Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects a multi-stage Business Email Compromise (BEC) attack involving executive impersonation via look-alike domains, followed by the creation of suspicious inbox rules (forwarding/deletion) by the victim, and concurrent external communication (Teams/Zoom meeting invites) from a newly created account. It correlates these activities to identify sophisticated payment fraud campaigns.
Detects the sequential activation of Android Accessibility services followed by Device Administrator activation by the same application within a short timeframe. This behavior is indicative of sophisticated Android malware, such as RatHat, establishing persistence and preventing uninstallation by combining Accessibility-based control with Device Admin-based device management capabilities (e.g., remote wipe or anti-uninstall).
Detects the sequential activation of Android Accessibility services followed by Device Administrator activation by the same application within a short timeframe. This behavior is indicative of sophisticated Android malware, such as RatHat, establishing persistence and preventing uninstallation by combining Accessibility-based control with Device Admin-based device management capabilities (e.g., remote wipe or anti-uninstall).
Detects anomalous, high-frequency, multi-channel probing of AI agent input surfaces. The rule identifies external actors sending instruction-injection style keywords across different communication channels (e.g., email, Teams, calendar) within a short window, which may indicate an attempt to identify and manipulate an organization's autonomous agents. Covers T1595.002
This rule detects potentially malicious search activity in Microsoft SharePoint by monitoring for high-frequency queries that include specific site class patterns ('STS_Site' or 'STS_Web') and a document ID range search pattern ('indexdocid'). This behavior is characteristic of an adversary attempting to enumerate or scrape documents within a SharePoint environment.
Detects UNC6240 PSEMHUB.war web shell/tunnel/trojanized installer artifacts by distinctive content markers (x.jsp, u.jsp, tunnel.jsp/jspx, Ple64.exe)
This rule detects the unauthorized download of complete ML model checkpoint or weight files from a model registry or object storage. It monitors for common model file extensions in download events that are not associated with a legitimate deployment justification or a pre-approved change management window, helping to identify potential intellectual property theft or model exfiltration attempts.
Detects the registration or installation of an MCP (Model Context Protocol) server or agent tool containing suspicious prompt-injection strings (e.g., instructions to ignore safety guardrails or role overrides), immediately followed by the execution of shell commands or unauthorized network connections originating from that tool.
Detects Azure AD / Entra ID sign-in events that utilize the OAuth 2.0 device code authentication flow. This protocol, designed for input-constrained devices, is frequently exploited by adversary-in-the-middle phishing kits (e.g., EvilTokens) to trick users into authorizing a malicious session, effectively bypassing traditional MFA by obtaining an active session token.
Detects the creation or modification of Google Cloud Config Connector (KCC) IAM resources (IAMPolicyMember, IAMPartialPolicy, IAMPolicy) that assign high-privilege roles like 'roles/owner' or 'roles/resourcemanager.organizationAdmin'. This monitors for potential privilege escalation where a low-privilege actor leverages the KCC controller's high-privilege service account to perform unauthorized IAM binding changes on Google Cloud resources.
Detects post-exploitation indicators of CVE-2026-62911, an authentication-bypass-by-capture-replay vulnerability in Microsoft Exchange. The rule identifies anomalous behavior following a potential bypass: either the assignment of the ApplicationImpersonation management role or a single impersonation session accessing an abnormally high number of distinct mailboxes (FolderBind, MessageBind, or SendAs).
This rule monitors Salesforce lead creation events for potential prompt-injection payloads. It identifies submissions containing common AI manipulation instructions, HTML tags, or suspicious outbound URLs, which could be used to hijack internal user sessions or execute malicious content within the Salesforce environment.
This rule detects internal users submitting potentially sensitive data to public generative AI applications (e.g., ChatGPT, Claude, Gemini) where Microsoft Purview DLP or a comparable inspection service has triggered a policy match. It correlates cloud application outbound signals with content inspection logs to identify high-risk exfiltration events while excluding sanctioned enterprise-licensed AI instances.
Detects OAuth application consent events where an application is granted a combination of 'offline_access' (allowing refresh token issuance) and email-read permissions. This pattern is commonly used by adversaries to establish persistent, long-term access to user mailboxes for data exfiltration or Business Email Compromise (BEC) activities, surviving password changes until the consent is explicitly revoked.
Detects instances where an Entra ID (Azure AD) application is registered and subsequently granted consent by the same user within 30 minutes, specifically when the activity occurs outside of typical business hours (7 AM - 7 PM) or from disparate IP addresses. This behavior pattern is indicative of potential malicious OAuth application registration and subsequent token-granting by an attacker to maintain persistent access to an environment.
Detects instances where a user grants OAuth consent or assigns roles to an application that lacks a verified publisher and requests broad permissions across multiple sensitive categories (e.g., Mail, Files, and Directory). This behavior is characteristic of consent-phishing campaigns designed to harvest data from cloud environments.
Detects instances where a user grants consent to an Azure AD application with highly sensitive permissions (such as ReadWrite access to Directory, Roles, or Applications). This pattern is commonly used in OAuth consent phishing attacks to maintain persistence or escalate privileges by authorizing a malicious application to act on behalf of the user or the entire directory.
Detects instances where a user grants an OAuth application consent to high-risk scopes (such as mail reading, file access, or directory reading) without administrator oversight. This behavior is a common indicator of OAuth abuse where an attacker lures a user into granting excessive permissions to a malicious application, providing the attacker persistent access to the user's data.
Detects OAuth application consent grants where the application requests both 'offline_access' (enabling refresh tokens for long-term access) and sensitive mailbox permission scopes (such as Mail.Read, Mail.ReadWrite, Mail.Send, or IMAP.AccessAsUser.All). This combination is indicative of consent phishing attacks designed to establish persistent, silent access to user email accounts, bypassing password resets and multi-factor authentication.
Detects mass-phishing consent campaigns by monitoring non-admin users consenting to multi-tenant or unverified-publisher applications requesting non-basic-profile OAuth scopes. The rule aggregates multiple consent events for the same application over a 1-hour window to identify potentially malicious consent-phishing activity.
Detects mass-phishing consent campaigns by monitoring non-admin users consenting to multi-tenant or unverified-publisher applications requesting non-basic-profile OAuth scopes. The rule aggregates multiple consent events for the same application over a 1-hour window to identify potentially malicious consent-phishing activity.
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