Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential lateral movement or compromised account use where a single user identity authenticates to multiple distinct cloud or administrative resources within a short time window (15 minutes). The rule uses a threshold of six or more unique applications or resources to identify anomalous patterns typical of reconnaissance or mass resource access often associated with stolen credentials. Administrative, service, and automation-related accounts are excluded to minimize noise.
Detects activity from known Storm-3168 (JADEPUFFER) campaign IP addresses across Azure control-plane, sign-in, and App Service logs. The rule monitors for malicious indicators in Azure Activity logs, Azure Sign-in logs, and Service Principal sign-ins, as well as specific sensitive URI paths (e.g., shells, admin login paths) within App Service HTTP logs.
Detects activity from known Storm-3168 (JADEPUFFER) campaign IP addresses across Azure control-plane, sign-in, and App Service logs. The rule monitors for malicious indicators in Azure Activity logs, Azure Sign-in logs, and Service Principal sign-ins, as well as specific sensitive URI paths (e.g., shells, admin login paths) within App Service HTTP logs.
Detects autonomous behavior where AI-driven processes attempt multiple network connections (SMB, SSH, HTTP, RDP, WinRM) to diverse targets following failed access attempts. The rule correlates initial failure activity with subsequent credential-related events and new lateral movement traffic from the same agent process within a short window, suggesting adaptive adversary pivoting.
Detects patterns associated with the TeamFiltration backdoor module, specifically unauthorized OneDrive/SharePoint file modifications occurring shortly after an authentication from a previously unseen device/IP. The rule flags file changes (modifications, deletions, or renames) involving potential executable or script extensions, or those performed by the OneDrive SyncEngine app from a new source.
This rule detects successful authentication events for remote access applications (VPN, RDP, Azure AD App Proxy) where the source IP address or ASN has not been observed in the user's login history within the preceding 14 days. This behavior is indicative of potential account takeover using compromised credentials sourced from infostealers or other credential-harvesting activities.
Detects network exploitation attempts targeting Fortinet FortiOS and FortiProxy vulnerabilities (CVE-2024-55591, CVE-2025-24472) involving authentication bypass via HTTP header manipulation (Forwarded, X-Forwarded-For) and unauthorized access to the /jsconsole endpoint.
Detects network exploitation attempts targeting Fortinet FortiOS and FortiProxy vulnerabilities (CVE-2024-55591, CVE-2025-24472) involving authentication bypass via HTTP header manipulation (Forwarded, X-Forwarded-For) and unauthorized access to the /jsconsole endpoint.
Detects activity from known Storm-3168 (JADEPUFFER) campaign IP addresses across Azure control-plane, sign-in, and App Service logs. The rule monitors for malicious indicators in Azure Activity logs, Azure Sign-in logs, and Service Principal sign-ins, as well as specific sensitive URI paths (e.g., shells, admin login paths) within App Service HTTP logs.
This rule detects potential brute force or account compromise attempts by identifying user accounts that have successfully authenticated or initiated authentication events from two or more distinct IP addresses within the observed time window. It monitors Windows Event IDs 4624 (Successful Logon), 4648 (Logon attempted using explicit credentials), and 4776 (The domain controller attempted to validate the credentials for an account).
Detects successful Entra ID authentication events where the user login originated from an anonymized or malicious IP address, or exhibited unfamiliar features, despite successfully completing multi-factor authentication (MFA). This pattern is consistent with adversary-in-the-middle (AiTM) phishing attacks, where a proxy service is used to intercept and bypass MFA controls.
This rule detects when a user registers or adds a new device in Entra ID within a short timeframe (two hours) of experiencing a risky sign-in or a password reset. It specifically flags registrations involving potentially unmanaged, non-compliant, or unusually trusted devices, which may indicate an attempt to establish persistent access or bypass Conditional Access policies.
This rule correlates events across the end-to-end kill chain of an enterprise intrusion, specifically tracking the progression from initial endpoint-based infostealer activity (credential access), through anomalous or non-interactive sign-in activity, into privilege escalation or mailbox delegation within the cloud environment, and finally to mass data exfiltration or mail access. It detects accounts involved in at least three distinct stages of this progression within a 72-hour window.
This rule detects the installation or execution of common Remote Monitoring and Management (RMM) tools (e.g., AnyDesk, ScreenConnect, Atera, Splashtop, TeamViewer) on Windows endpoints within a 4-hour window of associated cloud identity risk activity (such as risky sign-ins, MFA changes, or privilege grants). It filters out legitimate activity initiated via standard software management pipelines (e.g., SCCM, Intune) to identify potential unauthorized use of remote access software by adversaries following account compromise.
Detects coordinated activity characteristic of NotPetya-like lateral movement. It identifies a local account authenticating across multiple hosts (credential reuse), followed by the creation of a transient Windows service (typically for remote command execution) and the invocation of rundll32.exe to execute a DLL export by ordinal on the same device.
Detects successful authentication events for accounts that have been dormant for at least 90 days, correlated with suspicious activity markers such as recent failed sign-in attempts, access from an unfamiliar geographic location or ASN, or a complete absence of historical sign-in activity.
Detects modifications, creations, or deletions of critical CI/CD pipeline configuration files (GitHub Actions, GitLab CI, Jenkins, Azure Pipelines) across cloud service logs. The rule correlates these actions with the account's historical IP baseline to identify potentially unauthorized changes originating from anomalous locations.
Detects activity from known Storm-3168 (JADEPUFFER) campaign IP addresses across Azure control-plane, sign-in, and App Service logs. The rule monitors for malicious indicators in Azure Activity logs, Azure Sign-in logs, and Service Principal sign-ins, as well as specific sensitive URI paths (e.g., shells, admin login paths) within App Service HTTP logs.
Detects the modification of critical Entra ID authentication method policies, such as the registration or configuration of external MFA/OIDC providers, by a user account shortly after an anomalous or high-risk login event. This behavior is indicative of an attacker attempting to establish persistent backdoor access via rogue MFA provider registration, consistent with techniques used to subvert cloud authentication policies.
Detects autonomous behavior where AI-driven processes attempt multiple network connections (SMB, SSH, HTTP, RDP, WinRM) to diverse targets following failed access attempts. The rule correlates initial failure activity with subsequent credential-related events and new lateral movement traffic from the same agent process within a short window, suggesting adaptive adversary pivoting.
Detects autonomous behavior where AI-driven processes attempt multiple network connections (SMB, SSH, HTTP, RDP, WinRM) to diverse targets following failed access attempts. The rule correlates initial failure activity with subsequent credential-related events and new lateral movement traffic from the same agent process within a short window, suggesting adaptive adversary pivoting.
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