Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 anomalous reuse of an authenticated Microsoft 365 session cookie shortly after a successful MFA-satisfied sign-in. The detection identifies scenarios where the subsequent access originates from a different IP address, device, or user agent without an intervening MFA challenge, which is a pattern indicative of session hijacking techniques like Adversary-in-the-Middle (AiTM) or session token replay.
Detects potential session replay or cookie theft attacks against Google Workspace accounts. The rule identifies anomalous session activity where a single session ID is associated with multiple country codes within a short timeframe (less than 60 minutes), suggesting that a stolen session token is being used by an adversary in a different location than the legitimate user.
Detects potential session replay or cookie theft attacks against Google Workspace accounts. The rule identifies anomalous session activity where a single session ID is associated with multiple country codes within a short timeframe (less than 60 minutes), suggesting that a stolen session token is being used by an adversary in a different location than the legitimate user.
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 sign-ins with impossible browser/OS combinations and Outlook-labeled sign-ins presenting non-native user agents, consistent with Storm-2755 AiTM session token replay and impersonation.
Detects Outlook sign-ins that reuse the same SessionId roughly every 8 hours while source IP/ASN change, consistent with attackers replaying a stolen AiTM-captured session token through rotating residential proxy infrastructure.
Detects a new-device Okta sign-in followed by three or more failed Admin Console authentication attempts originating from a different device/IP context, consistent with privilege escalation using a stolen AiTM session token.
Detects a single Entra ID session (SessionId) being used from two different countries within one hour at a travel velocity no physical journey could achieve. This is a signature of a stolen session/refresh token being replayed by an actor from a different location than the legitimate user.
Detects AiTM reverse-proxy pages injecting the ServerData=$Config script alongside a redirUrl/api.country.is capture script and a rewritten login.microsoftonline.com authorize path hosted on a non-Microsoft domain, used to steal OAuth2 session tokens and bypass MFA.
Slack Anomalous Activity
Cortex XDR
This rule detects anomalous activity reported by Slack's internal anomaly detection system. This includes events such as impossible travel, new device access, suspicious IP changes, and other behavioral anomalies that Slack identifies. The rule extracts relevant user and context information for further investigation.
Detects outbound network traffic to the 'logfriend[.]com' domain, specifically to endpoints used by the Forg365 'ForgCookie' browser extension. This extension is known to facilitate the automated refreshing of Microsoft SSO cookies, potentially enabling persistent session hijacking and bypassing MFA.
This rule detects scenarios where a user's session originates from the 'Microsoft Authentication Broker' and another application (like 'OfficeHome' or 'One Outlook Web') within a short window (15 minutes), but from different source IP addresses. This indicates potential session hijacking or the use of stolen session cookies by an external actor.
Detects the presence of specific Microsoft Entra (formerly Azure AD) authentication session cookies (ESTSAUTH, ESTSAUTHPERSISTENT, ESTSAUTHLIGHT) in web proxy traffic. This activity is indicative of session cookie theft and potential replay attacks (Pass-the-Cookie) where an adversary attempts to authenticate to Microsoft services using stolen session material from an unauthorized or non-enrolled device.
Detects instances where a user successfully authenticates using Multi-Factor Authentication (MFA) from one location, followed by a Single-Factor Authentication (SFA) logon from a different location within a 10-minute window. This behavior is indicative of potential session hijacking or session cookie theft where an attacker reuses an authenticated session or manipulates the authentication flow to bypass MFA requirements.
Detects stolen session token reuse to bypass MFA by correlating a successful SSO/VPN login from one IP with a subsequent successful login from a different IP using the same user agent context, or a user-agent change between sessions for the same user within a short window. Targets access broker technique where infostealer-harvested session cookies are replayed from different source IPs.
Detects potential Adversary-in-the-Middle (AiTM) activity by monitoring for suspicious browser process spawning scripting child processes (powershell.exe, wscript.exe, etc.), unusual DNS requests to Microsoft login/Graph API endpoints from scripting hosts, and direct non-browser access to browser cookie database files.
Detects potential Adversary-in-the-Middle (AiTM) phishing activity by identifying successful user sign-ins from a new, historically unseen IP address occurring within 30 minutes of a legitimate sign-in from a known IP, indicating the potential replay of a stolen session or refresh token.
Detects stolen session token reuse to bypass MFA by correlating a successful SSO/VPN login from one IP with a subsequent successful login from a different IP using the same user agent context, or a user-agent change between sessions for the same user within a short window. Targets access broker technique where infostealer-harvested session cookies are replayed from different source IPs.
This rule detects potential MFA bypass via stolen session cookies by identifying successful single-factor authentications from new or unmanaged/non-compliant devices, especially when originating from a new geographical location for the user or exhibiting medium/high sign-in risk. It correlates impossible travel, new device, and lack of MDM/EDR compliance signals.
Detects non-interactive OAuth2 token refresh attempts targeting Microsoft 365 services where the authentication is satisfied by a pre-existing session without MFA challenge. The rule flags instances where the sign-in originates from an IP address with a different ASN or country than the user's previous interactive session and uses specific browser user-agents identified in known Adversary-in-the-Middle (AiTM) campaigns like the Payroll Pirate.
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