Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
125 detections
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Detects when the explorer.exe process makes a network connection over SMB to a remote host and subsequently creates an executable file. This behavior is indicative of CVE-2025-50154, where a specially crafted LNK file can cause explorer.exe to silently download a binary from a remote share without user interaction.
The following analytic detects the creation or connection of anonymous pipes for inter-process communication (IPC) within a Windows environment. Anonymous pipes are commonly used by legitimate system processes, services, and applications to transfer data between related processes. However, adversaries frequently abuse anonymous pipes to facilitate stealthy process injection, command-and-control (C2) communication, credential theft, or privilege escalation. This detection monitors for unusual anonymous pipe activity, particularly involving non-system processes, unsigned executables, or unexpected parent-child process relationships. While legitimate use cases exist—such as Windows services, software installers, or security tools—unusual or high-frequency anonymous pipe activity should be investigated for potential malware, persistence mechanisms, or lateral movement techniques.
The analytic detects potentially suspicious modifications to Windows Audit Policy auditing options registry values. It focuses on changes to specific auditing option values ("CrashOnAuditFail", "FullPrivilegeAuditing", "AuditBaseObjects", "AuditBaseDirectories") within the "HKLM\System\CurrentControlSet\Control\Lsa\" registry key. Such modifications could indicate a threat actor attempting to tamper with audit policy configurations, potentially disabling SACLs (System Access Control Lists) to bypass defenses and facilitate further malicious activities like machine compromise or lateral movement.
KQL Query
KQL Query from file: Endpoint SMB exposed on Public Internet
KQL Query from file: NTLMv2 Hash Leak via COM Detection
KQL Query from file: KQLWiz PDF NTLM Leak Detector
KQL Query
The analytic detects outbound SMB (Server Message Block) connections from internal hosts to external servers. It identifies this activity by monitoring network traffic for SMB requests directed towards the Internet, which are unusual for standard operations. This detection is significant for a SOC as it can indicate an attacker's attempt to retrieve credential hashes through compromised servers, a key step in lateral movement and privilege escalation. If confirmed malicious, this activity could lead to unauthorized access to sensitive data and potential full system compromise.
Query for processes that accessed more than 10 IP addresses over port 445 (SMB) - possibly scanning for network shares.
To read more about Network Share Discovery, see: https://attack.mitre.org/wiki/Technique/T1135.
Tags: #SMB, #NetworkScanning, #UniqueProcessId.
To read more about Network Share Discovery, see: https://attack.mitre.org/wiki/Technique/T1135.
Tags: #SMB, #NetworkScanning, #UniqueProcessId.
Detects repeated failed (outgoing) attempts to mount a hidden share
This query looks for a large number of network-based authentications using local credentials coming from a single source IP address. High counts of logons involving a large number of distinct machines may identify an attacker beachhead within an enterprise.
Detect Attempt PrintNightmare (CVE-2021-1675) Remote code execution in Windows Spooler Service
This analytic detects suspicious modifications to Unix shell configuration files, such as `.bashrc` or `.profile`, which may indicate an attempt to alter system behavior or gain unauthorized access. Unauthorized changes to these files can be used to execute malicious commands, escalate privileges, or hide malicious activities. By monitoring for unusual or unauthorized modifications to shell configuration files, this analytic helps identify potential security threats, allowing security teams to respond quickly and mitigate risks.
The following analytic detects attempts to stop a service on Linux systems. It leverages data from Linux Auditd. This activity is significant as adversaries often stop or terminate security or critical services to disable defenses or disrupt operations, as seen in malware like Industroyer2. If confirmed malicious, this could lead to the disabling of security mechanisms, allowing attackers to persist, escalate privileges, or deploy destructive payloads, severely impacting system integrity and availability.
The following analytic detects the suspicious auditd service stop. This behavior is critical for a SOC to monitor because it may indicate attempts to gain unauthorized access or maintain control over a system. Such actions could be signs of malicious activity. If confirmed, this could lead to serious consequences, including a compromised system, unauthorized access to sensitive data, or even a wider breach affecting the entire network. Detecting and responding to these signs early is essential to prevent potential security incidents.
The analytic detects cloud API calls executed by user roles that have not previously run these commands. It leverages the Change data model in Splunk to identify commands executed by users with the user_type of AssumedRole and a status of success. This activity is significant because new commands from different user roles can indicate potential malicious activity or unauthorized actions. If confirmed malicious, this behavior could lead to unauthorized access, data breaches, or other damaging outcomes by exploiting new or unmonitored commands within the cloud environment.
The analytic detects the creation of cloud compute instances using previously unseen image IDs. It leverages cloud infrastructure logs to identify new image IDs that have not been observed before. This activity is significant because it may indicate unauthorized or suspicious activity, such as the deployment of malicious payloads or unauthorized access to sensitive information. If confirmed malicious, this could lead to data breaches, unauthorized access, or further compromise of the cloud environment. Immediate investigation is required to determine the legitimacy of the instance creation and to mitigate potential threats.
This analytic aggregates and summarizes alerts from Microsoft Defender for Endpoint. It extracts details such as source, file name, severity, process command line, IP address, registry key, signature, description, and unique ID. The detection is not intended to identify new activity from raw data but rather to leverage existing Microsoft Defender for Endpoint alerts for correlation and risk-based alerting. It filters out alerts with a 'clean' verdict and dynamically maps MITRE techniques and assigns risk scores based on the alert's severity.
The following analytic identifies when a new device is enrolled on an Okta account. It uses OktaIm2 logs ingested via the Splunk Add-on for Okta Identity Cloud to detect the creation of new device enrollments. This activity is significant as it may indicate a legitimate user settinging up a new device or an adversary adding a device to maintain unauthorized access. If confirmed malicious, this could lead to potential account takeover, unauthorized access, and persistent control over the compromised Okta account. Monitoring this behavior is crucial for detecting and mitigating unauthorized access attempts.
This correlation rule identifies when a user exceeds a predefined risk threshold based on multiple suspicious Okta activities within a 24-hour period. It aggregates risk events from "Suspicious Okta Activity," "Okta Account Takeover," and "Okta MFA Exhaustion" analytic stories. The detection is significant as it highlights potentially compromised user accounts exhibiting multiple tactics, techniques, and procedures (TTPs). If confirmed malicious, this activity could indicate a serious security breach, allowing attackers to gain unauthorized access, escalate privileges, or persist within the environment.
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