Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 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.
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.
Detects NTLM network logons (NtLmSsp) for accounts that may have been targets of certificate-based identity abuse (e.g., ESC1). Attackers often leverage this technique to extract NTLM hashes from PKINIT TGT PACs and subsequently utilize Pass-the-Hash for lateral movement within the network.
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.
This rule detects the presence of specific file hashes known to be associated with backdoored software builds, specifically related to recent supply chain compromises affecting South Korean software vendors (e.g., HAProxy builds). It monitors device file events, process initiation, and identity logon events to identify systems that have deployed, executed, or been accessed by these malicious binaries.
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 creation of a Windows Scheduled Task (Event ID 4698) that uses the 'InteractiveToken' LogonType, where the user specified to execute the task is different from the user who registered the task. This behavior is indicative of potential session hijacking or lateral movement techniques, such as those used by tools like 'atexec' or to facilitate PRT (Primary Refresh Token) theft.
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.
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 the registration of a new scheduled task occurring within a network logon session (LogonType 3). This behavior is characteristic of lateral movement techniques where attackers use remote service execution tools (such as Impacket's atexec or PRTremote) to register and execute tasks on a remote host via SMB/RPC. The rule correlates Windows Security Event 4698 (Task creation) with network logon events and validates the action using Task Scheduler operational logs.
This rule detects the presence of specific file hashes known to be associated with backdoored software builds, specifically related to recent supply chain compromises affecting South Korean software vendors (e.g., HAProxy builds). It monitors device file events, process initiation, and identity logon events to identify systems that have deployed, executed, or been accessed by these malicious binaries.
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 identifies potentially compromised Entra ID accounts by correlating multiple suspicious behaviors within a 14-day window. It aggregates four specific indicators: successful authentication following repeated MFA failures, impossible travel (sign-ins from multiple countries within a short timeframe), unusual hour logons (00:00-05:00), and sign-ins flagged with medium/high risk or reported as compromised. The rule triggers when an account exhibits two or more of these distinct anomalous behaviors.
This rule identifies potentially compromised Entra ID accounts by correlating multiple suspicious behaviors within a 14-day window. It aggregates four specific indicators: successful authentication following repeated MFA failures, impossible travel (sign-ins from multiple countries within a short timeframe), unusual hour logons (00:00-05:00), and sign-ins flagged with medium/high risk or reported as compromised. The rule triggers when an account exhibits two or more of these distinct anomalous behaviors.
Detects a pattern of multiple failed authentication attempts (brute force) from an external IP address followed by a successful authentication event on remote access services such as RDP, VPN, or NTLM. The rule filters for non-private IP addresses and flags successes occurring outside of standard business hours.
Detects anomalous sign-in behavior shortly after a successful MFA-authenticated session in Microsoft 365. This rule flags scenarios where a subsequent session for the same user occurs within a short window (30 minutes) from a different IP, ASN, User-Agent, or device identifier, potentially indicating the replay of a stolen session cookie obtained via Adversary-in-the-Middle (AiTM) phishing.
Detects the registration of a new scheduled task occurring within a network logon session (LogonType 3). This behavior is characteristic of lateral movement techniques where attackers use remote service execution tools (such as Impacket's atexec or PRTremote) to register and execute tasks on a remote host via SMB/RPC. The rule correlates Windows Security Event 4698 (Task creation) with network logon events and validates the action using Task Scheduler operational logs.
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