Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
3,240 detections
Filters
Last updated
All Time
Detection languages
1,690
638
186
183
172
Contributors
781
591
426
265
151
Categories
2,253
2,024
730
384
305
Platforms
2,613
886
443
69
43
Products / Services
938
630
365
186
163
MITRE Techniques
18,113
15,640
12,591
8,389
6,208
3,240
CVEs
20
13
13
12
9
IDS Classtypes
11
7
2
2
1
IDS Protocols
17
3
The analytic identifies potential exploitation of Log4Shell CVE-2021-44228 by correlating multiple MITRE ATT&CK tactics detected in risk events. It leverages Splunk's risk data model to calculate the distinct count of MITRE ATT&CK tactics from Log4Shell-related detections. This activity is significant because it indicates a high probability of exploitation if two or more distinct tactics are observed. If confirmed malicious, this activity could lead to initial payload delivery, callback to a malicious server, and post-exploitation activities, potentially resulting in unauthorized access, lateral movement, and further compromise of the affected systems.
The following analytic identifies an excessive number of distinct processes executing from the Windows\Temp directory. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process paths and counts within a 20-minute window. This behavior is significant as it often indicates the presence of post-exploit frameworks like Koadic and Meterpreter, which use this technique to execute malicious actions. If confirmed malicious, this activity could allow attackers to execute arbitrary code, escalate privileges, and maintain persistence within the environment, posing a severe threat to system integrity and security.
The following analytic identifies instances where four or more distinct detection analytics are associated with malicious command line behavior on a specific host. This detection leverages the Command Line Interface (CLI) data from various sources to identify suspicious activities. This behavior is significant as it often indicates attempts to execute malicious commands, access sensitive data, install backdoors, or perform other nefarious actions. If confirmed malicious, attackers could gain unauthorized control, exfiltrate information, escalate privileges, or launch further attacks within the network, leading to severe compromise.
The analytic detects the execution of cscript.exe or wscript.exe processes initiated by cmd.exe. This activity is significant as it may indicate script-based attacks or administrative actions that could be leveraged for malicious purposes. If confirmed malicious, this behavior could allow attackers to execute scripts, potentially leading to code execution, privilege escalation, or persistence within the environment.
The following analytic identifies the download of potentially malicious file types, such as .scr, .dll, .bat, and .lnk, within a network. It leverages web proxy logs from Zscaler, focusing on blocked actions and analyzing fields like deviceowner, user, urlcategory, url, dest, and filename. This activity is significant as these file types are often used to spread malware, posing a threat to network security. If confirmed malicious, this activity could lead to malware execution, data compromise, or further network infiltration.
This analytic detects file downloads involving executable, archive, or scripting-related file types that are commonly used in malware delivery. These file types include formats like PE executables, shell scripts, autorun files, installers, and known testing samples such as EICAR. This detection leverages Cisco Secure Firewall Threat Defense logs and enriches the results using a filetype lookup to provide context. If confirmed malicious, these downloads could indicate the initial infection vector, malware staging, or scripting abuse.
The following analytic detects attempts to exploit a remote code execution vulnerability in Juniper Networks devices. It identifies requests to /webauth_operation.php?PHPRC=*, which are indicative of uploading and executing malicious PHP files. This detection leverages the Web data model, focusing on specific URL patterns and HTTP status codes. This activity is significant because it signals an attempt to gain unauthorized access and execute arbitrary code on the device. If confirmed malicious, the attacker could gain control over the device, leading to data theft, network compromise, or other severe consequences.
The analytic detects the execution of mshta.exe via registry entries to run malicious scripts. It leverages registry activity logs to identify entries containing "mshta," "javascript," "vbscript," or "WScript.Shell." This behavior is significant as it indicates potential fileless malware, such as Kovter, which uses encoded scripts in the registry to persist and execute without files. If confirmed malicious, this activity could allow attackers to maintain persistence, execute arbitrary code, and evade traditional file-based detection methods, posing a significant threat to system integrity and security.
This analytic identifies suspicious process names using a pre-trained Deep Learning model. It analyzes Endpoint Detection and Response (EDR) telemetry to classify process names as benign or suspicious based on a threshold score. This detection is significant for identifying malware, such as TrickBot, which often uses randomly generated filenames to evade detection. If confirmed malicious, this activity could indicate the presence of malware capable of propagating across the network and executing harmful actions.
The following analytic detects attempts to escalate privileges on a Linux system using Docker. It identifies processes where Docker commands are used to mount the root directory or execute shell commands within a container. This detection leverages Endpoint Detection and Response (EDR) telemetry, focusing on process names, command-line arguments, and parent processes. This activity is significant because it can allow an attacker with Docker privileges to modify critical system files, such as /etc/passwd, to create a superuser. If confirmed malicious, this could lead to full system compromise and persistent unauthorized access.
