule]
 34author = ["Elastic"]
 35description = """
 36Identifies child processes of unusual instances of RunDLL32 where the command line parameters were suspicious. Misuse of
 37RunDLL32 could indicate malicious activity.
 38"""
 39from = "now-60m"
 40index = ["logs-endpoint.events.process-*", "winlogbeat-*", "logs-windows.sysmon_operational-*"]
 41interval = "30m"
 42language = "eql"
 43license = "Elastic License v2"
 44name = "Unusual Child Processes of RunDLL32"
 45note = """## Triage and analysis
 46
 47### Investigating Unusual Child Processes of RunDLL32
 48
 49By examining the specific traits of Windows binaries -- such as process trees, command lines, network connections, registry modifications, and so on -- it's possible to establish a baseline of normal activity. Deviations from this baseline can indicate malicious activity, such as masquerading and deserve further investigation.
 50
 51RunDLL32 is a legitimate Windows utility used to load and execute functions within dynamic-link libraries (DLLs). However, adversaries may abuse RunDLL32 to execute malicious code, bypassing security measures and evading detection. This rule identifies potential abuse by looking for an unusual process creation with no arguments followed by the creation of a child process.
 52
 53> **Note**:
 54> 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.
 55
 56### Possible investigation steps
 57
 58- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
 59- Investigate other alerts associated with the user/host during the past 48 hours.
 60- Investigate any abnormal behavior by the subject process, such as network connections, registry or file modifications, and any spawned child processes.
 61- Investigate the behavior of child processes, such as network connections, registry or file modifications, and any spawned processes.
 62- Inspect the host for suspicious or abnormal behavior in the alert timeframe.
 63- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
 64- Examine the host for derived artifacts that indicate suspicious activities:
 65  - Analyze the process executable using a private sandboxed analysis system.
 66  - Observe and collect information about the following activities in both the sandbox and the subject host:
 67    - Attempts to contact external domains and addresses.
 68      - Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' `process.entity_id`.
 69      - Examine the DNS cache for suspicious or anomalous entries.
 70        - $osquery_0
 71    - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
 72    - Examine the host services for suspicious or anomalous entries.
 73      - $osquery_1
 74      - $osquery_2
 75      - $osquery_3
 76  - Retrieve the files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
 77
 78### False positive analysis
 79
 80- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
 81
 82### Related Rules
 83
 84- Unusual Network Connection via RunDLL32 - 52aaab7b-b51c-441a-89ce-4387b3aea886
 85
 86### Response and Remediation
 87
 88- Initiate the incident response process based on the outcome of the triage.
 89- Isolate the involved host to prevent further post-compromise behavior.
 90- If the triage identified malware, search the environment for additional compromised hosts.
 91  - Implement temporary network rules, procedures, and segmentation to contain the malware.
 92  - Stop suspicious processes.
 93  - Immediately block the identified indicators of compromise (IoCs).
 94  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
 95- Remove and block malicious artifacts identified during triage.
 96- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
 97- 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.
 98- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
 99- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
100"""
101risk_score = 73
102rule_id = "f036953a-4615-4707-a1ca-dc53bf69dcd5"
103severity = "high"
104tags = [
105    "Domain: Endpoint",
106    "OS: Windows",
107    "Use Case: Threat Detection",
108    "Tactic: Defense Evasion",
109    "Data Source: Elastic Defend",
110    "Data Source: Sysmon",
111]
112type = "eql"
113
114query = '''
115sequence with maxspan=1h
116  [process where host.os.type == "windows" and event.type == "start" and
117     (process.name : "rundll32.exe" or process.pe.original_file_name == "RUNDLL32.EXE") and
118      process.args_count == 1
119  ] by process.entity_id
120  [process where host.os.type == "windows" and event.type == "start" and process.parent.name : "rundll32.exe"
121  ] by process.parent.entity_id
122'''
123
124
125[[rule.threat]]
126framework = "MITRE ATT&CK"
127[[rule.threat.technique]]
128id = "T1218"
129name = "System Binary Proxy Execution"
130reference = "https://attack.mitre.org/techniques/T1218/"
131[[rule.threat.technique.subtechnique]]
132id = "T1218.011"
133name = "Rundll32"
134reference = "https://attack.mitre.org/techniques/T1218/011/"
135
136
137
138[rule.threat.tactic]
139id = "TA0005"
140name = "Defense Evasion"
141reference = "https://attack.mitre.org/tactics/TA0005/"

Triage and analysis

Investigating Unusual Child Processes of RunDLL32

By examining the specific traits of Windows binaries -- such as process trees, command lines, network connections, registry modifications, and so on -- it's possible to establish a baseline of normal activity. Deviations from this baseline can indicate malicious activity, such as masquerading and deserve further investigation.

RunDLL32 is a legitimate Windows utility used to load and execute functions within dynamic-link libraries (DLLs). However, adversaries may abuse RunDLL32 to execute malicious code, bypassing security measures and evading detection. This rule identifies potential abuse by looking for an unusual process creation with no arguments followed by the creation of a child process.

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.

Possible investigation steps

  • Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
  • Investigate other alerts associated with the user/host during the past 48 hours.
  • Investigate any abnormal behavior by the subject process, such as network connections, registry or file modifications, and any spawned child processes.
  • Investigate the behavior of child processes, such as network connections, registry or file modifications, and any spawned processes.
  • Inspect the host for suspicious or abnormal behavior in the alert timeframe.
  • Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
  • Examine the host for derived artifacts that indicate suspicious activities:
    • Analyze the process executable using a private sandboxed analysis system.
    • Observe and collect information about the following activities in both the sandbox and the subject host:
      • Attempts to contact external domains and addresses.
        • Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' process.entity_id.
        • Examine the DNS cache for suspicious or anomalous entries.
          • $osquery_0
      • Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
      • Examine the host services for suspicious or anomalous entries.
        • $osquery_1
        • $osquery_2
        • $osquery_3
    • Retrieve the files' SHA-256 hash values using the PowerShell Get-FileHash cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.

False positive analysis

  • This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
  • Unusual Network Connection via RunDLL32 - 52aaab7b-b51c-441a-89ce-4387b3aea886

Response and Remediation

  • 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.
  • Remove and block malicious artifacts identified during triage.
  • Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
  • 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.
  • Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
  • Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).

Related rules

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