Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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SharpSuccessor is a .NET-based post-exploitation tool designed to weaponize the BadSuccessor attack. This rule detects the execution of SharpSuccessor.exe or command-line arguments containing 'SharpSuccessor' in process launch events or specific Windows Security Auditing events (EventCode 4673) indicating a privileged service call. This activity is indicative of privilege escalation attempts in Active Directory environments, specifically leveraging 'CreateChild' permissions over Organizational Units (OUs) to escalate privileges to Domain Administrator.
This rule identifies process creations or file creations where the associated file has been tagged as an 'exploit' by VirusTotal. It leverages enrichment from a VirusTotal integration to flag potentially malicious activity related to exploit execution.
This rule detects buffer overflow attempts in Unix system log files by looking for specific keywords. These keywords include phrases indicating an attempt to execute code on the stack, known exploit strings like '0bin0sh1', a long string of 'A's (which can be indicative of buffer filling), and messages related to 'stack smashing detected'. The rule aims to identify malicious activity where an attacker tries to overflow a buffer to gain control of program execution, potentially leading to privilege escalation.
Detects the execution of SharpSuccessor, a tool used to exploit the BadSuccessor attack for privilege escalation in WinServer 2025 Active Directory environments.
Successful usage of this tool can let the attackers gain the domain admin privileges by exploiting the BadSuccessor vulnerability.
Successful usage of this tool can let the attackers gain the domain admin privileges by exploiting the BadSuccessor vulnerability.
SharpSuccessor is a .NET-based post-exploitation tool designed to weaponize the BadSuccessor attack discovered by Yuval Gordon (@YuG0rd) from Akamai. It allows a low-privileged user with 'CreateChild' permissions over any Organizational Unit (OU) in an Active Directory domain to escalate privileges to Domain Administrator. This detection rule identifies execution patterns or behavioral indicators linked to SharpSuccessor activity, which may signal privilege escalation attempts in Active Directory environments.
Detects buffer overflow attempts in Unix system log files
This analytic identifies high-severity intrusion events based on the classification assigned to Snort rules within Cisco Secure Firewall logs. It leverages Cisco Secure Firewall Threat Defense logs and focuses on events classified as: A Network Trojan was Detected, Successful Administrator Privilege Gain, Successful User Privilege Gain, Attempt to Login By a Default Username and Password, Known malware command and control traffic, Known malicious file or file based exploit, Known client side exploit attempt, Large Scale Information Leak. These classifications typically represent significant threats such as remote code execution, credential theft, lateral movement, or malware communication. Detection of these classifications should be prioritized for immediate investigation.
The following analytic identifies the first-time execution of child processes spawned by Zoom (zoom.exe or zoom.us). It leverages Endpoint Detection and Response (EDR) data, specifically monitoring process creation events and comparing them against previously seen child processes. This activity is significant because the execution of unfamiliar child processes by Zoom could indicate malicious exploitation or misuse of the application. If confirmed malicious, this could lead to unauthorized code execution, data exfiltration, or further compromise of the endpoint.
The analytic detects the execution of `pkexec` without any command-line arguments. This behavior leverages data from Endpoint Detection and Response (EDR) agents, focusing on process telemetry. The significance lies in the fact that this pattern is associated with the exploitation of CVE-2021-4034 (PwnKit), a critical vulnerability in Polkit's pkexec component. If confirmed malicious, this activity could allow an attacker to gain full root privileges on the affected Linux system, leading to complete system compromise and potential unauthorized access to sensitive information.
This analytic identifies the use of the GCPloit exploitation framework within Google Cloud Platform (GCP). It detects specific GCP Pub/Sub messages with a function timeout of 539 seconds, which is indicative of GCPloit activity. This detection is significant as GCPloit can be used to escalate privileges and facilitate lateral movement from compromised high-privilege accounts. If confirmed malicious, this activity could allow attackers to gain unauthorized access, escalate their privileges, and move laterally within the GCP environment, potentially compromising sensitive data and critical resources.
