Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
18,116 detections
Filters
Last updated
All Time
Detection languages
6,549
6,199
1,473
1,002
661
Contributors
3,555
2,652
2,153
2,087
1,515
Categories
7,567
3,899
1,465
1,391
1,330
Platforms
13,722
1,392
1,318
824
738
Products / Services
3,828
3,129
2,448
912
908
MITRE Techniques
18,116
15,636
12,583
8,393
6,223
CVEs
19
18
17
16
14
IDS Classtypes
305
51
24
23
22
IDS Protocols
308
136
13
10
10
Detects file events involving NCrypt.exe, which may indicate process execution or file modification related to cryptographic functions or potential masquerading.
Detects the deletion of the Exchange PowerShell cmdlet History logs which may indicate an attempt to destroy forensic evidence
Detects payload staging activity associated with threat actor UAC-0099, correlating the creation or modification of executable/DLL files in disguised LocalAppData directories with decoy images or library configuration files within a one-hour window.
Detects PowerShell processes invoked with obfuscated command lines that enumerate Microsoft.PowerShell.Utility
exported commands and invoke cmdlets indirectly by array index. This technique is used to evade
detections that look for explicit strings such as Invoke-RestMethod or Invoke-Expression.
exported commands and invoke cmdlets indirectly by array index. This technique is used to evade
detections that look for explicit strings such as Invoke-RestMethod or Invoke-Expression.
The following analytic identifies a popular 3rd party software process being executed where it's process name does not match it's original file name attribute.
Processes that have been renamed and executed may be an indicator that an adversary is attempting to evade defenses or execute malicious code.
Processes that have been renamed and executed may be an indicator that an adversary is attempting to evade defenses or execute malicious code.
The following analytic detects the execution of programs initiated by forfiles.exe. This command is typically used to run commands on multiple files, often within batch scripts. The detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process creation events where forfiles.exe is the parent process. This activity is significant because forfiles.exe can be exploited to bypass command line execution protections, making it a potential vector for malicious activity. If confirmed malicious, this could allow attackers to execute arbitrary commands, potentially leading to unauthorized access or further system compromise.
The following analytic detects programs initiated by pcalua.exe, the Microsoft Windows Program Compatibility Assistant. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and parent process information. While pcalua.exe can start legitimate programs, it is significant because attackers may use it to bypass command line execution protections. If confirmed malicious, this activity could allow attackers to execute arbitrary commands, potentially leading to unauthorized actions, privilege escalation, or persistence within the environment.
The following analytic detects the execution of hh.exe (HTML Help) using InfoTech Storage Handlers to load Windows script code from a Compiled HTML Help (CHM) file. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant because it can be used to execute malicious scripts embedded within CHM files, potentially leading to code execution. If confirmed malicious, this technique could allow an attacker to execute arbitrary code, escalate privileges, or persist within the environment.
The following analytic identifies the abuse of Regsvr32.exe to proxy execution of malicious code, specifically detecting the loading of "scrobj.dll" by Regsvr32.exe. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process creation events and command-line executions. This activity is significant because Regsvr32.exe is a trusted, signed Microsoft binary, often used in "Squiblydoo" attacks to bypass application control mechanisms. If confirmed malicious, this technique could allow an attacker to execute arbitrary code, potentially leading to system compromise and persistent access.
The following analytic detects the behavior of decoding base64-encoded data and passing it to a Linux shell. Additionally, it mitigates the potential damage and protects the organization's systems and data.The detection is made by searching for specific commands in the Splunk query, namely "base64 -d" and "base64 --decode", within the Endpoint.Processes data model. The analytic also includes a filter for Linux shells. The detection is important because it indicates the presence of malicious activity since Base64 encoding is commonly used to obfuscate malicious commands or payloads, and decoding it can be a step in running those commands. It suggests that an attacker is attempting to run malicious commands on a Linux system to gain unauthorized access, for data exfiltration, or perform other malicious actions.
The following analytic identifies the use of the 'kmod' process to list kernel modules on a Linux system. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. While listing kernel modules is not inherently malicious, it can be a precursor to loading unauthorized modules using 'insmod'. If confirmed malicious, this activity could allow an attacker to load kernel modules, potentially leading to privilege escalation, persistence, or other malicious actions within the system.
The following analytic detects the use of the EncodedCommand parameter in PowerShell processes.
It leverages Endpoint Detection and Response (EDR) data to identify variations of the EncodedCommand parameter, including shortened forms and different command switch types.
This activity can be significant because adversaries often use encoded commands to obfuscate malicious scripts, making detection harder.
If confirmed malicious, this behavior could allow attackers to execute hidden code, potentially leading to unauthorized access, privilege escalation, or persistent threats within the environment.
Review parallel events to determine legitimacy and tune based on known administrative scripts.
It leverages Endpoint Detection and Response (EDR) data to identify variations of the EncodedCommand parameter, including shortened forms and different command switch types.
