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 high-privilege OAuth consent grants to applications shortly followed by suspicious mailbox modifications, such as creating new inbox or transport rules. This behavior is indicative of a post-compromise activity where an adversary uses an illicitly granted OAuth application to maintain persistence or exfiltrate data from an Exchange Online environment.
This rule detects potentially malicious activity involving Service Principals in Microsoft Entra ID. It identifies two scenarios: 1) Impossible travel, where a service principal authenticates from two distinct geographic locations within a 60-minute window, and 2) Administrative modifications to a service principal's credentials or authentication methods (e.g., adding secrets, certificates, or MFA methods), which may indicate persistence or credential abuse.
Detects potential SaaS supply-chain attacks where a third-party application or connector triggers an OAuth permission scope escalation or publishes a new version, followed by the associated service account initiating outbound network connections to rare or newly-registered domains within a 24-hour window.
Detects the granting of high-privilege permissions (e.g., mail.read, files.readwrite) to a newly registered OAuth application (less than 24 hours old), followed by high-volume API activity from that same application within one hour. This behavior is indicative of an illicit OAuth consent grant attack, where an adversary lures a user into granting permissions to a malicious application to maintain persistent access to cloud resources or perform data exfiltration.
Detects a suspicious sequence of events: an anomalous login (new device, new location, or high-risk sign-in) followed by the assumption of a highly privileged role (via AssumeRole, PIM, or role elevation) and subsequent sensitive administrative actions (e.g., creating access keys, modifying IAM policies, or disabling security auditing). This pattern is indicative of cloud identity compromise and privilege escalation, commonly seen in attacks involving groups like Scattered Spider.
Detects when a user account assigned to high-privileged roles (Global Administrator or Authentication Policy Administrator) performs sensitive operations such as application registration, service principal creation, or modifications to authentication policies within a short timeframe (4 hours) of a successful sign-in. This activity is often associated with the initial setup phases of MFA bypass or persistence techniques in Entra ID.
Detects successful Entra ID sign-in events that utilize the OAuth 2.0 device authorization grant (device code) flow. This authentication mechanism is frequently abused by attackers to perform device code phishing (e.g., ARToken attacks), where victims are tricked into entering a malicious user code on a legitimate Microsoft login portal to facilitate token theft.
Detects high-risk administrative actions in Entra ID, such as role assignments, user creation, or password resets, occurring shortly after a user authenticates using the device code flow. This pattern is indicative of a post-compromise takeover where an adversary utilizes a stolen or coerced device code session to escalate privileges.
Detects anomalous, high-volume activity in cloud-based services such as SharePoint, OneDrive, and Exchange, specifically tracking file access, downloads, and mailbox exports. This behavior may indicate bulk data collection, unauthorized exfiltration, or malicious data staging by a compromised account.
This rule detects network activity and cloud API events indicative of an adversary utilizing the VAPI.ai platform to orchestrate automated voice-phishing (vishing) campaigns. It correlates outbound network connections to VAPI.ai endpoints with specific webhook callback patterns used to track call status for victim records.
Detects Microsoft Graph API requests targeting user information endpoints (/v1.0/users or /v1.0/me) using specific search filters associated with payroll or human resources and identified by the Axios HTTP client User-Agent string. This pattern is consistent with reconnaissance activities.
Detects specific, targeted search operations within M365 environments for keywords related to payroll, HR, and banking information. This behavior is indicative of post-compromise reconnaissance activity, often following AiTM (Adversary-in-the-Middle) session hijacking where an attacker attempts to locate financial documents and payroll correspondence.
Detects potentially malicious OAuth device code sign-ins by identifying sign-in events that exhibit anomalous characteristics, such as atypical geographic locations, rare client-application combinations, unmanaged/noncompliant device status, or elevated risk signals associated with the account. This detection helps identify account compromise or malicious OAuth consent activity often associated with 'EvilTokens' or device-code phishing attacks.
Detects potential abuse of stolen OAuth session tokens, where refresh tokens are used to authenticate after a user has performed a password reset. This rule identifies accounts that continue to sign in from previously unseen devices or IP addresses within 24 hours post-password reset, a technique consistent with session persistence mechanisms used by adversary tools and platforms like EvilTokens.
Detects a single Salesforce user or connected-app session performing an anomalous volume of SOQL queries against sensitive objects including Case, Account, Contact, and Opportunity. This behavior is indicative of mass data enumeration and potential exfiltration, as observed in historical incidents where attackers targeted CRM platforms to extract embedded secrets and sensitive record data.
Detects OAuth application consent events in Entra ID where the application display name mimics legitimate services like Salesforce or Data Loader while requesting high-risk API scopes (full_access, offline_access, api). This behavior is characteristic of phishing-driven OAuth grant campaigns, such as those observed by the ShinyHunters group.
Monitors SaaS application integration service accounts (e.g., Salesforce connected apps) by establishing baselines for API call volume and accessed object types. The rule alerts on anomalous spikes in usage or deviations in the scope of accessed data objects, which could indicate the abuse of compromised OAuth tokens following a vendor supply-chain compromise.
Detects anomalous anti-forensic behavior where a Salesforce Bulk API query job is deleted shortly after its creation or completion. This sequence is often associated with efforts to obscure data exfiltration activities by removing the metadata trail of bulk data exports.
Detects anomalous Salesforce API export patterns where a user or connected application maintains a daily record export volume below typical burst thresholds, yet accumulates a high total volume over a rolling 7-day period. This pattern mimics 'low-and-slow' data exfiltration techniques used by actors like ShinyHunters to evade standard volume-based DLP alerts.
Detects anomalous large-scale data export operations in Google BigQuery (via jobs.insert or jobs.query) performed by identities (service accounts, API keys) not previously observed in the environment. This activity is indicative of credential abuse where stolen third-party analytics or monitoring service tokens are utilized for illicit data exfiltration, a behavior consistent with tactics employed by threat actors such as ShinyHunters.
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