Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects signs of Adversary-in-the-Middle (AiTM) phishing kits by identifying sequential, rapid-fire attempts to authenticate using multiple distinct MFA methods (such as push notifications, TOTP codes, or SMS) within a single sign-in session. These attempts are combined with explicit failure states (rejected passwords, rejected codes, or denied MFA requests), suggesting an attacker is relaying authentication challenges in real-time to a victim.
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 monitors Azure AD Sign-in logs to identify 'impossible travel' scenarios, where a user authenticates successfully from two geographically distant locations within a time window (1 hour) that would require travel speeds exceeding a plausible threshold. This behavior is a common indicator of credential compromise or session token replay attacks.
This rule monitors network connections, DNS resolutions, and email URLs to detect traffic communicating with a known adversary-in-the-middle (AiTM) phishing infrastructure panel. By correlating security logs, DNS events, and email URL data against this specific indicator of compromise, it identifies potential interaction with phishing sites designed to capture credentials or session tokens.
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 alerts that reference specific CVEs historically exploited by the threat group QTFY against internet-facing applications, including common vulnerabilities in Pulse Secure, FortiOS, Citrix ADC, Exchange, F5 BIG-IP, Log4Shell, and others, when the alert severity is Medium or High and contains indicators of exploit or initial access.
Detects anomalous authentication patterns indicative of session token replay attacks. The rule identifies instances where a user successfully performs an MFA-authenticated, interactive sign-in, followed shortly (within 5-60 minutes) by a single-factor sign-in for the same user. The suspicious activity is characterized by a shift to a different IP/ASN, an unmanaged device (non-trusted), and a change in browser or OS identifiers, all while the user's geolocation (city/country) remains consistent. This behavioral pattern is highly consistent with the use of residential proxy infrastructure to replay stolen session tokens, effectively bypassing MFA.
Detects anomalous authentication patterns indicative of session token replay attacks. The rule identifies instances where a user successfully performs an MFA-authenticated, interactive sign-in, followed shortly (within 5-60 minutes) by a single-factor sign-in for the same user. The suspicious activity is characterized by a shift to a different IP/ASN, an unmanaged device (non-trusted), and a change in browser or OS identifiers, all while the user's geolocation (city/country) remains consistent. This behavioral pattern is highly consistent with the use of residential proxy infrastructure to replay stolen session tokens, effectively bypassing MFA.
Detects anomalous authentication patterns indicative of session token replay attacks. The rule identifies instances where a user successfully performs an MFA-authenticated, interactive sign-in, followed shortly (within 5-60 minutes) by a single-factor sign-in for the same user. The suspicious activity is characterized by a shift to a different IP/ASN, an unmanaged device (non-trusted), and a change in browser or OS identifiers, all while the user's geolocation (city/country) remains consistent. This behavioral pattern is highly consistent with the use of residential proxy infrastructure to replay stolen session tokens, effectively bypassing MFA.
This rule monitors network connections, DNS resolutions, and email URLs to detect traffic communicating with a known adversary-in-the-middle (AiTM) phishing infrastructure panel. By correlating security logs, DNS events, and email URL data against this specific indicator of compromise, it identifies potential interaction with phishing sites designed to capture credentials or session tokens.
This rule monitors Azure AD Sign-in logs to identify 'impossible travel' scenarios, where a user authenticates successfully from two geographically distant locations within a time window (1 hour) that would require travel speeds exceeding a plausible threshold. This behavior is a common indicator of credential compromise or session token replay attacks.
Detects anomalous authentication patterns indicative of session token replay attacks. The rule identifies instances where a user successfully performs an MFA-authenticated, interactive sign-in, followed shortly (within 5-60 minutes) by a single-factor sign-in for the same user. The suspicious activity is characterized by a shift to a different IP/ASN, an unmanaged device (non-trusted), and a change in browser or OS identifiers, all while the user's geolocation (city/country) remains consistent. This behavioral pattern is highly consistent with the use of residential proxy infrastructure to replay stolen session tokens, effectively bypassing MFA.
This rule monitors network connections, DNS resolutions, and email URLs to detect traffic communicating with a known adversary-in-the-middle (AiTM) phishing infrastructure panel. By correlating security logs, DNS events, and email URL data against this specific indicator of compromise, it identifies potential interaction with phishing sites designed to capture credentials or session tokens.
Detects signs of Adversary-in-the-Middle (AiTM) phishing kits by identifying sequential, rapid-fire attempts to authenticate using multiple distinct MFA methods (such as push notifications, TOTP codes, or SMS) within a single sign-in session. These attempts are combined with explicit failure states (rejected passwords, rejected codes, or denied MFA requests), suggesting an attacker is relaying authentication challenges in real-time to a victim.
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.
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 anomalous login activity in Google Workspace characterized by a high volume of login failures (5 or more) originating from a single IP address. The rule identifies potential brute force or credential stuffing campaigns and flags instances where a successful login occurs following a burst of failure events from the same source.
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 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.
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 successful authentication to Microsoft Teams or Slack where MFA was successfully completed, but the device is reported as unmanaged or non-compliant and is accompanied by sign-in risk signals. This behavior is consistent with Adversary-in-the-Middle (AitM) proxy attacks where an attacker captures credentials and session tokens, bypassing MFA, and using the hijacked session from an unrecognized device or location.
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