This analytic detects when the Windows Task Scheduler service (svchost.exe -k netsvcs -p -s Schedule) spawns common command-line interpreters or scripting engines such as powershell.exe, cmd.exe, wscript.exe, or cscript.exe. This activity is significant because attackers frequently abuse the Task Scheduler for execution and persistence, attempting to blend in with legitimate Windows operations. If confirmed malicious, this could allow attackers to execute arbitrary code, maintain persistence, or escalate privileges within the environment.
The analytic identifies shell activity within the Kubernetes privilege scope on a worker node, specifically when shell processes are consuming CPU resources. It leverages process metrics from an OTEL collector hostmetrics receiver, pulled from Splunk Observability Cloud via the Splunk Infrastructure Monitoring Add-on, focusing on process.cpu.utilization and process.memory.utilization. This activity is significant as unauthorized shell processes can indicate a security threat, potentially compromising the node and the entire Kubernetes cluster. If confirmed malicious, attackers could gain full control over the host's resources, leading to data theft, service disruption, privilege escalation, and further attacks within the cluster.
The analytic detects the execution of the Apache Benchmark binary (ab.exe), which is commonly used by MetaSploit payloads. It focuses on process creation events where the original file name is 'ab.exe'. This activity may indicate a MetaSploit attack, potentially leading to unauthorized network connections, system compromise, and data exfiltration. Immediate investigation is required.
The analytic identifies path traversal command-line executions, leveraging data from Endpoint Detection and Response (EDR) agents. It detects patterns in command-line arguments indicative of path traversal techniques, such as multiple instances of "/..", "\..", or "\\..". This activity is significant as it often indicates attempts to evade defenses by executing malicious code, such as through msdt.exe. If confirmed malicious, this behavior could allow attackers to execute arbitrary code, potentially leading to system compromise, data exfiltration, or further lateral movement within the network.
This detection searches for Windows Defender ASR block events. ASR is a feature of Windows Defender Exploit Guard that prevents actions and apps that are typically used by exploit-seeking malware to infect machines. ASR rules are applied to processes and applications. When a process or application attempts to perform an action that is blocked by an ASR rule, an event is generated. This detection searches for ASR block events that are generated when a process or application attempts to perform an action that is blocked by an ASR rule. Typically, these will be enabled in block most after auditing and tuning the ASR rules themselves. Set to TTP once tuned.
The following analytic detects the launch of rarely used applications within the environment, which may indicate the use of potentially malicious software or tools by attackers. It leverages Windows AppLocker event logs, aggregating application launch counts over time and flagging those that significantly deviate from the norm. This behavior is significant as it helps identify unusual application activity that could signal a security threat. If confirmed malicious, this activity could allow attackers to execute unauthorized code, potentially leading to further compromise of the system.
The analytic identifies the use of protocol handlers executed via the command line. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and command-line telemetry. This activity is significant because protocol handlers can be exploited to execute arbitrary commands or launch applications, potentially leading to unauthorized actions. If confirmed malicious, an attacker could use this technique to gain code execution, escalate privileges, or maintain persistence within the environment, posing a significant security risk.
This analytic identifies suspicious command-line activity where `cmd.exe` is used to fetch environment variables via the `set` command, but the parent process is not a typical shell like `cmd.exe`, `explorer.exe`, or `powershell`. This behavior is often observed in malware, such as Qakbot, to gather system information. Detection of this activity could indicate a compromised parent process, potentially leading to further malicious actions like arbitrary command execution, privilege escalation, or persistence.
This analytic detects Microsoft Office applications dropping or creating executables or scripts on a Windows OS. It leverages process creation and file system events from the Endpoint data model to identify Office applications like Word or Excel generating files with extensions such as ".exe", ".dll", or ".ps1". This behavior is significant as it is often associated with spear-phishing attacks where malicious files are dropped to compromise the host. If confirmed malicious, this activity could lead to code execution, privilege escalation, or persistent access, posing a severe threat to the environment.
The following analytic identifies an excessive number of taskhost.exe and taskhostex.exe processes running within a short time frame. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and their counts. This behavior is significant as it is commonly associated with post-exploitation tools like Meterpreter and Koadic, which use multiple instances of these processes for actions such as discovery and lateral movement. If confirmed malicious, this activity could indicate an ongoing attack, allowing attackers to execute code, escalate privileges, or move laterally within the network.
The following analytic detects instances where the PaperCut NG application (pc-app.exe) spawns a Windows shell, such as cmd.exe or PowerShell. This behavior is identified using Endpoint Detection and Response (EDR) telemetry, focusing on process creation events where the parent process is pc-app.exe. This activity is significant as it may indicate an attacker attempting to gain unauthorized access or execute malicious commands on the system. If confirmed malicious, this could lead to unauthorized code execution, privilege escalation, or further compromise of the affected environment.
Page 145 of 155