Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects a multi-stage attack pattern associated with Akira ransomware, including AD enumeration using PowerShell, data staging with WinRAR, S3 exfiltration via s5cmd, AnyDesk service installation, registry manipulation for persistence via Safe Mode, and boot configuration changes to facilitate EDR bypass. It also incorporates detection for specific IOCs like attacker jump host RDP connections and malicious file hashes.
This rule monitors for high or medium-risk user events and sign-in activities within Azure Active Directory. It correlates data from both the AADUserRiskEvents and SigninLogs tables to identify potentially compromised user accounts.
Detects non-interactive sign-ins, such as those using refresh or session tokens, originating from an IP address, ASN, device, or country that does not match the user's recent interactive sign-in history. The absence of an MFA challenge for these new contexts is characteristic of session token replay attacks, often associated with AiTM phishing campaigns.
Detects successful device code authentication flows from users who have not utilized this authentication method within the past 14 days. This rule monitors Entra ID (Azure AD) sign-in logs and non-interactive logs, enriching results with Intune device compliance data and authentication protocol details to assist in identifying anomalous access patterns that may indicate credential abuse or device-code phishing.
Detects the creation of a Windows Scheduled Task (Event ID 4698) that uses the 'InteractiveToken' LogonType, where the user specified to execute the task is different from the user who registered the task. This behavior is indicative of potential session hijacking or lateral movement techniques, such as those used by tools like 'atexec' or to facilitate PRT (Primary Refresh Token) theft.
This rule aggregates sign-in log activity for a specific user to identify the volume and distribution of authentication attempts across different IP addresses, applications, and client types within a specified time range. It is primarily used for identifying anomalies in access patterns that might indicate credential abuse or unauthorized access.
This rule detects a multi-stage attack pattern associated with Akira ransomware, including AD enumeration using PowerShell, data staging with WinRAR, S3 exfiltration via s5cmd, AnyDesk service installation, registry manipulation for persistence via Safe Mode, and boot configuration changes to facilitate EDR bypass. It also incorporates detection for specific IOCs like attacker jump host RDP connections and malicious file hashes.
Detects the enabling of the WDigest UseLogonCredential registry value, which forces the storage of plaintext credentials in memory by the LSASS process, followed by a privileged interactive or remote interactive logon on the same host within 72 hours. This sequence suggests an attacker is positioning the system to harvest credentials.
This rule monitors for high-risk modifications to Zscaler security policies such as disabling SSL inspection or DLP engines, or deleting/modifying firewall and URL filtering rules. It also flags administrative logins from locations previously unseen for that user, which may indicate account compromise or unauthorized access.
Detects successful device code authentication flows from users who have not utilized this authentication method within the past 14 days. This rule monitors Entra ID (Azure AD) sign-in logs and non-interactive logs, enriching results with Intune device compliance data and authentication protocol details to assist in identifying anomalous access patterns that may indicate credential abuse or device-code phishing.
This rule detects a multi-stage attack pattern associated with Akira ransomware, including AD enumeration using PowerShell, data staging with WinRAR, S3 exfiltration via s5cmd, AnyDesk service installation, registry manipulation for persistence via Safe Mode, and boot configuration changes to facilitate EDR bypass. It also incorporates detection for specific IOCs like attacker jump host RDP connections and malicious file hashes.
Aggregates identity, endpoint, cloud application, and messaging telemetry to build a consolidated profile of the devices, clients, applications, and user agents associated with a specific user account.
The query combines Microsoft Entra sign-in data, endpoint logon activity, cloud application events, and email telemetry to provide a high-level overview of a user's activity footprint across the environment.
This query is useful for incident response, account compromise investigations, insider threat investigations, and validating whether a user is accessing services from expected devices and client applications.
The query combines Microsoft Entra sign-in data, endpoint logon activity, cloud application events, and email telemetry to provide a high-level overview of a user's activity footprint across the environment.
This query is useful for incident response, account compromise investigations, insider threat investigations, and validating whether a user is accessing services from expected devices and client applications.
Detects Microsoft Entra ID Protection risk telemetry for sign-ins with unfamiliar properties. Microsoft evaluates characteristics such as ASN, browser, device, and location against the user's historical behavior to identify anomalous sign-ins that may warrant investigation.
This rule detects successful SSH logins that follow a burst of at least 10 failed SSH authentication attempts from the same remote IP address to the same device within a 10-minute window, followed by a successful login within 15 minutes. This pattern is indicative of a successful credential brute-force attack, frequently associated with botnet propagation efforts.
Detects sign-ins from known UNC6671 residential-proxy IPs, ranked by rarity (first-seen for the user) and correlated with a following sensitive account action (MFA registration, mailbox rule change, admin role change).
Detects successful sign-ins using the device code authentication flow that are infrequent for a specific user and location. This flow is often targeted by attackers attempting to bypass MFA or perform device phishing, as it requires the user to manually authorize the device on a separate platform.
This rule detects scenarios where a new user account is created (Event ID 4720) and is subsequently logged into (Event ID 4624) within a 30-minute window. This behavior can indicate an adversary creating a backdoor or service account for persistence or lateral movement, followed by immediate usage of that account.
This rule monitors for high-risk modifications to Zscaler security policies such as disabling SSL inspection or DLP engines, or deleting/modifying firewall and URL filtering rules. It also flags administrative logins from locations previously unseen for that user, which may indicate account compromise or unauthorized access.
Detects sign-in events using 'deviceCode' authentication or single-factor authentication via mobile/desktop clients where the device identifier has not been seen in the previous 30 days. This pattern can indicate an adversary using a new device to access an account, potentially utilizing stolen sessions or bypassing MFA.
Detects two distinct offensive patterns: Impacket PsExec usage, identified by a Type-3 network logon followed within 2 minutes by an ADMIN$ service installation matching typical PsExec naming patterns; and DCSync replication requests originating from non-Domain Controller accounts.
This rule detects scenarios where a new user account is created (Event ID 4720) and is subsequently logged into (Event ID 4624) within a 30-minute window. This behavior can indicate an adversary creating a backdoor or service account for persistence or lateral movement, followed by immediate usage of that account.
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