Tool
Hunt pack: Akira
957 vendor-native detections · ready to paste into your SIEM · cross-linked to ATT&CK
Vendor-native detections covering the ATT&CK techniques attributed to Akira - a ready-to-deploy hunt pack across Splunk, Elastic and Sentinel.
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Detections
50 shown of 957Powershell Execute COM Object
The following analytic detects the execution of a COM CLSID through PowerShell. It leverages EventCode 4104 and searches for specific script block text indicating the creation of a COM object. This activity is significant as it is commonly used by adversaries and malware, such as the Conti ransomware, to execute commands, potentially for privilege escalation or bypassing User Account Control (UAC). If confirmed malicious, this technique could allow attackers to gain elevated privileges or persist within the environment, posing a significant security risk.
Show query
`powershell` EventCode=4104 ScriptBlockText = "*CreateInstance([type]::GetTypeFromCLSID*"
| fillnull
| stats count min(_time) as firstTime max(_time) as lastTime
BY dest signature signature_id
user_id vendor_product EventID
Guid Opcode Name
Path ProcessID ScriptBlockId
ScriptBlockText
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `powershell_execute_com_object_filter`Powershell Load Module in Meterpreter
The following analytic detects the execution of suspicious PowerShell commands associated with Meterpreter modules, such as "MSF.Powershell" and "MSF.Powershell.Meterpreter". It leverages PowerShell Script Block Logging (EventCode=4104) to capture and analyze the full command sent to PowerShell. This activity is significant as it indicates potential post-exploitation actions, including credential dumping and persistence mechanisms. If confirmed malicious, an attacker could gain extensive control over the compromised system, escalate privileges, and maintain long-term access, posing a severe threat to the environment.
Show query
`powershell` EventCode=4104 ScriptBlockText IN ("*MSF.Powershell*","*MSF.Powershell.Meterpreter*","*MSF.Powershell.Meterpreter.Kiwi*","*MSF.Powershell.Meterpreter.Transport*")
| fillnull
| stats count min(_time) as firstTime max(_time) as lastTime
BY dest signature signature_id
user_id vendor_product EventID
Guid Opcode Name
Path ProcessID ScriptBlockId
ScriptBlockText
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `powershell_load_module_in_meterpreter_filter`Powershell Processing Stream Of Data
The following analytic detects suspicious PowerShell script execution involving compressed stream data processing, identified via EventCode 4104. It leverages PowerShell Script Block Logging to flag scripts using `IO.Compression`, `IO.StreamReader`, or decompression methods. This activity is significant as it often indicates obfuscated PowerShell or embedded .NET/binary execution, which are common tactics for evading detection. If confirmed malicious, this behavior could allow attackers to execute hidden code, escalate privileges, or maintain persistence within the environment.
Show query
`powershell` EventCode=4104 ScriptBlockText = "*IO.Compression.*" OR ScriptBlockText = "*IO.StreamReader*" OR ScriptBlockText = "*]::Decompress*"
| fillnull
| stats count min(_time) as firstTime max(_time) as lastTime
BY dest signature signature_id
user_id vendor_product EventID
Guid Opcode Name
Path ProcessID ScriptBlockId
ScriptBlockText
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `powershell_processing_stream_of_data_filter`Powershell Using memory As Backing Store
The following analytic detects suspicious PowerShell script execution using memory streams as a backing store, identified via EventCode 4104. It leverages PowerShell Script Block Logging to capture scripts that create new objects with memory streams, often used to decompress and execute payloads in memory. This activity is significant as it indicates potential in-memory execution of malicious code, bypassing traditional file-based detection. If confirmed malicious, this technique could allow attackers to execute arbitrary code, maintain persistence, or escalate privileges without leaving a trace on the disk.
Show query
`powershell` EventCode=4104 ScriptBlockText = *New-Object* ScriptBlockText = *IO.MemoryStream*
| fillnull
| stats count min(_time) as firstTime max(_time) as lastTime
BY dest signature signature_id
user_id vendor_product EventID
Guid Opcode Name
Path ProcessID ScriptBlockId
ScriptBlockText
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `powershell_using_memory_as_backing_store_filter`Process Deleting Its Process File Path
The following analytic identifies a process attempting to delete its own file path, a behavior often associated with defense evasion techniques. This detection leverages Sysmon EventCode 1 logs, focusing on command lines executed via cmd.exe that include deletion commands. This activity is significant as it may indicate malware, such as Clop ransomware, trying to evade detection by removing its executable file if certain conditions are met. If confirmed malicious, this could allow the attacker to persist undetected, complicating incident response and remediation efforts.
Show query
`sysmon` EventCode=1 CommandLine = "* /c *" CommandLine = "* del*" Image = "*\\cmd.exe" | eval result = if(like(process,"%".parent_process."%"), "Found", "Not Found") | stats min(_time) as firstTime max(_time) as lastTime count by action dest original_file_name parent_process parent_process_exec parent_process_guid parent_process_id parent_process_name parent_process_path process process_exec process_guid process_hash process_id process_integrity_level process_name process_path user user_id vendor_product result | where result = "Found" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `process_deleting_its_process_file_path_filter`
Randomly Generated Scheduled Task Name
The following analytic detects the creation of a Scheduled Task with a high entropy, randomly generated name, leveraging Event ID 4698. It uses the `ut_shannon` function from the URL ToolBox Splunk application to measure the entropy of the Task Name. This activity is significant as adversaries often use randomly named Scheduled Tasks for lateral movement and remote code execution, employing tools like Impacket or CrackMapExec. If confirmed malicious, this could allow attackers to execute arbitrary code remotely, potentially leading to further compromise and persistence within the network.
