Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential suspicious behaviour using secedit.exe. Such as exporting or modifying the security policy
Detects Processes accessing the camera and microphone from suspicious folder
This query looks for users sharing access to files with external users.
This applies to SharePoint and OneDrive users.
Audit event and Cloud application identifier references.
Reference - https://learn.microsoft.com/microsoft-365/compliance/audit-log-sharing?view=o365-worldwide
Reference - https://learn.microsoft.com/azure/sentinel/entities-reference#cloud-application-identifiers
This applies to SharePoint and OneDrive users.
Audit event and Cloud application identifier references.
Reference - https://learn.microsoft.com/microsoft-365/compliance/audit-log-sharing?view=o365-worldwide
Reference - https://learn.microsoft.com/azure/sentinel/entities-reference#cloud-application-identifiers
In this detection,we hunt for any sign-in attempt from a non-managed, non-compliant, untrusted device.
Detects PowerShell scripts that contains reference to keystroke capturing functions
Detects chromium based browsers starting in headless and debugging mode and pointing to a user profile. This could be a sign of data stealing or remote control
'This query looks for any mass download by a single user with possible file copy activity to a new USB drive. Malicious insiders may perform such activities that may cause harm to the organization.
This query could also reveal unintentional insider that had no intention of malicious activity but their actions may impact an organizations security posture.
Reference:https://docs.microsoft.com/defender-cloud-apps/policy-template-reference'
This query could also reveal unintentional insider that had no intention of malicious activity but their actions may impact an organizations security posture.
Reference:https://docs.microsoft.com/defender-cloud-apps/policy-template-reference'
Detects suspicious patterns in program names or folders that are often found in malicious samples or hacktools
Detects PowerShell scripts that make use of the "Compress-Archive" cmdlet in order to compress folders and files.
An adversary might compress data (e.g., sensitive documents) that is collected prior to exfiltration in order to make it portable and minimize the amount of data sent over the network.
An adversary might compress data (e.g., sensitive documents) that is collected prior to exfiltration in order to make it portable and minimize the amount of data sent over the network.
Hacktool Ruler
Sigma
This events that are generated when using the hacktool Ruler by Sensepost
Detects loading of "credui.dll" and related DLLs by an uncommon process. Attackers might leverage this DLL for potential use of "CredUIPromptForCredentials" or "CredUnPackAuthenticationBufferW".
This query searches for file copies which occur within a period of time (by default 15 min) to volumes other than the C drive or UNC shares. By default, this query will
search all devices. A single device can be specified by entering the DeviceName in the DeviceNameToSearch variable. Additionally, to change the period of time from when
the USB device was inserted, adjust the TimespanInSeconds value.
Happy hunting!
search all devices. A single device can be specified by entering the DeviceName in the DeviceNameToSearch variable. Additionally, to change the period of time from when
the USB device was inserted, adjust the TimespanInSeconds value.
Happy hunting!
Detects a command used by conti to dump database
Detects process injection using the signed Windows tool "Mavinject" via the "INJECTRUNNING" flag
Detects browsers starting with the remote debugging flags. Which is a technique often used to perform browser injection attacks
Detects potentially suspicious command line arguments of common data compression tools
"This Kusto (KQL) hunting query detects blob-enumeration or file-spraying behaviour in Azure Storage by:
- Aggregating requests into time-bound sessions with row_window_session().
- Defining a "user" as the combination of AccountName | UserAgentHeader, which is tolerant of rapid IP rotation.
- Raising an alert when, within any single session:
- The actor touches at least 10 distinct objects, and
- At least 50 % of those requests return an HTTP 4xx/5xx status, and
- Each object is accessed exactly once ("touch-once" pattern typical of enumeration).
All tuning knobs (look-back window, session gap, thresholds, authentication type) are exposed at the top of the query.
Be sure to validate the query against both benign and malicious samples in your own environment before relying on it for production detection.
Reference: https://techcommunity.microsoft.com/blog/microsoftdefendercloudblog/protect-your-storage-resources-against-blob-hunting/3735238"
- Aggregating requests into time-bound sessions with row_window_session().
- Defining a "user" as the combination of AccountName | UserAgentHeader, which is tolerant of rapid IP rotation.
- Raising an alert when, within any single session:
- The actor touches at least 10 distinct objects, and
- At least 50 % of those requests return an HTTP 4xx/5xx status, and
- Each object is accessed exactly once ("touch-once" pattern typical of enumeration).
All tuning knobs (look-back window, session gap, thresholds, authentication type) are exposed at the top of the query.
Be sure to validate the query against both benign and malicious samples in your own environment before relying on it for production detection.
Reference: https://techcommunity.microsoft.com/blog/microsoftdefendercloudblog/protect-your-storage-resources-against-blob-hunting/3735238"
This query helps hunting for BEC - File sharing tactics - OneDrive or SharePoint
Detects the execution of different compiled Windows binaries of the impacket toolset (based on names or part of their names - could lead to false positives)
Detects execution of renamed Remote Utilities (RURAT) via Product PE header field
'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.'
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