Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a sequence of events indicative of an Adversary-in-the-Middle (AiTM) attack, specifically 'NovaCookies'. The rule identifies a phishing email lure (DocuSign/SharePoint-themed) received by a user, followed within a 6-hour window by an anomalous Microsoft 365 sign-in from that same user. The anomalous sign-in is defined by either risk flags or conditional access failure, suggesting potential replay of a captured session cookie.
Detects OfficeHome sign-in events featuring the 90014 error code (missing OAuth nonce). The rule looks for a specific mismatch where mobile browser User Agents are observed on a system reported as Windows 10, a pattern consistent with Adversary-in-the-Middle (AiTM) session token replay attacks attempting to access Microsoft 365 environments.
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.
This rule detects email-based business fraud (BEC) targeting the organization, specifically looking for executive impersonation paired with financial lure terminology and sender domain mismatches. It utilizes both a blocklist of known fraudulent sender indicators (domains and addresses) and a heuristic approach analyzing discrepancies between the envelope sender domain and the header sender domain combined with executive titles in display names and invoice-related keywords.
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 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.
This rule monitors network connection logs, DNS query logs, and common security logs for known indicators of compromise, specifically IP addresses and domains associated with command and control (C2) infrastructure.
This rule detects email-based business fraud (BEC) targeting the organization, specifically looking for executive impersonation paired with financial lure terminology and sender domain mismatches. It utilizes both a blocklist of known fraudulent sender indicators (domains and addresses) and a heuristic approach analyzing discrepancies between the envelope sender domain and the header sender domain combined with executive titles in display names and invoice-related keywords.
This rule detects email-based business fraud (BEC) targeting the organization, specifically looking for executive impersonation paired with financial lure terminology and sender domain mismatches. It utilizes both a blocklist of known fraudulent sender indicators (domains and addresses) and a heuristic approach analyzing discrepancies between the envelope sender domain and the header sender domain combined with executive titles in display names and invoice-related keywords.
Detects a sequence of events where a user performs a sign-in from an unmanaged or mobile device while interacting with applications often associated with MFA or SSO prompts (indicative of a social engineering lure), followed by an administrative update to register a new authentication method within 30 minutes. This pattern is characteristic of attackers establishing persistent access to an account by adding their own MFA device.
Detects internal phishing messages sent via Microsoft Teams that contain common credential-harvesting lures (e.g., passkey, MFA, SSO updates) where the sender account has also exhibited indicators of compromise within the preceding 24 hours, such as risky sign-ins or impossible travel.
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 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.
This rule detects email-based business fraud (BEC) targeting the organization, specifically looking for executive impersonation paired with financial lure terminology and sender domain mismatches. It utilizes both a blocklist of known fraudulent sender indicators (domains and addresses) and a heuristic approach analyzing discrepancies between the envelope sender domain and the header sender domain combined with executive titles in display names and invoice-related keywords.
Detects anomalous, high-volume enumeration of SharePoint and OneDrive resources via Microsoft Graph API by monitoring for repeated access patterns involving /sites, /drives, or /drive endpoints combined with search, directory traversal, and pagination parameters.
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 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 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 detects email-based business fraud (BEC) targeting the organization, specifically looking for executive impersonation paired with financial lure terminology and sender domain mismatches. It utilizes both a blocklist of known fraudulent sender indicators (domains and addresses) and a heuristic approach analyzing discrepancies between the envelope sender domain and the header sender domain combined with executive titles in display names and invoice-related keywords.
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 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.
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