Show query
`wineventlog_security` EventCode=4698 | xmlkv Message | lookup ut_shannon_lookup word as Task_Name | where ut_shannon > 3 | table _time, dest, Task_Name, ut_shannon, Command, Author, Enabled, Hidden | `randomly_generated_scheduled_task_name_filter`
Recursive Delete of Directory In Batch CMD
The following analytic detects the execution of a batch command designed to recursively delete files or directories, a technique often used by ransomware like Reddot to delete files in the recycle bin and prevent recovery. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions that include specific flags for recursive and quiet deletions. This activity is significant as it indicates potential ransomware behavior aimed at data destruction. If confirmed malicious, it could lead to significant data loss and hinder recovery efforts, severely impacting business operations.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE `process_cmd` Processes.process=*/c* Processes.process="* rd *" Processes.process="*/s*" Processes.process="*/q*"
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `recursive_delete_of_directory_in_batch_cmd_filter`Remcos client registry install entry
The following analytic detects the presence of a registry key associated with the Remcos RAT agent on a host. It leverages data from the Endpoint.Processes and Endpoint.Registry data models in Splunk, focusing on instances where the "license" key is found in the "Software\Remcos" path. This behavior is significant as it indicates potential compromise by the Remcos RAT, a remote access Trojan used for unauthorized access and data exfiltration. If confirmed malicious, the attacker could gain control over the system, steal sensitive information, or use the compromised host for further attacks. Immediate investigation and remediation are required.
Show query
| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Registry WHERE (Registry.registry_path=*\\Software\\Remcos*) by Registry.action Registry.dest Registry.process_guid Registry.process_id Registry.registry_hive Registry.registry_path Registry.registry_key_name Registry.registry_value_data Registry.registry_value_name Registry.registry_value_type Registry.status Registry.user Registry.vendor_product | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` |`remcos_client_registry_install_entry_filter`
Remote System Discovery with Adsisearcher
The following analytic detects the use of the `[Adsisearcher]` type accelerator in PowerShell scripts to query Active Directory for domain computers. It leverages PowerShell Script Block Logging (EventCode=4104) to identify specific script blocks containing `adsisearcher` and `objectcategory=computer` with methods like `findAll()` or `findOne()`. This activity is significant as it may indicate an attempt by adversaries or Red Teams to perform Active Directory discovery and gain situational awareness. If confirmed malicious, this could lead to further reconnaissance and potential lateral movement within the network.
Show query
`powershell` EventCode=4104 ScriptBlockText = "*adsisearcher*" AND ScriptBlockText = "*objectcategory=computer*" AND ScriptBlockText IN ("*findAll()*","*findOne()*")
| fillnull
| stats count min(_time) as firstTime max(_time) as lastTime
BY dest signature signature_id
user_id vendor_product EventID
Guid Opcode Name
Path ProcessID ScriptBlockId
ScriptBlockText
| `security_content_ctime(firstTime)`
| `remote_system_discovery_with_adsisearcher_filter`Remote System Discovery with Dsquery
The following analytic detects the execution of `dsquery.exe` with the `computer` argument, which is used to discover remote systems within a domain. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. Remote system discovery is significant as it indicates potential reconnaissance activities by adversaries or Red Teams to map out network resources and Active Directory structures. If confirmed malicious, this activity could lead to further exploitation, lateral movement, and unauthorized access to critical systems within the network.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE (
Processes.process_name="dsquery.exe"
)
(Processes.process="*computer*")
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `remote_system_discovery_with_dsquery_filter`Remote System Discovery with Wmic
The following analytic detects the execution of `wmic.exe` with specific command-line arguments used to discover remote systems within a domain. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as it indicates potential reconnaissance efforts by adversaries to map out network resources and Active Directory structures. If confirmed malicious, this behavior could allow attackers to gain situational awareness, identify critical systems, and plan further attacks, potentially leading to unauthorized access and data exfiltration.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name="wmic.exe") (Processes.process=*/NAMESPACE:\\\\root\\directory\\ldap* AND Processes.process=*ds_computer* AND Processes.process="*GET ds_samaccountname*") by Processes.action Processes.dest Processes.original_file_name Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path Processes.process Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `remote_system_discovery_with_wmic_filter`
Revil Common Exec Parameter
The following analytic detects the execution of command-line parameters commonly associated with REVIL ransomware, such as "-nolan", "-nolocal", "-fast", and "-full". It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs mapped to the `Processes` node of the `Endpoint` data model. This activity is significant because these parameters are indicative of ransomware attempting to encrypt files on a compromised machine. If confirmed malicious, this could lead to widespread data encryption, rendering critical files inaccessible and potentially causing significant operational disruption.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE Processes.process = "* -nolan *"
OR
Processes.process = "* -nolocal *"
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `revil_common_exec_parameter_filter`Revil Registry Entry
The following analytic identifies suspicious modifications in the registry entry, specifically targeting paths used by malware like REVIL. It detects changes in registry paths such as `SOFTWARE\\WOW6432Node\\Facebook_Assistant` and `SOFTWARE\\WOW6432Node\\BlackLivesMatter`. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on registry modifications linked to process GUIDs. This activity is significant as it indicates potential malware persistence mechanisms, often used by advanced persistent threats (APTs) and ransomware. If confirmed malicious, this could allow attackers to maintain persistence, encrypt files, and store critical ransomware-related information on compromised hosts.
Show query
| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Registry WHERE (Registry.registry_path="*\\SOFTWARE\\WOW6432Node\\Facebook_Assistant\\*" OR Registry.registry_path="*\\SOFTWARE\\WOW6432Node\\BlackLivesMatter*") by Registry.action Registry.dest Registry.process_guid Registry.process_id Registry.registry_hive Registry.registry_path Registry.registry_key_name Registry.registry_value_data Registry.registry_value_name Registry.registry_value_type Registry.status Registry.user Registry.vendor_product | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `revil_registry_entry_filter`
Risk Rule for Dev Sec Ops by Repository
The following analytic identifies high-risk activities within repositories by correlating repository data with risk scores. It leverages findings and intermediate findings created by detections from the Dev Sec Ops analytic stories, summing risk scores and capturing source and user information. The detection focuses on high-risk scores above 100 and sources with more than three occurrences. This activity is significant as it highlights repositories frequently targeted by threats, providing insights into potential vulnerabilities. If confirmed malicious, attackers could exploit these repositories, leading to data breaches or infrastructure compromise.
