Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential data exfiltration attempts via email by monitoring internal users sending emails to external domains. It flags suspicious activity based on three criteria: a high volume of emails sent (over 100) combined with a large total data size (over 50 MB), a significant number of emails sent to personal domains (over 20), or a notable count of emails with sensitive subjects (over 5). The rule aggregates these metrics over a 1-day window for each user.
This analytic detects the creation or modification of mailbox rules in Office 365, a technique commonly used in Business Email Compromise (BEC) attacks to hide malicious emails. It uses a scoring mechanism based on attributes like rule name entropy, name length, 'MarkAsRead' action, and 'MoveToFolder' destination to identify suspicious rules. A high score indicates a potential attacker has gained access to the account and is attempting to conceal their activities or exfiltrate information.
KQL Query from file: Direct Send Abuse Detection
Analyze Mail Bomb Attack by ISP
KQL Query from file: Sentinel All-In-One IP ThreatHunt
KQL Query
KQL Query
KQL Query from file: Data Exfiltration via Microsoft Teams
KQL Query
KQL Query from file: MailItemsAccessed Defense
KQL Query
KQL Query from file: Sentinel All-In-One UPN ThreatHunt
KQL Query
This query visualises top outbound recipient domains by outbound email volume and shows total number of inbound emails with Threats from the same domains (as inbound senders)
This query helps reviewing quarantine release trend in Defender for Office 365
'This query helps detect new Microsoft Entra ID sign in from a new location correlating with Office Activity data highlighting cases where user mails are being forwarded and shows if it is being forwarded to external domains as well.'
'It is possible that a disabled user account is compromised and another account on the same IP is used to perform operations that are not typical for that user.
The query filters the SigninLogs for entries where ResultType is indicates a disabled account and the TimeGenerated is within a defined time range.
It then summarizes these entries by IPAddress and AppId, calculating various statistics such as number of login attempts, distinct UPNs, App IDs etc and joins these results with another set of results from SigninLogs, filtering for entries with less than normal number of successful sign-ins.
It then filters out entries where there were no successful sign-ins or where successful sign-ins did not occur within the same lookback period as the failed sign-ins, later projecting relevant fields by the count of login attempts, and expands the set of successful sign-ins into individual events.
Finally, it joins these results with entries from OfficeActivity where certain operations deemed rare and high risk have been performed, ensuring their occurrance within a certain time range of the successful sign-ins.'
The query filters the SigninLogs for entries where ResultType is indicates a disabled account and the TimeGenerated is within a defined time range.
It then summarizes these entries by IPAddress and AppId, calculating various statistics such as number of login attempts, distinct UPNs, App IDs etc and joins these results with another set of results from SigninLogs, filtering for entries with less than normal number of successful sign-ins.
It then filters out entries where there were no successful sign-ins or where successful sign-ins did not occur within the same lookback period as the failed sign-ins, later projecting relevant fields by the count of login attempts, and expands the set of successful sign-ins into individual events.
Finally, it joins these results with entries from OfficeActivity where certain operations deemed rare and high risk have been performed, ensuring their occurrance within a certain time range of the successful sign-ins.'
This query looks for anomalies in mail item access events made by Graph API. It uses standard deviation to determine if the number of events is anomalous. The query returns all clientIDs where the amount of mail sent per day was larger than value given by the formula, 'average + STDThreshold(2.5)*(standard deviation)'.
See The MailItemsAccessed mailbox auditing action.
Reference - https://docs.microsoft.com/microsoft-365/compliance/mailitemsaccessed-forensics-investigations?view=o365-worldwide#the-mailitemsaccessed-mailbox-auditing-action
See The MailItemsAccessed mailbox auditing action.
Reference - https://docs.microsoft.com/microsoft-365/compliance/mailitemsaccessed-forensics-investigations?view=o365-worldwide#the-mailitemsaccessed-mailbox-auditing-action
Intent:
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.
This query helps hunting for Inbox rule changes which forward-redirect email
This query helps in reviewing top policies for admin overrides (Allow/Block)
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