Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects inbound emails from external domains containing keywords related to financial transactions or urgency in the subject line (specifically matching forwarded or reply formats) accompanied by PDF or HTML attachments. This heuristic approach attempts to identify potential business email compromise (BEC) or phishing lures mimicking invoices or approval requests in environments where raw email body content is unavailable.
This rule detects potential OAuth token theft resulting from device code phishing (e.g., N0va phishkit). It monitors for a successful OAuth device-code authentication followed within 5 minutes by a secondary successful sign-in for the same user from a different IP address, different browser client, or different user agent, which is a common indicator of an adversary-in-the-middle (AiTM) session hijacking attempt.
This rule detects potential credential or token theft attempts from the N0va phishing kit. It monitors for emails lacking attachments that contain specific URL patterns associated with verification or session initialization, coupled with social engineering tactics such as spoofing legitimate service display names or subjects (e.g., Microsoft Teams, DocuSign, etc.) while originating from non-legitimate domains.
This rule detects potential credential or token theft attempts from the N0va phishing kit. It monitors for emails lacking attachments that contain specific URL patterns associated with verification or session initialization, coupled with social engineering tactics such as spoofing legitimate service display names or subjects (e.g., Microsoft Teams, DocuSign, etc.) while originating from non-legitimate domains.
This rule detects phishing emails where the sender's display name impersonates well-known brands (e.g., Microsoft, DocuSign, Zoom) while using a non-official domain. It further correlates these suspicious senders with embedded URLs that either match the targeted brands' domains or contain patterns commonly associated with device code phishing or API verification workflows.
This rule detects phishing emails where the sender's display name impersonates well-known brands (e.g., Microsoft, DocuSign, Zoom) while using a non-official domain. It further correlates these suspicious senders with embedded URLs that either match the targeted brands' domains or contain patterns commonly associated with device code phishing or API verification workflows.
Detects anomalous access to sensitive Microsoft Graph API endpoints (messages, mailFolders, contacts) following a device-code authentication. The rule specifically flags activity from non-standard or generic client applications, which is a pattern often associated with post-compromise proxying or token abuse, such as the 'ARToken' technique.
This rule detects high-volume, burst-pattern email distribution associated with a 'New VM Received' subject line, originating from non-authorized or non-corporate domains. This behavior is indicative of potential mass phishing or spam campaigns mimicking automated voicemail notifications.
This rule detects high-volume, burst-pattern email distribution associated with a 'New VM Received' subject line, originating from non-authorized or non-corporate domains. This behavior is indicative of potential mass phishing or spam campaigns mimicking automated voicemail notifications.
This rule detects high-volume, burst-pattern email distribution associated with a 'New VM Received' subject line, originating from non-authorized or non-corporate domains. This behavior is indicative of potential mass phishing or spam campaigns mimicking automated voicemail notifications.
This rule monitors incoming emails by cross-referencing sender addresses against a hardcoded list of known malicious or suspicious email accounts. It associates these emails with any potential attachments to provide context for further investigation.
Detects anomalous administrative activity within Microsoft Exchange by identifying accounts performing multiple suspicious operations within a short timeframe. This rule flags activities like modifying transport rules, virtual directories, or management role assignments, which are often indicative of malicious persistence or configuration tampering, while excluding known authorized service accounts.
Detects inbound traffic, sign-ins, and email activity originating from the Anthropic IP range 160.79.104.0/21.
This rule correlates email sender activity with network, cloud, and identity logs by matching traffic against a specific IP range (160.79.104.0/21) identified as malicious or suspicious. The rule flags instances where this range appears as an email sender IP or as a remote/source IP address across various infrastructure indices, potentially indicating adversary communication or exfiltration.
This rule detects various event types (email, identity authentication, network connections, and cloud audit logs) originating from or interacting with the specific IP address range 160.79.104.0/22 to 160.79.111.0/22, which is associated with known malicious activity.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
This rule performs a hunting activity across multiple telemetry sources (Network, Email, Endpoint) to detect known indicators of compromise (IOCs) associated with Anthropic threat intelligence reporting (September 2026). It looks for specific malware file names, command-line patterns, service installations, phishing email addresses, and C2 communication URLs.
Detects high-frequency access requests to SharePoint or OneDrive services using the 'python-httpx' library. This behavior is indicative of automated scraping or mass data retrieval often associated with malicious actors or unauthorized automated tools.
Detects users accessing files across SharePoint, OneDrive, or Exchange over a sustained period of at least 6 hours, while maintaining a low-to-moderate frequency (1-999 events per hour). This behavioral pattern may indicate slow, automated data exfiltration or unauthorized reconnaissance of sensitive files while attempting to stay under traditional volume-based alerting thresholds.
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