Show query
| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime sum(All_Risk.calculated_risk_score) as sum_risk_score, values(All_Risk.annotations.mitre_attack.mitre_tactic) as annotations.mitre_attack.mitre_tactic, values(All_Risk.annotations.mitre_attack.mitre_technique_id) as annotations.mitre_attack.mitre_technique_id, dc(All_Risk.annotations.mitre_attack.mitre_technique_id) as mitre_technique_id_count values(source) as source, dc(source) as source_count FROM datamodel=Risk.All_Risk WHERE All_Risk.analyticstories="Dev Sec Ops" All_Risk.risk_object_type = "other" BY All_Risk.risk_object All_Risk.risk_object_type All_Risk.annotations.mitre_attack.mitre_tactic | `drop_dm_object_name(All_Risk)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | where source_count > 3 and sum_risk_score > 100 | `risk_rule_for_dev_sec_ops_by_repository_filter`
Rundll32 Shimcache Flush
The following analytic detects the execution of a suspicious rundll32 command line used to clear the shim cache. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs and command-line arguments. This activity is significant because clearing the shim cache is an anti-forensic technique aimed at evading detection and removing forensic artifacts. If confirmed malicious, this action could hinder incident response efforts, allowing an attacker to cover their tracks and maintain persistence on the compromised machine.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE `process_rundll32`
AND
Processes.process = "*apphelp.dll,ShimFlushCache*"
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `rundll32_shimcache_flush_filter`Ryuk Wake on LAN Command
The following analytic detects the use of Wake-on-LAN commands associated with Ryuk ransomware. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific process and command-line activities. This behavior is significant as Ryuk ransomware uses Wake-on-LAN to power on devices in a compromised network, increasing its encryption success rate. If confirmed malicious, this activity could lead to widespread ransomware encryption across multiple endpoints, causing significant operational disruption and data loss. Immediate isolation and thorough investigation of the affected endpoints are crucial to mitigate the impact.
Show query
| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime
FROM datamodel=Endpoint.Processes WHERE
Processes.process IN (
"* 8 LAN",
"* 8 LAN *",
"* 9 REP",
"* 9 REP *"
)
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec
Processes.parent_process_guid Processes.parent_process_id
Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `ryuk_wake_on_lan_command_filter`SAM Database File Access Attempt
The following analytic detects attempts to access the SAM, SYSTEM, or SECURITY database files within the `windows\system32\config` directory using Windows Security EventCode 4663. This detection leverages Windows Security Event logs to identify unauthorized access attempts. Monitoring this activity is crucial as it indicates potential credential access attempts, possibly exploiting vulnerabilities like CVE-2021-36934. If confirmed malicious, an attacker could extract user passwords, leading to unauthorized access, privilege escalation, and further compromise of the system.
Show query
`wineventlog_security` (EventCode=4663) ProcessName!=*\\dllhost.exe ObjectName IN ("*\\Windows\\System32\\config\\SAM*","*\\Windows\\System32\\config\\SYSTEM*","*\\Windows\\System32\\config\\SECURITY*") | stats values(AccessList) count by ProcessName ObjectName dest src_user | rename ProcessName as process_name | `sam_database_file_access_attempt_filter`SAP NetWeaver Visual Composer Exploitation Attempt
Detects potential exploitation attempts targeting CVE-2025-31324, a critical unauthenticated file upload vulnerability in SAP NetWeaver Visual Composer.
This flaw allows remote attackers to send specially crafted POST requests to the /developmentserver/metadatauploader endpoint, enabling arbitrary file uploads—commonly webshells—resulting in full system compromise.
The detection looks for HTTP HEAD or POST requests with a 200 OK status to sensitive Visual Composer endpoints, which may indicate reconnaissance or active exploitation.
Successful exploitation can lead to attackers gaining privileged access, deploying malware, and impacting business-critical SAP resources.
Immediate patching and investigation of suspicious activity are strongly recommended, as this vulnerability is being actively exploited in the wild.
Show query
| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime
FROM datamodel=Web.Web WHERE
Web.url IN (
"*/ctc/CTCWebService/CTCWebServiceBean",
"*/CTCWebService/CTCWebServiceBean",
"*/VisualComposer/services/DesignTimeService"
)
Web.http_method IN ("HEAD", "POST")
Web.status=200
BY Web.src Web.dest Web.http_method
Web.url Web.http_user_agent Web.url_length
| `drop_dm_object_name("Web")`
| eval action=case(
http_method="HEAD", "Recon/Probe",
http_method="POST", "Possible Exploitation"
)
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| table firstTime lastTime src dest http_method
action url user_agent url_length
| `sap_netweaver_visual_composer_exploitation_attempt_filter`SQL Injection with Long URLs
The following analytic detects long URLs containing multiple SQL commands, indicating a potential SQL injection attack. This detection leverages web traffic data, specifically targeting web server destinations with URLs longer than 1024 characters or HTTP user agents longer than 200 characters. SQL injection is significant as it allows attackers to manipulate a web application's database, potentially leading to unauthorized data access or modification. If confirmed malicious, this activity could result in data breaches, unauthorized access, and complete system compromise. Immediate investigation and validation of alerts are crucial to mitigate these risks.
Show query
| tstats `security_content_summariesonly` count FROM datamodel=Web
WHERE Web.dest_category=web_server
AND
(Web.url_length > 1024
OR
Web.http_user_agent_length > 200)
BY Web.src Web.dest Web.url
Web.url_length Web.http_user_agent
| `drop_dm_object_name("Web")`
| eval url=lower(url)
| eval num_sql_cmds=mvcount(split(url, "alter%20table")) + mvcount(split(url, "between")) + mvcount(split(url, "create%20table")) + mvcount(split(url, "create%20database")) + mvcount(split(url, "create%20index")) + mvcount(split(url, "create%20view")) + mvcount(split(url, "delete")) + mvcount(split(url, "drop%20database")) + mvcount(split(url, "drop%20index")) + mvcount(split(url, "drop%20table")) + mvcount(split(url, "exists")) + mvcount(split(url, "exec")) + mvcount(split(url, "group%20by")) + mvcount(split(url, "having")) + mvcount(split(url, "insert%20into")) + mvcount(split(url, "inner%20join")) + mvcount(split(url, "left%20join")) + mvcount(split(url, "right%20join")) + mvcount(split(url, "full%20join")) + mvcount(split(url, "select")) + mvcount(split(url, "distinct")) + mvcount(split(url, "select%20top")) + mvcount(split(url, "union")) + mvcount(split(url, "xp_cmdshell")) - 24
| where num_sql_cmds > 3
| `sql_injection_with_long_urls_filter`SchCache Change By App Connect And Create ADSI Object
The following analytic detects an application attempting to connect and create an ADSI object to perform an LDAP query. It leverages Sysmon EventCode 11 to identify changes in the Active Directory Schema cache files located in %LOCALAPPDATA%\Microsoft\Windows\SchCache or %systemroot%\SchCache. This activity is significant as it can indicate the presence of suspicious applications, such as ransomware, using ADSI object APIs for LDAP queries. If confirmed malicious, this behavior could allow attackers to gather sensitive directory information, potentially leading to further exploitation or lateral movement within the network.
