Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential password spraying activity in Azure Active Directory by identifying a single source IP address that authenticates against multiple distinct user accounts within a short time frame. The rule flags instances where there are numerous authentication attempts across many users, characterized by a low per-user failure count followed by at least one successful authentication, which is indicative of a successful password spray attempt.
Detects potential password spraying activity in Azure Active Directory by identifying a single source IP address that authenticates against multiple distinct user accounts within a short time frame. The rule flags instances where there are numerous authentication attempts across many users, characterized by a low per-user failure count followed by at least one successful authentication, which is indicative of a successful password spray attempt.
Flags anomalous volume of Entra ID sign-ins using the device-code authorization grant, matching the Kali365 phishing-as-a-service technique (sold on Telegram, ~$250/month per FBI PSA) that captures Microsoft 365 OAuth tokens through the legitimate device-code flow.
Detects high-velocity, multi-application sign-in activity within a short timeframe (<= 15 minutes) originating from suspicious Python-based user agents (requests library). This pattern is often indicative of automated script-based reconnaissance or unauthorized access attempts against Microsoft 365 services.
Detects sign-in events in Entra ID where the OAuth 2.0 device authorization grant (device code) flow is utilized. This flow is a common vector for phishing attacks designed to steal tokens by tricking users into authenticating on a secondary device, potentially bypassing MFA.
This rule monitors for indicators of compromise (IOCs) associated with the TrustSink rogue MFA provider, specifically tracking the domain 'trident-sip-filter.ngrok-free.dev' and its associated OIDC discovery path. It aggregates signals from sign-in logs, audit logs, DNS queries, and network proxy traffic to identify attempts to interact with this malicious infrastructure.
Detects a suspicious sequence of events where a user engagement (voice/video call) involving themes of urgency or helpdesk interaction is closely followed by a high-risk administrative action (e.g., password reset, MFA device enrollment, or financial transfer) by the same user, where the communication session context differs from standard activity, indicative of a deepfake-enabled vishing attack.
This rule detects a suspicious monetization pattern where a user account experiences a high-risk sign-in event, followed shortly (within 2 hours) by the creation or modification of inbox rules. This pattern is often indicative of account compromise, where an adversary configures mailbox rules (e.g., forwarding or redirection) to facilitate data exfiltration or financial fraud.
This rule detects a suspicious monetization pattern where a user account experiences a high-risk sign-in event, followed shortly (within 2 hours) by the creation or modification of inbox rules. This pattern is often indicative of account compromise, where an adversary configures mailbox rules (e.g., forwarding or redirection) to facilitate data exfiltration or financial fraud.
Detects multiple MFA push notifications generated within a short timeframe for a single user during a Self-Service Password Reset (SSPR) flow. This behavior is indicative of an attacker attempting to perform MFA fatigue/push harassment to gain unauthorized access via SSPR or to bypass account security controls.
Detects multiple MFA push notifications generated within a short timeframe for a single user during a Self-Service Password Reset (SSPR) flow. This behavior is indicative of an attacker attempting to perform MFA fatigue/push harassment to gain unauthorized access via SSPR or to bypass account security controls.
Detects anomalous, high-volume account enumeration against the Microsoft Self-Service Password Reset (SSPR) endpoint from a single source IP. The rule identifies a pattern of mixed response codes, specifically interleaving '50034' (Account does not exist) with successful or other outcomes, which indicates the use of automated tools to validate the existence of corporate accounts via response differentiation.
Detects anomalous, high-volume account enumeration against the Microsoft Self-Service Password Reset (SSPR) endpoint from a single source IP. The rule identifies a pattern of mixed response codes, specifically interleaving '50034' (Account does not exist) with successful or other outcomes, which indicates the use of automated tools to validate the existence of corporate accounts via response differentiation.
Detects successful authentication attempts in Azure AD or Microsoft 365 logs originating from known proxy/VPN service providers or identified by suspicious Python-requests user agent strings. The rule specifically filters for events where MFA was not satisfied, indicating potentially bypassed or failed security controls from potentially malicious infrastructure.
This rule identifies enterprise resource access from OnePlus or OxygenOS devices that lack proper management or compliance. It calculates an exposure score based on factors including device management status, compliance state, device trust type, and whether the device is newly observed. The rule flags high and medium priority exposure incidents, specifically targeting non-managed or non-compliant BYOD devices, which could represent an increased risk profile for corporate data access.
Detects instances where a Claude session token is reused from a new IP address without the completion of an MFA challenge, indicating a potential session hijacking or session theft attempt.
Detects session hijacking (AiTM) attempts where a failed or interrupted sign-in (ResultType 50199) is followed by a successful login using the same SessionId but with an Axios user-agent, indicating automated replay of a stolen session token rather than legitimate browser usage.
This rule hunts for indicators associated with the TrustSink technique, which involves using rogue External Authentication Methods (EAM) or malicious OIDC providers to bypass authentication or maintain persistence within a cloud environment. It monitors Azure AD sign-in and audit logs, alongside DNS and network events, for references to known malicious domains and URLs used for EAM-based attacks.
This rule hunts for indicators associated with the TrustSink technique, which involves using rogue External Authentication Methods (EAM) or malicious OIDC providers to bypass authentication or maintain persistence within a cloud environment. It monitors Azure AD sign-in and audit logs, alongside DNS and network events, for references to known malicious domains and URLs used for EAM-based attacks.
This rule monitors for indicators of compromise (IOCs) associated with the ShinyHunters threat actor, including specific malicious domains, IP addresses, and artifacts found in command lines or event data. It aggregates telemetry from network events, Entra ID sign-in logs, cloud application activity, email logs, process execution, and general device events to detect interaction with known malicious infrastructure or execution of threat-actor specific artifacts.
This rule detects a password-spraying attack pattern directed at privileged or manager-titled accounts. It monitors for multiple failed sign-in attempts from a single source IP address against a large volume of distinct user accounts identified as managers or senior staff. The detection logic filters for low-frequency attempts per account, which is indicative of a distributed spray attack designed to evade account lockout thresholds while focusing on high-value targets.
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