Azure Sentinel
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1,223 detections
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'Detect mass file deletion events within Azure File and Blob storage. deleteWindow controls
the period of time the deletions must occur in, whilst the deleteThreshold controls how many files
must be deleted within that threshold. Query works on a per-IP address basis, so will only detect a single
IP deleting multiple files.'
the period of time the deletions must occur in, whilst the deleteThreshold controls how many files
must be deleted within that threshold. Query works on a per-IP address basis, so will only detect a single
IP deleting multiple files.'
'This content is utilized to identify instances of successful login by risky users, who have been observed engaging in potentially suspicious network activity on non-Microsoft network devices.'
'This content is employed to correlate with Microsoft Defender XDR phishing-related alerts. It focuses on instances where a user successfully connects to a phishing URL from a non-Microsoft network device and subsequently makes successful sign-in attempts from the phishing IP address.'
Looks for multiple users that had their admin role removed by a single user within a certain period.
'This detection identifies high-severity alerts across various Microsoft security products, including Microsoft Defender XDR and Microsoft Entra ID, and correlates them with instances of Google Cloud VM creation. It focuses on instances where VMs were created within a short timeframe of high-severity alerts, potentially indicating suspicious activity.'
'Identifies a list of IP addresses with a minimum number (default of 5) of failed logon attempts to Microsoft Entra ID.
Uses that list to identify any successful remote logons to hosts from these IPs within the same timeframe.'
Uses that list to identify any successful remote logons to hosts from these IPs within the same timeframe.'
This query helps you design client firewall rules based on data stored within DeviceNetworkEvents. Folder paths are alias'ed to help represent the
files making or receiving network connections without dealing with duplication from path variance due to different root drive letter or user profile
association.
To make the report easy to read, inbound remote IP addresses are not calculated by default (this can be changed by setting the value of IncludeInboundRemoteIPs to true).
Also, the ephemeral range is defaulted to 49152 to help eliminate false detections.
files making or receiving network connections without dealing with duplication from path variance due to different root drive letter or user profile
association.
To make the report easy to read, inbound remote IP addresses are not calculated by default (this can be changed by setting the value of IncludeInboundRemoteIPs to true).
Also, the ephemeral range is defaulted to 49152 to help eliminate false detections.
'Identifies anomalous data transfer to public networks. The query leverages built-in KQL anomaly detection algorithms that detects large deviations from a baseline pattern.
A sudden increase in data transferred to unknown public networks is an indication of data exfiltration attempts and should be investigated.
The higher the score, the further it is from the baseline value.
The output is aggregated to provide summary view of unique source IP to destination IP address and port bytes sent traffic observed in the flagged anomaly hour.
The source IP addresses which were sending less than bytessentperhourthreshold have been exluded whose value can be adjusted as needed .
You may have to run queries for individual source IP addresses from SourceIPlist to determine if anything looks suspicious'
A sudden increase in data transferred to unknown public networks is an indication of data exfiltration attempts and should be investigated.
The higher the score, the further it is from the baseline value.
The output is aggregated to provide summary view of unique source IP to destination IP address and port bytes sent traffic observed in the flagged anomaly hour.
The source IP addresses which were sending less than bytessentperhourthreshold have been exluded whose value can be adjusted as needed .
You may have to run queries for individual source IP addresses from SourceIPlist to determine if anything looks suspicious'
"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 look for Service Principal accounts that are no longer used where a user has added or updated credentials for them before logging in with the Service Principal.
Threat actors may look to re-activate dormant accounts and use them for access in the hope that changes to such dormant accounts may go un-noticed.'
Threat actors may look to re-activate dormant accounts and use them for access in the hope that changes to such dormant accounts may go un-noticed.'
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