Show query
`sysmon` EventCode=11 TargetFilename = "*\\Windows\\SchCache\\*" TargetFilename
= "*.sch*" NOT (Image IN ("*\\Windows\\system32\\mmc.exe"))
| stats count min(_time)
as firstTime max(_time) as lastTime by action dest file_name file_path process_guid
process_id user_id vendor_product process_name
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `schcache_change_by_app_connect_and_create_adsi_object_filter`Schedule Task with HTTP Command Arguments
The following analytic detects the creation of scheduled tasks on Windows systems that include HTTP command arguments, using Windows Security EventCode 4698. It identifies tasks registered via schtasks.exe or TaskService with HTTP in their command arguments. This behavior is significant as it often indicates malware activity or the use of Living off the Land binaries (lolbins) to download additional payloads. If confirmed malicious, this activity could lead to data exfiltration, malware propagation, or unauthorized access to sensitive information, necessitating immediate investigation and mitigation.
Show query
`wineventlog_security` EventCode=4698
| xmlkv Message
| search Arguments IN ("*http*")
| stats count min(_time) as firstTime max(_time) as lastTime
BY dest, Task_Name, Command,
Author, Enabled, Hidden,
Arguments
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `schedule_task_with_http_command_arguments_filter`Schedule Task with Rundll32 Command Trigger
The following analytic detects the creation of scheduled tasks in Windows that use the rundll32 command. It leverages Windows Security EventCode 4698, which logs the creation of scheduled tasks, and filters for tasks executed via rundll32. This activity is significant as it is a common technique used by malware, such as TrickBot, to persist in an environment or deliver additional payloads. If confirmed malicious, this could lead to data theft, ransomware deployment, or other damaging outcomes. Immediate investigation and mitigation are crucial to prevent further compromise.
Show query
`wineventlog_security` EventCode=4698
| xmlkv Message
| search Command IN ("*rundll32*")
| stats count min(_time) as firstTime max(_time) as lastTime
BY dest, Task_Name, Command,
Author, Enabled, Hidden,
Arguments
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `schedule_task_with_rundll32_command_trigger_filter`Scheduled Task Creation on Remote Endpoint using At
The following analytic detects the creation of scheduled tasks on remote Windows endpoints using the at.exe command. This detection leverages Endpoint Detection and Response (EDR) telemetry, focusing on process creation events involving at.exe with remote command-line arguments. Identifying this activity is significant for a SOC as it may indicate lateral movement or remote code execution attempts by an attacker. If confirmed malicious, this activity could lead to unauthorized access, persistence, or execution of malicious code, potentially resulting in data theft or further compromise of the network.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=at.exe OR Processes.original_file_name=at.exe) (Processes.process=*\\\\*) by Processes.action Processes.dest Processes.original_file_name Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path Processes.process Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `scheduled_task_creation_on_remote_endpoint_using_at_filter`
Scheduled Task Deleted Or Created via CMD
The following analytic detects the creation or deletion of scheduled tasks via schtasks.exe when invoked with create or delete flags, specifically focusing on those executions where the process includes additional parameters such as /tr, /sc, or /ru. The detection uses Endpoint Detection and Response (EDR) telemetry mapped to the Endpoint data model, and filters out events originating from trusted system paths like C:\Windows\System32 or C:\Program Files. It further narrows results to cases where schtasks.exe is launched by potentially suspicious parent processes such as cmd.exe, wscript.exe, or cscript.exe, and excludes service accounts. This behavior may indicate adversary efforts to gain persistence or evade detection by manipulating scheduled tasks using scripts or command shells. If confirmed malicious, such activity could lead to unauthorized code execution or the removal of monitoring mechanisms on endpoints.
Show query
| tstats `security_content_summariesonly`
count
min(_time) as firstTime
max(_time) as lastTime
FROM datamodel=Endpoint.Processes WHERE
Processes.parent_process_name="cmd.exe"
Processes.process_name="schtasks.exe"
Processes.process IN (
"*/create*",
"*-create*",
"*/delete*",
"*-delete*"
)
NOT Processes.process IN (
"* \"C:\\Program Files (x86)\\*",
"* \"C:\\Program Files\\*",
"* \"C:\\Windows\\System32\\*",
"* \"C:\\Windows\\SysWOW64\\*",
"* C:\\Program Files (x86)\\*",
"* C:\\Program Files\\*",
"* C:\\Windows\\System32\\*",
"* C:\\Windows\\SysWOW64\\*"
)
NOT Processes.user="*$"
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec
Processes.parent_process_guid Processes.parent_process_id
Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `scheduled_task_deleted_or_created_via_cmd_filter`
Scheduled Task Initiation on Remote Endpoint
The following analytic detects the use of 'schtasks.exe' to start a Scheduled Task on a remote endpoint. This detection leverages Endpoint Detection and Response (EDR) data, focusing on process details such as process name, parent process, and command-line executions. This activity is significant as adversaries often abuse Task Scheduler for lateral movement and remote code execution. If confirmed malicious, this behavior could allow attackers to execute arbitrary code remotely, potentially leading to further compromise of the network.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE (
Processes.process_name=schtasks.exe
OR
Processes.original_file_name=schtasks.exe
)
(Processes.process= "* /S *" AND Processes.process=*/run*)
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `scheduled_task_initiation_on_remote_endpoint_filter`Schtasks Run Task On Demand
The following analytic detects the execution of a Windows Scheduled Task on demand via the shell or command line. It leverages process-related data, including process name, parent process, and command-line executions, sourced from endpoint logs. The detection focuses on 'schtasks.exe' with an associated 'run' command. This activity is significant as adversaries often use it to force the execution of their created Scheduled Tasks for persistent access or lateral movement within a compromised machine. If confirmed malicious, this could allow attackers to maintain persistence or move laterally within the network, potentially leading to further compromise.
