Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects bulk access to the 'about-us' page on a web server. It triggers an alert if a single source IP makes 15 or more HTTP requests containing 'about-us' in the URI within a 30-second window. This behavior can indicate reconnaissance activity, where an attacker is rapidly enumerating or scraping information from a company's public-facing web pages.
This rule detects attempts to harvest physical location data via web requests. It specifically looks for HTTP GET requests where the URI contains both 'location' and 'address' (case-insensitive). A threshold of 15 such requests within 30 seconds from the same source IP triggers the alert, indicating a potential network scan or automated data collection activity.
This rule detects repeated HTTP requests to a web server where the URI contains the case-insensitive string "headquarters". It triggers an alert if a single source IP makes 10 such requests within a 30-second window. This behavior is indicative of an automated attempt to scrape information related to a company's headquarters address, potentially for reconnaissance purposes.
This rule detects attempts to look up physical office locations via web requests. It specifically triggers on HTTP GET requests where the URI contains both 'office' and 'location' (case-insensitive). A threshold of 10 such requests from the same source within 30 seconds is set to reduce false positives.
'Highlights accounts associated with multiple authentications from different geographical locations in a short period of time.'
'This query examines Microsoft Entra ID sign-ins and identifies anomalous changes in a user's location profile. A variation joins results back onto the original sign-in data to review the location set with each identified user in tabular form.'
Detects when there is a login attempt from a country that has not seen a successful login in the previous 14 days.
Threat actors may attempt to authenticate with credentials from compromised accounts - monitoring attempts from anomalous locations may help identify these attempts.
Authentication attempts should be investigated to ensure the activity was legitimate and if there is other similar activity.
Ref: https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts#monitoring-for-failed-unusual-sign-ins
Threat actors may attempt to authenticate with credentials from compromised accounts - monitoring attempts from anomalous locations may help identify these attempts.
Authentication attempts should be investigated to ensure the activity was legitimate and if there is other similar activity.
Ref: https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts#monitoring-for-failed-unusual-sign-ins
'The alert shows users that join a Zoom meeting from a time zone other than the one the meeting was created in.
You can also whitelist known good time zones in the tz_whitelist value using the tz database name format https://en.wikipedia.org/wiki/List_of_tz_database_time_zones'
You can also whitelist known good time zones in the tz_whitelist value using the tz database name format https://en.wikipedia.org/wiki/List_of_tz_database_time_zones'