The analytic detects the loading of `msi.dll` by a binary not located in `system32`, `syswow64`, `winsxs`, or `windows` directories. This is identified using Sysmon EventCode 7, which logs DLL loads, and filters out legitimate system paths. This activity is significant as it may indicate exploitation of CVE-2021-41379 or DLL side-loading attacks, both of which can lead to unauthorized system modifications. If confirmed malicious, this could allow an attacker to execute arbitrary code, escalate privileges, or persist within the environment.
The analytic detects the loading of known vulnerable Windows drivers, which may indicate potential persistence or privilege escalation attempts. It leverages Windows System service install EventCode 7045 to identify driver loading events and cross-references them with a list of vulnerable drivers. This activity is significant as attackers often exploit vulnerable drivers to gain elevated privileges or maintain persistence on a system. If confirmed malicious, this could allow attackers to execute arbitrary code with high privileges, leading to further system compromise and potential data exfiltration. This detection is a Windows Event Log adaptation of the Sysmon driver loaded detection written by Michael Haag.
This analytic detects previously unseen processes within the Kubernetes environment on master or worker nodes. It leverages process metrics collected via an OTEL collector and hostmetrics receiver, with data pulled from Splunk Observability Cloud. The detection compares processes observed in the last hour against those seen in the previous 30 days. Identifying new processes is crucial as they may indicate unauthorized activity or attempts to compromise the node. If confirmed malicious, these processes could lead to data exfiltration, privilege escalation, denial-of-service attacks, or the introduction of malware, posing significant risks to the Kubernetes cluster.
The 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.
The following analytic identifies processes running from newly seen paths within a Kubernetes environment. It leverages process metrics collected via an OTEL collector and hostmetrics receiver, and data is pulled from Splunk Observability Cloud using the Splunk Infrastructure Monitoring Add-on. This detection compares processes observed in the last hour with those seen over the previous 30 days. This activity is significant as it may indicate unauthorized changes, compromised nodes, or the introduction of malicious software. If confirmed malicious, it could lead to unauthorized process execution, control over critical resources, data exfiltration, privilege escalation, or malware introduction within the Kubernetes cluster.
The analytic detects attempts to exploit the Baron Samedit vulnerability (CVE-2021-3156) by identifying the use of the "sudoedit -s \" command. This detection leverages logs from Linux systems, specifically searching for instances of the sudoedit command with the "-s" flag followed by a double quote. This activity is significant because it indicates an attempt to exploit a known vulnerability that allows attackers to gain root privileges. If confirmed malicious, this could lead to complete system compromise, unauthorized access to sensitive data, and potential data breaches.
This analytic identifies a heap-based buffer overflow in sudoedit by detecting Linux logs containing both "sudoedit" and "segfault" terms. This detection leverages Splunk to monitor for more than five occurrences of these terms on a single host within a specified timeframe. This activity is significant because exploiting this vulnerability (CVE-2021-3156) can allow attackers to gain root privileges, leading to potential system compromise, unauthorized access, and data breaches. If confirmed malicious, this could result in elevated privileges and full control over the affected system, posing a severe security risk.
The following analytic identifies child processes spawned by spoolsv.exe, the Print Spooler service in Windows, which typically runs with SYSTEM privileges. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and parent process relationships. Monitoring this activity is crucial as it can indicate exploitation attempts, such as those associated with CVE-2018-8440, which can lead to privilege escalation. If confirmed malicious, attackers could gain SYSTEM-level access, allowing them to execute arbitrary code, escalate privileges, and potentially compromise the entire system.
The analytic detects the execution of the "sudoedit -s *" command, which is associated with the Baron Samedit CVE-2021-3156 heap-based buffer overflow vulnerability. This detection leverages the `osquery_process` data source to identify instances where this specific command is run. This activity is significant because it indicates an attempt to exploit a known vulnerability that allows privilege escalation. If confirmed malicious, an attacker could gain full control of the system, execute arbitrary code, or access sensitive data, leading to potential data breaches and system disruptions.
This analytic detects the creation of new .sys files on disk. It leverages the Endpoint.Filesystem data model to identify and log instances where .sys files are written to the filesystem. This activity is significant because .sys files are often used as kernel mode drivers, and their unauthorized creation can indicate malicious activity such as rootkit installation. If confirmed malicious, this could allow an attacker to gain kernel-level access, leading to full system compromise, persistent control, and the ability to bypass security mechanisms.
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.
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