Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects rapid enumeration of Azure AD identity and configuration components by identifying a burst of specific, high-level administrative API calls (Get user flows, Get API connectors, Get identity providers, Get user attributes) within a short window. This pattern is indicative of reconnaissance activities aimed at mapping out the identity provider configuration.
Detects successful Azure AD sign-ins where the user agent identifies as a Python requests library version (2.33.1 or 2.34.2) that has not been observed for that specific user account in the preceding 14 days. This behavior is indicative of anomalous automated or scripted access.
No description available.
Detects instances where a user performs an interactive login followed by a non-interactive login within a 1-hour window, where the source IP address and geographical location of both sessions differ. This behavior is indicative of potential session hijacking or token theft where an attacker is using stolen session artifacts from a different location.
This rule detects potentially unauthorized access to cloud resources or OAuth applications by identifying sign-ins or API calls originating from IP addresses or locations not previously observed for the user in the 30 days prior to a documented Coder registry compromise exposure window.
Detects non-interactive sign-in events involving OIDC or external authentication tokens shortly after a known Coder registry compromise. The rule flags high-risk or at-risk single-factor authentication sessions, which may indicate the replay of stolen tokens harvested during the compromise window.
This rule correlates Microsoft Entra ID (formerly Azure AD) identity risk events with sign-in activity and behavioral analytics for a specific user to facilitate forensic investigation of potential identity compromise. It aggregates risk events, anomalous sign-in attempts (including failures or failed conditional access), and suspicious behavioral telemetry from the same source IP addresses associated with identified user risk.
This rule detects potentially unauthorized access to cloud resources or OAuth applications by identifying sign-ins or API calls originating from IP addresses or locations not previously observed for the user in the 30 days prior to a documented Coder registry compromise exposure window.
Detects non-interactive sign-in events involving OIDC or external authentication tokens shortly after a known Coder registry compromise. The rule flags high-risk or at-risk single-factor authentication sessions, which may indicate the replay of stolen tokens harvested during the compromise window.
This rule correlates Microsoft Entra ID (formerly Azure AD) risk events identified as 'passwordSpray' with subsequent sign-in logs from the same source IP address within a 60-minute window. This helps identify successful or suspicious authentication activity originating from an IP address previously flagged for password spraying attempts against a specific user account.
Detects high-risk account modifications, such as adding MFA methods or OAuth consent grants, occurring shortly after a user sign-in. This pattern is indicative of post-AiTM session theft (e.g., NovaCookies) where an adversary uses a stolen session token to modify account settings for persistence or MFA bypass.
Detects non-interactive sign-ins, such as those using refresh or session tokens, originating from an IP address, ASN, device, or country that does not match the user's recent interactive sign-in history. The absence of an MFA challenge for these new contexts is characteristic of session token replay attacks, often associated with AiTM phishing campaigns.
Detects the execution of common command-line utilities and tools used to enumerate virtual machines, hypervisors, and cloud instance information. Adversaries may perform this reconnaissance to identify virtualization environments, sandbox targets, or cloud infrastructure configurations.
Detects a sequence of events starting with a device code OAuth sign-in, followed within two hours by the creation or modification of inbox rules and high-frequency enumeration of email items (contacts, folders, messages, threads, people) via Microsoft Graph API. This behavior is indicative of post-compromise activity where an adversary uses OAuth device code grants to maintain access and subsequently automates inbox analysis or data harvesting.
Detects a suspicious sequence of interactive sign-ins to Microsoft management and profile-related applications from unmanaged devices occurring within a tight 15-minute window. This behavior is indicative of post-compromise activity, potentially associated with activity clusters such as UNC6671, where an attacker interacts with account settings shortly after compromising a session.
Detects a suspicious sequence of events where a user's password is changed or reset by an administrator (or help-desk role) followed within a short time window by that same user registering a new MFA device, potentially indicating a vishing-based account takeover attack (e.g., PREY-0058/UNC6671).
This rule detects rapid enumeration of Azure AD identity and configuration components by identifying a burst of specific, high-level administrative API calls (Get user flows, Get API connectors, Get identity providers, Get user attributes) within a short window. This pattern is indicative of reconnaissance activities aimed at mapping out the identity provider configuration.
This rule detects user authentication events that deviate significantly from a 14-day historical baseline of known devices, operating systems, browsers, and network locations (ASN). It flags logins where at least two out of four key metadata signals (DeviceId, OS, Browser, ASN) have changed compared to the user's historical pattern, specifically targeting successful authentications that did not trigger a fresh multi-factor authentication (MFA) challenge, potentially indicating token theft or unauthorized session reuse.
Detects successful Azure AD sign-ins where the user agent identifies as a Python requests library version (2.33.1 or 2.34.2) that has not been observed for that specific user account in the preceding 14 days. This behavior is indicative of anomalous automated or scripted access.
Detects instances where a user account performs a device configuration change (such as updating compliance policies) followed by a potentially destructive operation (Wipe, Retire, or Delete) on the same device or entity within a 6-hour window. This behavior often suggests unauthorized administrative activity or a malicious insider attempting to disable security controls before removing access or destroying data.
Detects instances where a user performs an interactive login followed by a non-interactive login within a 1-hour window, where the source IP address and geographical location of both sessions differ. This behavior is indicative of potential session hijacking or token theft where an attacker is using stolen session artifacts from a different location.
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