Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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.
The following analytic identifies instances of the WinDBG process spawning AutoIt3. This behavior is detected by monitoring endpoint telemetry for processes where 'windbg.exe' is the parent process and 'autoit3.exe' or similar is the child process. This activity is significant because AutoIt3 is frequently used by threat actors for scripting malicious automation, potentially indicating an ongoing attack. If confirmed malicious, this could allow attackers to automate tasks, execute arbitrary code, and further compromise the system, leading to data exfiltration or additional malware deployment.
The analytic detects unusually long command lines, which may indicate malicious activity. Attackers often use obfuscated or complex command lines to evade detection and execute malicious payloads. If confirmed malicious, this activity could lead to data theft, ransomware deployment, or further system compromise. Analysts should investigate the source and content of the command line, inspect relevant artifacts, and review concurrent processes to identify potential threats.
The analytic identifies unusually long command lines executed on hosts, which may indicate malicious activity. It leverages the Machine Learning Toolkit (MLTK) to detect command lines with lengths that deviate from the norm for a given user. This is significant for a SOC as unusually long command lines can be a sign of obfuscation or complex malicious scripts. If confirmed malicious, this activity could allow attackers to execute sophisticated commands, potentially leading to unauthorized access, data exfiltration, or further compromise of the system.
The following analytic detects the spawning of cmd or PowerShell processes by the wermgr.exe process. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process telemetry, including parent-child process relationships and command-line executions. This behavior is significant as it is commonly associated with code injection techniques used by malware like TrickBot to execute shellcode or malicious DLL modules. If confirmed malicious, this activity could allow attackers to execute arbitrary code, escalate privileges, or maintain persistence within the environment, posing a severe threat to system security.
The analytic detects potentially malicious command lines using a pretrained machine learning text classifier. It identifies unusual keyword combinations in command lines, such as "streamreader," "webclient," "mutex," "function," and "computehash," which are often associated with adversarial PowerShell code execution for C2 communication. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on command lines longer than 200 characters. This activity is significant as it can indicate an attempt to execute malicious scripts, potentially leading to unauthorized code execution, data exfiltration, or further system compromise.
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.
This rule detects the execution of known Proof-of-Concept (PoC) executables for the ZeroLogon vulnerability (CVE-2020-1472). It specifically looks for `cmd.exe` spawning executables named `cool.exe` or `zero.exe` with command-line arguments indicating administrative context and execution flags. Additionally, it identifies subsequent actions such as `taskkill` commands or `powershell` execution, which are common post-exploitation activities after successful ZeroLogon exploitation.
Detects the execution of known attacker tools, specifically those associated with the IronSharpPack toolset. This rule identifies process launches where common command and scripting interpreters (cmd.exe, python, ipy.exe, powershell.exe, pwsh.exe, wsl.exe) are used to execute scripts or binaries with names indicative of IronSharpPack components. The presence of these tools in an unauthorized environment suggests malicious activity, often related to offensive security operations, post-exploitation, or privilege escalation.
Detects the execution of known attacker tools, including but not limited to those in the IronSharpPack toolset. These tools are commonly used for offensive security operations and may indicate malicious activity if observed in unauthorized environments.
Detects when a shell program such as the Windows command prompt or PowerShell is launched with system privileges. This rule helps identify potential suspicious processes that have escalated privileges.
Detects when a shell program such as the Windows command prompt or PowerShell is launched with system privileges from an uncommon parent location. This behavior can indicate privilege escalation or defense evasion by an attacker.
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