Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential help-desk impersonation or social engineering activity involving account credential or MFA method resets, followed shortly by a sign-in from an unknown device or geography. The rule excludes activity tied to established ticketing systems or standard automated password expiration processes.
This rule detects inbound email messages where the SPF check passes for a specific domain (osc-cdn.com) or uses specific infrastructure (Migadu), but the DMARC check fails due to misalignment between the envelope domain and the From header. This pattern is indicative of email spoofing or domain impersonation attempts where the attacker abuses misconfigured SPF/DMARC policies (p=none) to facilitate spearphishing.
Detects an authentication pattern characteristic of credential compromise, consisting of a burst of failed authentication attempts against an account within a short window, followed immediately by a successful sign-in from an anomalous or new device/location. This pattern is indicative of brute-force or credential spraying followed by successful validation and potential lateral movement.
Detects an authentication pattern characteristic of credential compromise, consisting of a burst of failed authentication attempts against an account within a short window, followed immediately by a successful sign-in from an anomalous or new device/location. This pattern is indicative of brute-force or credential spraying followed by successful validation and potential lateral movement.
Detects a multi-stage attack chain originating with a healthcare-themed phishing email (e.g., billing or patient coordination lures) that leads to a link click, followed by a subsequent suspicious user sign-in from a non-managed/non-compliant device for the same recipient. This correlates email threat data, URL click telemetry, and sign-in logs to identify potential credential harvesting.
Detects a multi-stage attack chain originating with a healthcare-themed phishing email (e.g., billing or patient coordination lures) that leads to a link click, followed by a subsequent suspicious user sign-in from a non-managed/non-compliant device for the same recipient. This correlates email threat data, URL click telemetry, and sign-in logs to identify potential credential harvesting.
Detects a multi-stage attack chain originating with a healthcare-themed phishing email (e.g., billing or patient coordination lures) that leads to a link click, followed by a subsequent suspicious user sign-in from a non-managed/non-compliant device for the same recipient. This correlates email threat data, URL click telemetry, and sign-in logs to identify potential credential harvesting.
Detects MFA-fatigue style attacks (push-bombing) against Microsoft 365 accounts. The rule identifies a pattern where a user experiences a high frequency of MFA challenges or denials (at least 5 within a 10-minute window) immediately followed by a successful sign-in from a previously unseen IP and device, excluding phishing-resistant authentication methods and break-glass accounts.
Detects MFA-fatigue style attacks (push-bombing) against Microsoft 365 accounts. The rule identifies a pattern where a user experiences a high frequency of MFA challenges or denials (at least 5 within a 10-minute window) immediately followed by a successful sign-in from a previously unseen IP and device, excluding phishing-resistant authentication methods and break-glass accounts.
Detects modifications to Microsoft Entra ID applications or service principals involving the addition or configuration of 'externalauthprovider' redirect URIs or properties. This behavior is indicative of an attacker attempting to establish a malicious federated identity or persistence mechanism by manipulating application configuration to use an adversary-controlled authentication provider.
Detects a suspicious sequence of identity-related operations in Azure AD, characterized by the modification of authentication methods policies followed by rapid application or service principal registration, consent granting, or role assignments by the same actor within a 10-minute window. This behavior often indicates an adversary attempting to establish persistence or escalate privileges via malicious OAuth applications or service principals after weakening security posture.
Detects a suspicious sequence of identity-related operations in Azure AD, characterized by the modification of authentication methods policies followed by rapid application or service principal registration, consent granting, or role assignments by the same actor within a 10-minute window. This behavior often indicates an adversary attempting to establish persistence or escalate privileges via malicious OAuth applications or service principals after weakening security posture.
This rule detects potential data exfiltration by monitoring corporate user activities involving consumer generative AI services (e.g., ChatGPT, Gemini, Claude). It identifies suspicious patterns such as large volume submissions, repeated chunked prompts, and the presence of sensitive content (e.g., PII markers, classification labels) or obfuscated payloads (base64/rot13) that suggest an attempt to bypass DLP or detection controls.
Single-source Sigma proxy for the authentication-persistence stage of the multi-stage device-code-phishing-to-Graph-collection chain (see the companion KQL correlation rule "Passkey Persistence: Device-Code Phishing to MFA Takeover and Graph Collection" for the full, threshold-gated, cross-table detection). Sigma has no join, temporal-windowing, or aggregation support, so this rule fires on the authentication-persistence event alone and does NOT enforce the device-code sign-in precursor or the subsequent Graph-activity burst - both required by the full correlation. Scoped to the two highest-signal operations only (new security-info registration, and any admin-initiated registration on another user's account) to cut noise from routine self-service profile edits.
Detects the multi-stage Microsoft cloud identity compromise chain reported by Microsoft Security Research (September 2026): a victim completes a successful Entra ID device-code sign-in (often induced by passkey-themed device-code phishing), the same identity's authentication/security info is registered or changed (MFA/passkey persistence) within 60 minutes (deduplicated to the earliest such event per sign-in), followed within 120 minutes by a burst of at least 25 successful, delegated-context Microsoft Graph API calls (Scopes claim populated, i.e. user-delegated permissions rather than pure application/client-credential access) spanning at least 3 distinct resource paths, exhibiting reconnaissance (>=5 requests against /users, /groups, /directoryRoles, /roleManagement, /applications, /servicePrincipals, /organization) and/or collection (>=10 requests against /messages, /mailFolders, /attachments, /drive, /drives, /sites, /lists, /search) patterns. Restricting to delegated (Scopes-bearing) Graph calls and requiring resource-path breadth removes the two largest false-positive sources: service-principal/application-only automation jobs (Roles-only tokens) and single-endpoint polling tools. Pure behavioral correlation across SigninLogs, AuditLogs, and MicrosoftGraphActivityLogs - no static IOCs. Flags whether Graph activity originated from an IP different from the original device-code sign-in IP as a strong pivot/session-reuse indicator.
This rule detects anomalous, high-volume activity from a single user account interacting with known public generative AI platforms (e.g., ChatGPT, Copilot, Claude). It uses a threshold-based approach on CloudAppEvents logs to identify potential reconnaissance or bulk information gathering activities which could signify unauthorized use or automated data scraping via AI interfaces.
This rule detects known malicious activity including network connections to a specific C2 IP address (69.48.229.140), downloading files from specific C2 URLs, the presence of known malicious file hashes (SHA256), and communications involving specific actor-associated email addresses.
This rule performs an indicator of compromise (IOC) sweep for activities associated with the TOPHIT / VHX Harvester / @prime0 NPM typosquatting campaign. It detects known malicious C2 network connections (IPs and URLs), file artifacts (hashes) on endpoints, and suspicious email activity involving specific operator email addresses.
This rule performs an indicator of compromise (IOC) sweep for activities associated with the TOPHIT / VHX Harvester / @prime0 NPM typosquatting campaign. It detects known malicious C2 network connections (IPs and URLs), file artifacts (hashes) on endpoints, and suspicious email activity involving specific operator email addresses.
This rule detects potential malicious activity where a single sender local-part (username) is observed sending emails across multiple, disparate, and likely compromised domains (such as cPanel or WordPress sites). This behavior is characteristic of large-scale phishing campaigns where a single attacker controls multiple compromised mail relays.
Detects phishing emails themed around Atlantic Council invitations that contain links attempting to lure users into installing iOS configuration profiles, often associated with malicious backdoors like DarkSword, attributed to the Star Blizzard (G1033) threat group.
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