Show query
| tstats `security_content_summariesonly` values(Processes.process) as process values(Processes.process_id) as process_id count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE Processes.process_name = "schtasks.exe" Processes.process = "*/run*"
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `schtasks_run_task_on_demand_filter`Schtasks scheduling job on remote system
The following analytic detects the use of 'schtasks.exe' to create a scheduled task on a remote system, indicating potential lateral movement or remote code execution. It leverages process data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line arguments and flags. This activity is significant as it may signify an adversary's attempt to persist or execute code remotely. If confirmed malicious, this could allow attackers to maintain access, execute arbitrary commands, or further infiltrate the network, posing a severe security risk.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE (
Processes.process_name = schtasks.exe
OR
Processes.original_file_name=schtasks.exe
)
(Processes.process="*/create*" AND Processes.process="*/s *")
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `schtasks_scheduling_job_on_remote_system_filter`Schtasks used for forcing a reboot
The following analytic detects the use of 'schtasks.exe' to schedule forced system reboots using the 'shutdown' and '/create' flags. It leverages endpoint process data to identify instances where these specific command-line arguments are used. This activity is significant because it may indicate an adversary attempting to disrupt operations or force a reboot to execute further malicious actions. If confirmed malicious, this could lead to system downtime, potential data loss, and provide an attacker with an opportunity to execute additional payloads or evade detection.
Show query
| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE Processes.process_name=schtasks.exe Processes.process="*shutdown*" Processes.process="*/create *"
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `schtasks_used_for_forcing_a_reboot_filter`Sdelete Application Execution
The following analytic detects the execution of the sdelete.exe application, a Sysinternals tool often used by adversaries to securely delete files and remove forensic evidence from a targeted host. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs. Monitoring this activity is crucial as sdelete.exe is not commonly used in regular operations and its presence may indicate an attempt to cover malicious activities. If confirmed malicious, this could lead to the loss of critical forensic data, hindering incident response and investigation efforts.
Show query
| tstats `security_content_summariesonly` values(Processes.process) as process values(Processes.parent_process) as parent_process values(Processes.process_id) as process_id count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE (
Processes.process_name="sdelete.exe"
OR
Processes.original_file_name="sdelete.exe"
)
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `sdelete_application_execution_filter`SecretDumps Offline NTDS Dumping Tool
The following analytic detects the potential use of the secretsdump.py tool to dump NTLM hashes from a copy of ntds.dit and the SAM, SYSTEM, and SECURITY registry hives. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line patterns and process names associated with secretsdump.py. This activity is significant because it indicates an attempt to extract sensitive credential information offline, which is a common post-exploitation technique. If confirmed malicious, this could allow an attacker to obtain NTLM hashes, facilitating further lateral movement and potential privilege escalation within the network.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE Processes.process_name = "python*.exe" Processes.process = "*.py*" Processes.process = "*-ntds*" (Processes.process = "*-system*"
OR
Processes.process = "*-sam*"
OR
Processes.process = "*-security*"
OR
Processes.process = "*-bootkey*")
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `secretdumps_offline_ntds_dumping_tool_filter`Set Default PowerShell Execution Policy To Unrestricted or Bypass
The following analytic detects changes to the PowerShell ExecutionPolicy in the registry to "Unrestricted" or "Bypass." It leverages data from Endpoint Detection and Response (EDR) agents, focusing on registry modifications under the path *Software\Microsoft\Powershell\1\ShellIds\Microsoft.PowerShell*. This activity is significant because setting the ExecutionPolicy to these values can allow the execution of potentially malicious scripts without restriction. If confirmed malicious, this could enable an attacker to execute arbitrary code, leading to further compromise of the system and potential escalation of privileges.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry WHERE (Registry.registry_path=*Software\\Microsoft\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* Registry.registry_value_name=ExecutionPolicy (Registry.registry_value_data=Unrestricted OR Registry.registry_value_data=Bypass)) by Registry.action Registry.dest Registry.process_guid Registry.process_id Registry.registry_hive Registry.registry_path Registry.registry_key_name Registry.registry_value_data Registry.registry_value_name Registry.registry_value_type Registry.status Registry.user Registry.vendor_product | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter`
Shai-Hulud 2 Exfiltration Artifact Files
Detects creation of exfiltration artifact files associated with Shai-Hulud 2.0 npm supply
chain malware. The malware creates cloud.json, contents.json, environment.json, truffleSecrets.json,
and actionsSecrets.json files containing harvested credentials from AWS, Azure, GCP, GitHub secrets,
and environment variables. These files are staged before being pushed to attacker-controlled repositories.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where Filesystem.file_name IN ( "cloud.json", "contents.json", "environment.json", "truffleSecrets.json", "actionsSecrets.json" ) by Filesystem.action Filesystem.dest Filesystem.file_access_time Filesystem.file_create_time Filesystem.file_hash Filesystem.file_modify_time Filesystem.file_name Filesystem.file_path Filesystem.file_acl Filesystem.file_size Filesystem.process_guid Filesystem.process_id Filesystem.user Filesystem.vendor_product | `drop_dm_object_name(Filesystem)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `shai_hulud_2_exfiltration_artifact_files_filter`
Short Lived Scheduled Task
The following analytic detects the creation and deletion of scheduled tasks within a short time frame (less than 30 seconds) using Windows Security EventCodes 4698 and 4699. This behavior is identified by analyzing Windows Security Event Logs and leveraging the Windows TA for parsing. Such activity is significant as it may indicate lateral movement or remote code execution attempts by adversaries. If confirmed malicious, this could lead to unauthorized access, data exfiltration, or execution of malicious payloads, necessitating prompt investigation and response by security analysts.
