Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a pattern associated with ShinyHunters/UNC6040, where a user authorizes a new or rarely-used OAuth connected application shortly after performing a help-desk initiated password reset or MFA re-enrollment, originating from a different geographic location.
Detects successful authentication to administrative identity provider consoles that are flagged by identity-provider risk engines as anomalous (e.g., unfamiliar location, new device, or suspicious sign-in properties). This pattern monitors for potential account takeovers or compromised insider activity targeting critical administrative infrastructure, as observed in attacks utilizing recruited or purchased credentials.
Detects successful authentication to administrative identity provider consoles that are flagged by identity-provider risk engines as anomalous (e.g., unfamiliar location, new device, or suspicious sign-in properties). This pattern monitors for potential account takeovers or compromised insider activity targeting critical administrative infrastructure, as observed in attacks utilizing recruited or purchased credentials.
Detects a successful login attempt by the user account 'p2pwn' targeting port 37777. Port 37777 is commonly associated with DVR/NVR surveillance equipment and is frequently targeted by brute-force attacks and botnets attempting to gain unauthorized access to embedded devices.
Detects a suspicious sequence of events indicating account takeover: a password reset, followed by an MFA factor re-enrollment, and concluding with a successful login from a geographically impossible location compared to recent history. This pattern often signifies a help-desk-assisted account compromise or token theft.
Detects sign-in activity using the OAuth 2.0 device code flow, followed by subsequent authentication attempts from the same account originating from anomalous, previously unseen geographic locations or using unfamiliar applications. This pattern is indicative of a device code phishing attack where an adversary lures a user into authorizing a malicious device or application and subsequently hijacks the resulting session to access resources from a different location.
Detects a suspicious sequence of behavior where an Azure service principal authenticates and immediately performs broad reconnaissance (enumeration) across multiple subscriptions and resource types. This pattern is often indicative of an adversary using a compromised service principal credential to map out an environment.
Detects a suspicious sequence of behavior where an Azure service principal authenticates and immediately performs broad reconnaissance (enumeration) across multiple subscriptions and resource types. This pattern is often indicative of an adversary using a compromised service principal credential to map out an environment.
Detects a suspicious sequence of behavior where an Azure service principal authenticates and immediately performs broad reconnaissance (enumeration) across multiple subscriptions and resource types. This pattern is often indicative of an adversary using a compromised service principal credential to map out an environment.
Detects anomalous service principal activity characterized by multiple, rapidly issued, and overlapping OAuth tokens within a short time window. This pattern is associated with automated/agentic token orchestration (e.g., JADEPUFFER/Storm-3168 campaign) rather than standard manual operator activity, specifically when leveraging the python-requests user agent.
Detects a sequence of events characteristic of exploitation against RouterOS (CVE-2026-67276/CVE-2026-86060), involving a failed SSH login attempt with the username '-2', followed by the creation of a new user account within the same SSH session, and a successful login with that newly created account.
Detects suspicious AI inference API activity indicative of credential compromise or misuse. The rule identifies three main signals: rapid authentication failures (credential stuffing), anomalous geolocation/ASN usage for successful requests, and successful API calls occurring after a key rotation event.
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 Microsoft Entra ID sign-in events where a user authenticates from a known residential proxy ASN, matching the user's historical geography but using a new, unrecognized device fingerprint. This behavior is indicative of session token replay attacks, where an adversary uses stolen session cookies to bypass standard authentication.
Detects a successful login attempt by the user account 'p2pwn' targeting port 37777. Port 37777 is commonly associated with DVR/NVR surveillance equipment and is frequently targeted by brute-force attacks and botnets attempting to gain unauthorized access to embedded devices.
Detects instances where an administrative user performs a password or MFA method reset on a target account, followed within 24 hours by a sign-in event from that same target account flagged with a high or medium risk level. This sequence is characteristic of Adversary-in-the-Middle (AiTM) attacks, where an attacker utilizes stolen session tokens and subsequently coerces helpdesk or administrative intervention to reset MFA requirements to maintain unauthorized access.
This rule detects potential account compromise by identifying scenarios where a user's security information (MFA methods) is modified, deleted, or updated, followed shortly after (within 24 hours) by a successful sign-in using a less secure authentication method (SMS, Voice, OATH, or Mobile App notification) instead of a stronger method like FIDO2 or Passkey.
Detects the reuse of session identifiers (SessionId, DeviceId, or RefreshTokenJti) across different device fingerprints (e.g., changes in User-Agent, OS, or Browser) within a short timeframe. This behavior is indicative of session hijacking or adversary-in-the-middle (AiTM) attacks, where stolen session tokens or cookies are replayed by an attacker from a different endpoint than the original user.
Detects instances where a user account successfully registers or joins a device to Entra ID (Azure AD) immediately after performing a sign-in operation that was flagged with a medium or high-risk level. This pattern may indicate an adversary is attempting to enroll a malicious device to bypass conditional access policies or establish persistence in the environment using compromised credentials.
Detects Kerberos TGT requests (AS-REQ, Event ID 4768) where authentication is performed using a certificate (PKINIT) instead of a password. This pattern is commonly associated with Pass-the-Certificate attacks, often utilized by tools like Certipy following certificate enrollment or relaying to obtain a TGT as part of a credential access chain.
Detects Kerberos TGT requests (AS-REQ, Event ID 4768) where authentication is performed using a certificate (PKINIT) instead of a password. This pattern is commonly associated with Pass-the-Certificate attacks, often utilized by tools like Certipy following certificate enrollment or relaying to obtain a TGT as part of a credential access chain.
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