This activity can be significant because adversaries often use encoded commands to obfuscate malicious scripts, making detection harder.
If confirmed malicious, this behavior could allow attackers to execute hidden code, potentially leading to unauthorized access, privilege escalation, or persistent threats within the environment.
Review parallel events to determine legitimacy and tune based on known administrative scripts.
The following analytic detects the use of msiexec.exe with an HTTP or
HTTPS URL in the command line, indicating a remote file download attempt. This detection
leverages data from Endpoint Detection and Response (EDR) agents, focusing on process
execution logs that include command-line details. This activity is significant as
it may indicate an attempt to download and execute potentially malicious software
from a remote server. If confirmed malicious, this could lead to unauthorized code
execution, system compromise, or further malware deployment within the network.
HTTPS URL in the command line, indicating a remote file download attempt. This detection
leverages data from Endpoint Detection and Response (EDR) agents, focusing on process
execution logs that include command-line details. This activity is significant as
it may indicate an attempt to download and execute potentially malicious software
from a remote server. If confirmed malicious, this could lead to unauthorized code
execution, system compromise, or further malware deployment within the network.
The following analytic identifies a suspicious `explorer.exe` process with the `/root` command-line parameter. This detection leverages Endpoint Detection and Response (EDR) telemetry, focusing on process and command-line data. The presence of `/root` in `explorer.exe` is significant as it may indicate parent process spoofing, a technique used by malware to evade detection. If confirmed malicious, this activity could allow an attacker to operate undetected, potentially leading to unauthorized access, privilege escalation, or persistent threats within the environment.
The following analytic identifies the creation of a .crmlog file within the %windows%\Registration directory, typically with a format of <RANDOM_GUID>.<RANDOM_GUID>.crmlog. This detection leverages the Endpoint.Filesystem datamodel to monitor file creation events in the specified directory. This activity is significant as it is associated with the Snake malware, which uses this file for its operations. If confirmed malicious, this could indicate the presence of Snake malware, leading to potential data exfiltration, system compromise, and further malicious activities. Immediate investigation is required to mitigate the threat.
The following analytic detects the use of the decompile parameter with the HTML Help application (HH.exe). This behavior is identified through Endpoint Detection and Response (EDR) telemetry, focusing on command-line executions involving the decompile parameter. This activity is significant because it is an uncommon command and has been associated with APT41 campaigns, where it was used to unpack HTML help files for further malicious actions. If confirmed malicious, this technique could allow attackers to execute arbitrary commands, potentially leading to further compromise and persistence within the environment.
Detects obfuscated shell command execution on VMware ESXi as hunted by CrowdStrike, where attackers hide esxcli commands (e.g. syslog config reset for log evasion, vm process list for recon) behind decode-and-execute wrappers such as printf hex/octal escapes, awk BEGIN blocks (chr/ord/xor/zero-width-unicode/morse/binary decoders), python -c chr() reconstruction, sed/od character-reversal ciphers, and $TERM/$SHELL substring reassembly, frequently invoking /usr/lib/vmware/busybox/bin/busybox or staging output in hidden /vmfs/volumes//.sys files before piping the reconstructed command into sh.
This is a living-off-the-land technique used to evade detection and hinder forensic reconstruction of attacker activity on ESXi hosts, and has been observed enabling syslog exfil-log evasion and VM/hypervisor reconnaissance.
This is a living-off-the-land technique used to evade detection and hinder forensic reconstruction of attacker activity on ESXi hosts, and has been observed enabling syslog exfil-log evasion and VM/hypervisor reconnaissance.
Detects a Chrome/Edge WebDriver process launched with headless and
automation-hiding command-line flags (--headless combined with --disable-infobars
or excludeSwitches enable-automation/test-type). Astaroth's spambot component uses
this exact flag combination to drive a hidden browser instance against an active
WhatsApp Web session, sending spam to every Brazil-based contact without ever
displaying a window to the victim.
automation-hiding command-line flags (--headless combined with --disable-infobars
or excludeSwitches enable-automation/test-type). Astaroth's spambot component uses
this exact flag combination to drive a hidden browser instance against an active
WhatsApp Web session, sending spam to every Brazil-based contact without ever
displaying a window to the victim.
This rule monitors Entra ID Sign-in logs for authentication events flagged by risk detections related to anonymizing infrastructure, such as VPNs, TOR exit nodes, or proxies. It identifies successful logins and aggregate sign-in volume from these IP addresses, flagging successful logins as critical due to the potential for valid account abuse through multi-hop proxy chains.
This rule monitors Entra ID Sign-in logs for authentication events flagged by risk detections related to anonymizing infrastructure, such as VPNs, TOR exit nodes, or proxies. It identifies successful logins and aggregate sign-in volume from these IP addresses, flagging successful logins as critical due to the potential for valid account abuse through multi-hop proxy chains.
Detects outbound network traffic matching XMRig Monero cryptocurrency miner stratum login behavior originating from an internal host.
Page 11 of 863