Show query
`wineventlog_security` EventCode=4698 OR EventCode=4699 | xmlkv Message | transaction Task_Name startswith=(EventCode=4698) endswith=(EventCode=4699) | eval short_lived=case((duration<30),"TRUE") | search short_lived = TRUE | rename ComputerName as dest | table _time, dest, Account_Name, Command, Task_Name, short_lived | `short_lived_scheduled_task_filter`
Short Lived Windows Accounts
The following analytic detects the rapid creation and deletion of Windows accounts within a short time frame of 1 hour. It leverages the "Change" data model in Splunk, specifically monitoring events with result IDs 4720 (account creation) and 4726 (account deletion). This behavior is significant as it may indicate an attacker attempting to create and remove accounts quickly to evade detection or gain unauthorized access. If confirmed malicious, this activity could lead to unauthorized access, privilege escalation, or further malicious actions within the environment. Immediate investigation of flagged events is crucial to mitigate potential damage.
Show query
| tstats `security_content_summariesonly` values(All_Changes.result_id) as result_id count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change
WHERE All_Changes.result_id=4720
OR
All_Changes.result_id=4726
BY _time span=1h All_Changes.user
All_Changes.dest All_Changes.Account_Management.src All_Changes.Account_Management.src_user
| `security_content_ctime(lastTime)`
| `security_content_ctime(firstTime)`
| `drop_dm_object_name("All_Changes")`
| `drop_dm_object_name("Account_Management")`
| transaction user connected=false maxspan=60m
| eval create_result_id=mvindex(result_id, 0)
| eval delete_result_id=mvindex(result_id, 1)
| search create_result_id = 4720 delete_result_id=4726
| table firstTime lastTime count user src src_user dest create_result_id delete_result_id
| `short_lived_windows_accounts_filter`Single Letter Process On Endpoint
The following analytic detects processes with names consisting of a single letter, which is often indicative of malware or an attacker attempting to evade detection. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant because attackers use such techniques to obscure their presence and carry out malicious activities like data theft or ransomware attacks. If confirmed malicious, this behavior could lead to unauthorized access, data exfiltration, or system compromise. Immediate investigation is required to determine the legitimacy of the process.
Show query
| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime
from datamodel=Endpoint.Processes where
Processes.process_name IN (
"_.exe",
"-.exe",
",.exe",
";.exe",
"!.exe",
"'.exe"
"(.exe",
"(.exe",
").exe",
").exe",
"@.exe",
"&.exe",
"#.exe",
"%.exe",
"`.exe",
"^.exe",
"+.exe",
"=.exe",
"~.exe",
"$.exe",
"0.exe",
"1.exe",
"2.exe",
"3.exe",
"4.exe",
"5.exe",
"6.exe",
"7.exe",
"8.exe",
"9.exe",
"a.exe",
"b.exe",
"c.exe",
"d.exe",
"e.exe",
"f.exe",
"g.exe",
"h.exe",
"i.exe",
"j.exe",
"k.exe",
"l.exe",
"m.exe",
"N.exe",
"o.exe",
"p.exe",
"q.exe",
"r.exe",
"s.exe",
"t.exe",
"u.exe",
"v.exe",
"w.exe",
"x.exe",
"y.exe",
"z.exe",
)
by Processes.action Processes.dest Processes.original_file_name Processes.parent_process
Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id
Processes.parent_process_name Processes.parent_process_path Processes.process
Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id
Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(lastTime)`
| `security_content_ctime(firstTime)`
| `single_letter_process_on_endpoint_filter`
Sqlite Module In Temp Folder
The following analytic detects the creation of sqlite3.dll files in the %temp% folder. It leverages Sysmon EventCode 11 to identify when these files are written to the temporary directory. This activity is significant because it is associated with IcedID malware, which uses the sqlite3 module to parse browser databases and steal sensitive information such as banking details, credit card information, and credentials. If confirmed malicious, this behavior could lead to significant data theft and compromise of user accounts.
Show query
`sysmon` EventCode=11 (TargetFilename = "*\\sqlite32.dll" OR TargetFilename = "*\\sqlite64.dll") (TargetFilename = "*\\temp\\*") | stats count min(_time) as firstTime max(_time) as lastTime by action dest file_name file_path process_guid process_id user_id vendor_product | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `sqlite_module_in_temp_folder_filter`
Sunburst Correlation DLL and Network Event
The following analytic identifies the loading of the malicious SolarWinds.Orion.Core.BusinessLayer.dll by SolarWinds.BusinessLayerHost.exe and subsequent DNS queries to avsvmcloud.com. It uses Sysmon EventID 7 for DLL loading and Event ID 22 for DNS queries, correlating these events within a 12-14 day period. This activity is significant as it indicates potential Sunburst malware infection, a known supply chain attack. If confirmed malicious, this could lead to unauthorized network access, data exfiltration, and further compromise of the affected systems.
Show query
`sysmon`
(
EventCode=7
ImageLoaded=*SolarWinds.Orion.Core.BusinessLayer.dll
)
OR
(
EventCode=22
QueryName=*avsvmcloud.com
)
| eventstats dc(EventCode) AS dc_events
| where dc_events=2
| stats count min(_time) as firstTime
max(_time) as lastTime
by Image ImageLoaded dest
loaded_file loaded_file_path original_file_name
process_exec process_guid process_hash
process_id process_name process_path
service_dll_signature_exists service_dll_signature_verified signature
signature_id user_id vendor_product
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `sunburst_correlation_dll_and_network_event_filter`Suspicious Computer Account Name Change
The following analytic detects a suspicious computer account name change in Active Directory. It leverages Event ID 4781, which logs account name changes, to identify instances where a computer account name is changed to one that does not end with a `$`. This behavior is significant as it may indicate an attempt to exploit CVE-2021-42278 and CVE-2021-42287, which can lead to domain controller impersonation and privilege escalation. If confirmed malicious, this activity could allow an attacker to gain elevated privileges and potentially control the domain.
Show query
`wineventlog_security` EventCode=4781 OldTargetUserName="*$" NewTargetUserName!="*$" | table _time, Computer, Caller_User_Name, OldTargetUserName, NewTargetUserName | rename Computer as dest | `suspicious_computer_account_name_change_filter`
Suspicious Copy on System32
The following analytic detects potentially suspicious file copy operations targeting the
System32 or SysWow64 directories as source, often indicative of malicious activity.
