Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects when a user from a specified watchlist sends an email with a large attachment (over 5MB).
This rule detects suspicious activity related to mailbox access within Office 365. It has two main parts: 1) Identifies users accessing a high number of distinct mailboxes belonging to other users. 2) Identifies users accessing a high number of distinct folders within another user's mailbox. Both parts are designed to flag potential unauthorized access, data exfiltration, or reconnaissance activities within an Exchange Online environment.
This query detects suspicious sign-in activity from a user who has recently clicked on a phishing link. It correlates email click events with sign-in logs, identifying sign-ins from new or infrequent IP addresses after a user has interacted with a suspicious email. The rule uses configurable parameters for sender email addresses, sender domains, and subject keywords to identify phishing emails.
TIFCE (Threat Intelligence Feed Content Evaluation) is a simple way to measure if a TI feed is actually useful based on four things — uniqueness, real matches, confirmed maliciousness, and activity.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
TIFCE (Threat Intelligence Feed Content Evaluation) is a simple way to measure if a TI feed is actually useful based on four things — uniqueness, real matches, confirmed maliciousness, and activity.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
This rule detects inbound emails classified as phishing or malware by the email security system. It summarizes the total number of such messages, provides sample subjects, and counts how many were blocked, delivered to mailboxes, junked, or had other actions. The rule specifically focuses on emails that were delivered to a mailbox, indicating a potential bypass of initial security measures or a need for further investigation.
TIFCE (Threat Intelligence Feed Content Evaluation) is a simple way to measure if a TI feed is actually useful based on four things — uniqueness, real matches, confirmed maliciousness, and activity.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
Azure Device Code OAuth Consent
Cortex XDR
This rule detects suspicious activity related to Microsoft 365 Device Code OAuth consent flows. It specifically looks for device code authentications that are single-factor or lack MFA, and then groups these by IP address and client application. The rule identifies suspicious patterns such as a high number of logins, unique users, or unique applications from a single IP address, or rapid login attempts within a short timeframe, which could indicate enumeration or phishing attempts.
Detects phishing emails containing QR codes rendered using HTML tables. This technique is used to evade image-based scanning and OCR security controls by representing the QR code as a grid of small, colored table cells (<td>) instead of a traditional image file.
This rule detects inbound emails that appear to be Microsoft Teams invitations but contain suspicious keywords in the subject line related to financial transactions (invoice, billing, payment, renewal, charge). This could indicate a phishing attempt where adversaries leverage legitimate-looking Microsoft invitation emails to deliver financially themed lures.
Detects suspicious email inbox rule creation indicative of account compromise. Focuses on rules with randomly-generated names or rules that move emails to low-visibility folders combined with hiding actions (mark as read, delete, stop processing).
This rule detects potential malicious email campaigns by identifying when multiple users submit email reports (e.g., phishing or spam) that share common entities such as sender IP, primary sender address/domain, secondary sender address/domain, or subject line. A configurable threshold determines the minimum number of distinct reports required to flag an entity as suspicious.
Detects successful Microsoft 365 sign-ins using the OAuth 2.0 device code grant flow for applications with low prevalence. This technique is used by threat actors to gain unauthorized access to accounts, bypassing some MFA controls.
This detection identifies network connections to known first-stage Microsoft 365 phishing domains associated with an active Adversary-in-the-Middle (AiTM) campaign.
This Query is oriented to identify Malicious URL sent via Microsoft Teams and detect possible hits based on online Malware sites reported by the TI Feed URL Haus.
This KQL Query helps to understand all the URL Redirections from URLs received by Email using the UrlChainId identifier on KQL that groups together all URLs that belong to the same “click/redirect chain”. When an message contains a URL, that URL may redirect through several intermediate URLs (trackers, shorteners, phishing, etc.) before land on the final site. KQL builds a URL chain from the original URL in the email through each redirect hop. All URLs that are part of a single chain share the same UrlChainId and for each hop. On the other hand, UrlChainPosition register the position of every URL, the original one = value 0 and the other redirections tagged with next numbers(1, 2, etc. ) The following query includes different options to classify the insights into four categories:
Tracking Domains
Redirecting to Different Countries
Redirecting to Different Domains
Number of Redirections
Tracking Domains
Redirecting to Different Countries
Redirecting to Different Domains
Number of Redirections
This rule detects when a domain or URL observed in Teams Messages matches a known threat intelligence indicator from Microsoft Defender Threat Intelligence. It specifically looks for hits against 'Domain' and 'URL' type indicators.
Detects when an internal user successfully authenticates as a guest to an external Microsoft Teams tenant. This could be legitimate B2B collaboration, but it can also be abused by attackers to lure users into a malicious tenant where security controls (like Safe Links/Safe Attachments) are not enforced.
Detects a high volume of Microsoft Teams invitation emails sent to multiple users within the organization. This could indicate a reconnaissance attempt or a widespread phishing campaign where an attacker is trying to lure users into a malicious external tenant, bypassing some internal security controls.
Detects when a Microsoft Teams messaging policy is modified to allow users to send B2B invitations to external users ('UseB2BInvitesToAddExternalUsers' set to 'True'). While this can be a legitimate administrative change, it can also be an indicator of misconfiguration or malicious activity to enable phishing attacks by luring users to malicious external tenants where organizational security controls do not apply.
Detects when an internal user successfully authenticates as a guest to an external Microsoft Teams tenant. This could be legitimate B2B collaboration, but it can also be abused by attackers to lure users into a malicious tenant where security controls (like Safe Links/Safe Attachments) are not enforced.
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