Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Show usb mounted devices and drive letters
This rule detects outbound network connections to IP addresses that exhibit low prevalence within the monitored environment. Specifically, it flags connections to IPs that have a rolling maximum prevalence of 1 to 3 occurrences over a 10-day period. This behavior can be indicative of command and control (C2) communication, data exfiltration, or other suspicious activities where adversaries might use newly registered or rarely seen infrastructure.
Detects potentially suspicious processes being spawned by a web server process which could be the result of a successfully placed web shell or exploitation. This rule specifically looks for common web server processes (Caddy, Apache HTTPD, Nginx, PHP, Tomcat, IIS, Exchange UMWorkerProcess) or Java processes identified as Tomcat, spawning anomaly children processes like command-line interpreters (cmd.exe, powershell.exe, bash.exe), network utilities (net.exe, netsh.exe), or other system utilities often used in post-exploitation.
Detects potential exploitation of CVE-2021-26084, a Confluence RCE using OGNL injection. The rule looks for specific POST requests to Confluence endpoints, either '/pages/createpage-entervariables.action' with a 'SpaceKey=x' parameter or '/doenterpagevariables.action' with a 'u0027' string in the POST body's 'queryString' parameter. It specifically targets requests from 'anonymous' users that result in a 200 HTTP status code.
The analytic detects the use of `reg.exe` to export Windows Registry hives, specifically `sam`, `system`, or `security`, which may contain sensitive credentials. This activity indicates potential offline credential access attacks, often executed from untrusted processes or scripts. If confirmed malicious, attackers could gain access to credential data, enabling further compromise and lateral movement within the network.
This analytic detects exploitation activity of CVE-2023-27532 using Cisco Secure Firewall Intrusion Events. It leverages Cisco Secure Firewall Threat Defense IntrusionEvent logs to identify cases where Snort signature 61514 (Veeam Backup and Replication credential dump attempt) is followed within a 5-minute window by 64795 (Veeam Backup and Replication xp_cmdshell invocation attempt), which detects the use of `xp_cmdshell`, a common post-exploitation technique. If confirmed malicious, this behavior is highly indicative of a successful exploitation of CVE-2023-27532, followed by remote command execution or credential dumping.
Detects potentially suspicious processes being spawned by a web server process which could be the result of a successfully placed web shell or exploitation
Detects potential exploitation of a chained vulnerability attack targeting Ivanti EPMM 12.5.0.0. CVE-2025-4427 allows unauthenticated access to protected API endpoints via an authentication bypass, which can then be leveraged to trigger CVE-2025-4428 — a remote code execution vulnerability through template injection. This sequence enables unauthenticated remote code execution, significantly increasing the impact of exploitation.
This analytic detects Lumma Stealer download attempts using Cisco Secure Firewall Intrusion Events. It leverages Cisco Secure Firewall Threat Defense IntrusionEvent logs to identify cases where Snort signatures with specific IDs have been triggered. If confirmed malicious, this behavior could indicate an active infection of Lumma Stealer.
The following analytic identifies potential DLL side-loading instances involving unsigned DLLs mimicking Microsoft signatures. It detects this activity by analyzing Sysmon logs for Event Code 7, where both the `Image` and `ImageLoaded` paths do not match system directories like `system32`, `syswow64`, and `programfiles`. This behavior is significant as adversaries often exploit DLL side-loading to execute malicious code via legitimate processes. If confirmed malicious, this activity could allow attackers to execute arbitrary code, potentially leading to privilege escalation, persistence, and unauthorized access to sensitive information.
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.
This analytic employs the 3-sigma approach to detect an unusual volume of failed authentication attempts from a single source. A password spray attack is a type of brute force attack where an attacker tries a few common passwords across many different accounts to avoid detection and account lockouts. By utilizing the Authentication Data Model, this detection is effective for all CIM-mapped authentication events, providing comprehensive coverage and enhancing security against these attacks.
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.
This analytic identifies the creation or modification of email inbox rules within an Office 365 environment. It specifically looks for `New-InboxRule` and `Set-InboxRule` operations in the O365 management activity logs where the rule parameters indicate actions such as mail forwarding (`ForwardTo`, `ForwardAsAttachmentTo`, `RedirectTo`), or mail manipulation like deletion (`SoftDeleteMessage`, `DeleteMessage`) or moving to specific folders (`MoveToFolder`, `CopyToFolder`). While legitimate users create inbox rules, adversaries often leverage these techniques to exfiltrate emails, maintain persistence, or hide their activities by deleting or moving security alerts.
The analytic identifies a statistically significant increase in access to Active Directory objects, which may indicate attacker enumeration. It leverages Windows Security Event Code 4662 to monitor and analyze access patterns, comparing them against historical averages to detect anomalies. This activity is significant for a SOC because abnormal access to AD objects can be an early indicator of reconnaissance efforts by an attacker. If confirmed malicious, this behavior could lead to unauthorized access, privilege escalation, or further compromise of the Active Directory environment.
The analytic detects the registration of a new Multi-Factor Authentication (MFA) method for an Azure AD account. It leverages Azure AD AuditLogs to identify when a user registers new security information. This activity is significant because adversaries who gain unauthorized access to an account may add their own MFA method to maintain persistence. If confirmed malicious, this could allow attackers to bypass existing security controls, maintain long-term access, and potentially escalate their privileges within the environment.
The following analytic detects the execution of the `Invoke-AzureHound` command-line argument, commonly used by the AzureHound tool. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant because AzureHound is often used for reconnaissance in Azure environments, potentially exposing sensitive information. If confirmed malicious, this activity could allow an attacker to map out Azure Active Directory structures, aiding in further attacks and privilege escalation.
The following analytic identifies suspicious command-line parameters associated with the use of Impacket's smbexec.py for lateral movement. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line patterns indicative of Impacket tool usage. This activity is significant as both Red Teams and adversaries use Impacket for remote code execution and lateral movement. If confirmed malicious, this activity could allow attackers to execute commands on remote endpoints, potentially leading to unauthorized access, data exfiltration, or further compromise of the network.
The following analytic identifies excessive AccessDenied events within an hour timeframe for IAM users in AWS. It leverages AWS CloudTrail logs to detect multiple failed access attempts from the same source IP and user identity. This activity is significant as it may indicate that an access key has been compromised and is being misused for unauthorized discovery actions. If confirmed malicious, this could allow attackers to gather information about the AWS environment, potentially leading to further exploitation or privilege escalation.
The following analytic detects suspicious database file and directory discovery activities, which may signal an attacker attempt to locate and assess critical database assets on a compromised system. This behavior is often a precursor to data theft, unauthorized access, or privilege escalation, as attackers seek to identify valuable information stored in databases. By monitoring for unusual or unauthorized attempts to locate database files and directories, this analytic aids in early detection of potential reconnaissance or data breach efforts, enabling security teams to respond swiftly and mitigate the risk of further compromise.
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