It leverages data from Endpoint Detection and Response (EDR) agents,
focusing on activity initiated by command-line tools like cmd.exe or PowerShell.
This behavior is significant as it may indicate an attempt to evade defenses by copying
an existing binary from the system directory and renaming it.
If confirmed malicious, this activity could allow an attacker to execute
code undetected and potentially leading to system compromise or further lateral movement
within the network.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
as lastTime from datamodel=Endpoint.Processes where
Processes.parent_process_name IN (
"cmd.exe",
"powershell.exe",
"pwsh.exe",
"sqlps.exe",
"sqltoolsps.exe"
)
(
Processes.process_name IN ("copy.exe", "xcopy.exe")
OR
Processes.original_file_name IN ("copy.exe", "xcopy.exe")
)
Processes.process IN (
"* \"C:\\Windows\\System32\\*",
"* \'C:\\Windows\\System32\\*",
"* C:\\Windows\\System32\\*",
"* \"C:\\Windows\\SysWow64\\*",
"* \'C:\\Windows\\SysWow64\\*",
"* C:\\Windows\\SysWow64\\*"
)
by Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid Processes.process_hash
Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path
Processes.user Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `suspicious_copy_on_system32_filter`
Suspicious Curl Network Connection
The following analytic detects the use of the curl command contacting suspicious remote domains, such as s3.amazonaws.com, which is indicative of Command and Control (C2) activity or downloading further implants. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs and command-line arguments. This activity is significant as it may indicate the presence of MacOS adware or other malicious software attempting to establish persistence or exfiltrate data. If confirmed malicious, this could allow attackers to maintain control over the compromised system and deploy additional payloads.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
as lastTime from datamodel=Endpoint.Processes where Processes.process_name IN ("curl", "curl.exe")
Processes.process IN ("*s3.amazonaws.com*")
by Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec
Processes.parent_process_guid Processes.parent_process_id
Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id
Processes.process_integrity_level Processes.process_name
Processes.process_path Processes.user Processes.user_id
Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `suspicious_curl_network_connection_filter`
Suspicious Java Classes
The following analytic identifies suspicious Java classes often used for remote command execution exploits in Java frameworks like Apache Struts.
It detects this activity by analyzing HTTP POST requests with specific content patterns using Splunk's `stream_http` data source.
This behavior is significant because it may indicate an attempt to exploit vulnerabilities in web applications, potentially leading to unauthorized remote code execution.
If confirmed malicious, this activity could allow attackers to execute arbitrary commands on the server, leading to data breaches, system compromise, and further network infiltration.
Show query
`stream_http`
http_method=POST
http_content_length>1
| regex form_data="(?i)java\.lang\.(?:runtime|processbuilder)"
| rename src_ip as src
| stats count earliest(_time) as firstTime
latest(_time) as lastTime
values(url) as uri
values(status) as status
values(http_user_agent) as http_user_agent
BY src dest
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `suspicious_java_classes_filter`Suspicious Kerberos Service Ticket Request
The following analytic detects suspicious Kerberos Service Ticket (TGS) requests where the requesting account name matches the service name, potentially indicating an exploitation attempt of CVE-2021-42278 and CVE-2021-42287. This detection leverages Event ID 4769 from Domain Controller and Kerberos events. Such activity is significant as it may represent an adversary attempting to escalate privileges by impersonating a domain controller. If confirmed malicious, this could allow an attacker to take control of the domain controller, leading to complete domain compromise and unauthorized access to sensitive information.
Show query
`wineventlog_security` EventCode=4769 | eval isSuspicious = if(lower(ServiceName) = lower(mvindex(split(TargetUserName,"@"),0)),1,0) | where isSuspicious = 1 | rename Computer as dest | rename TargetUserName as user | table _time, dest, src_ip, user, ServiceName, Error_Code, isSuspicious | `suspicious_kerberos_service_ticket_request_filter`
Suspicious Linux Discovery Commands
The following analytic detects the execution of suspicious bash commands commonly used in scripts like AutoSUID, LinEnum, and LinPeas for system discovery on a Linux host. It leverages Endpoint Detection and Response (EDR) data, specifically looking for a high number of distinct commands executed within a short time frame. This activity is significant as it often precedes privilege escalation or other malicious actions. If confirmed malicious, an attacker could gain detailed system information, identify vulnerabilities, and potentially escalate privileges, posing a severe threat to the environment.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.action) as action values(Processes.original_file_name) as original_file_name values(Processes.parent_process) as parent_process values(Processes.parent_process_exec) as parent_process_exec values(Processes.parent_process_guid) as parent_process_guid values(Processes.parent_process_id) as parent_process_id values(Processes.parent_process_name) as parent_process_name values(Processes.parent_process_path) as parent_process_path values(Processes.process) as process values(Processes.process_exec) as process_exec values(Processes.process_guid) as process_guid values(Processes.process_hash) as process_hash values(Processes.process_id) as process_id values(Processes.process_integrity_level) as process_integrity_level values(Processes.process_path) as process_path values(Processes.user_id) as user_id values(Processes.vendor_product) as vendor_product dc(Processes.process) as distinct_commands dc(Processes.process_name) as distinct_process_names FROM datamodel=Endpoint.Processes WHERE [ | inputlookup linux_tool_discovery_process | rename process as Processes.process | table Processes.process] by _time span=5m Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | where distinct_commands > 40 AND distinct_process_names > 3 | `suspicious_linux_discovery_commands_filter`
Suspicious MSBuild Rename
The following analytic detects the execution of renamed instances of msbuild.exe. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and original file names within the Endpoint data model. This activity is significant because msbuild.exe is a legitimate tool often abused by attackers to execute malicious code while evading detection. If confirmed malicious, this behavior could allow an attacker to execute arbitrary code, potentially leading to system compromise, data exfiltration, or further lateral movement within the network.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE Processes.process_name!=msbuild.exe
AND
Processes.original_file_name=MSBuild.exe
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `suspicious_msbuild_rename_filter`Suspicious Process DNS Query Known Abuse Web Services
The following analytic detects a suspicious process making DNS queries to known, abused text-paste web services, VoIP, instant messaging, and digital distribution platforms. It leverages Sysmon EventID 22 logs to identify queries from processes like cmd.exe, powershell.exe, and others. This activity is significant as it may indicate an attempt to download malicious files, a common initial access technique. If confirmed malicious, this could lead to unauthorized code execution, data exfiltration, or further compromise of the target host.
Show query
`sysmon` EventCode=22 QueryName IN ("*pastebin*", "*discord*", "*api.telegram*","*t.me*") process_name IN ("cmd.exe", "*powershell*", "pwsh.exe", "wscript.exe","cscript.exe") OR Image IN ("*\\users\\public\\*", "*\\programdata\\*", "*\\temp\\*", "*\\Windows\\Tasks\\*", "*\\appdata\\*", "*\\perflogs\\*") | stats count min(_time) as firstTime max(_time) as lastTime by answer answer_count dvc process_exec process_guid process_name query query_count reply_code_id signature signature_id src user_id vendor_product QueryName QueryResults QueryStatus | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `suspicious_process_dns_query_known_abuse_web_services_filter`Suspicious Process Executed From Container File
The following analytic identifies a suspicious process executed from within common container/archive file types such as ZIP, ISO, IMG, and others. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as it is a common technique used by adversaries to execute scripts or evade defenses. If confirmed malicious, this behavior could allow attackers to execute arbitrary code, escalate privileges, or persist within the environment, posing a significant security risk.
Show query
| tstats `security_content_summariesonly` count values(Processes.process_name) as process_name min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process IN ("*.ZIP\\*","*.ISO\\*","*.IMG\\*","*.CAB\\*","*.TAR\\*","*.GZ\\*","*.RAR\\*","*.7Z\\*") AND Processes.action="allowed" by Processes.action Processes.dest Processes.original_file_name Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path Processes.process Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product | `drop_dm_object_name(Processes)` | regex process="(?i).*(ZIP|ISO|IMG|CAB|TAR|GZ|RAR|7Z)\\\\.+\.(BAT|BIN|CAB|CMD|COM|CPL|EX_|EXE|GADGET|INF1|INS|INX||HTM|HTML|ISU|JAR|JOB|JS|JSE|LNK|MSC|MSI|MSP|MST|PAF|PIF|PS1|REG|RGS|SCR|SCT|SHB|SHS|U3P|VB|VBE|VBS|VBSCRIPT|WS|WSF|WSH)\"?$" | rex field=process "(?i).+\\\\(?<file_name>[^\\\]+\.(ZIP|ISO|IMG|CAB|TAR|GZ|RAR|7Z))\\\\((.+\\\\)+)?(?<process_name>.+\.(BAT|BIN|CAB|CMD|COM|CPL|EX_|EXE|GADGET|INF1|INS|INX||HTM|HTML|ISU|JAR|JOB|JS|JSE|LNK|MSC|MSI|MSP|MST|PAF|PIF|PS1|REG|RGS|SCR|SCT|SHB|SHS|U3P|VB|VBE|VBS|VBSCRIPT|WS|WSF|WSH))\"?$"| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `suspicious_process_executed_from_container_file_filter`Suspicious Process With Discord DNS Query
The following analytic identifies a process making a DNS query to Discord, excluding legitimate Discord application paths. It leverages Sysmon logs with Event ID 22 to detect DNS queries containing "discord" in the QueryName field. This activity is significant because Discord can be abused by adversaries to host and download malicious files, as seen in the WhisperGate campaign. If confirmed malicious, this could indicate malware attempting to download additional payloads from Discord, potentially leading to further code execution and compromise of the affected system.
Show query
`sysmon` EventCode=22 QueryName IN ("*discord*") Image != "*\\AppData\\Local\\Discord\\*" AND Image != "*\\Program Files*" AND Image != "discord.exe" | stats count min(_time) as firstTime max(_time) as lastTime by answer answer_count dvc process_exec process_guid process_name query query_count reply_code_id signature signature_id src user_id vendor_product QueryName QueryResults QueryStatus | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `suspicious_process_with_discord_dns_query_filter`Suspicious Reg exe Process
The following analytic identifies instances of reg.exe being launched from a command prompt (cmd.exe) that was not initiated by the user, as indicated by a parent process other than explorer.exe. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and parent process names. This activity is significant because reg.exe is often used in registry manipulation, which can be indicative of malicious behavior such as persistence mechanisms or system configuration changes. If confirmed malicious, this could allow an attacker to modify critical system settings, potentially leading to privilege escalation or persistent access.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE Processes.parent_process_name != explorer.exe Processes.process_name =cmd.exe
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name("Processes")`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| search [
| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes
WHERE Processes.parent_process_name=cmd.exe Processes.process_name= reg.exe
BY Processes.parent_process_id Processes.dest Processes.process_name
| `drop_dm_object_name("Processes")`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| rename parent_process_id as process_id
| dedup process_id
| table process_id dest]
| `suspicious_reg_exe_process_filter`Suspicious SQLite3 LSQuarantine Behavior
The following analytic identifies the use of SQLite3 querying the MacOS preferences to determine the original URL from which a package was downloaded. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions involving LSQuarantine. This activity is significant as it is commonly associated with MacOS adware and other malicious software. If confirmed malicious, this behavior could indicate an attempt to track or manipulate downloaded packages, potentially leading to further system compromise or persistent adware infections.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE Processes.process_name=sqlite3 Processes.process=*LSQuarantine*
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `suspicious_sqlite3_lsquarantine_behavior_filter`Suspicious Scheduled Task from Public Directory
The following analytic identifies the creation of scheduled tasks that execute binaries or scripts from public directories, such as users\public, \programdata\, or \windows\temp, using schtasks.exe with the /create command. It leverages Sysmon Event ID 1 data to detect this behavior. This activity is significant because it often indicates an attempt to maintain persistence or execute malicious scripts, which are common tactics in malware deployment. If confirmed as malicious, this could lead to data compromise, unauthorized access, and potential lateral movement within the network.
Show query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe (Processes.process=*\\users\\public\\* OR Processes.process=*\\programdata\\* OR Processes.process=*windows\\temp*) Processes.process=*/create* by Processes.action Processes.dest Processes.original_file_name Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path Processes.process Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `suspicious_scheduled_task_from_public_directory_filter`
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