Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects suspicious enumeration of Azure Blob, File, Table, Queue, or DFS storage accounts by internal users. It identifies devices making network connections to public Azure storage URLs using potentially suspicious processes (e.g., PowerShell, Python, AzCopy, curl, wget, WinSCP, FileZilla, Storage Explorer). The rule then analyzes the distinct storage accounts accessed and uses a Jaccard index to identify unusual naming conventions among the accessed storage accounts, potentially indicating an insider attempting to discover or exfiltrate data from unfamiliar storage resources.
This detection identifies when a user or service principal executes a command inside an AKS pod ('kubectl exec') and then, using the same identity, accesses data in a sensitive Azure Blob Storage container within a short time frame. This pattern can indicate an attacker, having gained initial access to the Kubernetes API, is using a pod as a pivot point to discover and exfiltrate sensitive data.
This rule detects successful 'GetObject' operations on AWS S3 buckets originating from external IP addresses (not within common private IP ranges). This could indicate an attempt to exfiltrate data from S3 buckets by an unauthorized entity or compromised credential.
Detects suspicious access to multiple Azure Storage Accounts using a Shared Access Signature (SAS) token from a single external IP address. This pattern can indicate the use of a compromised, potentially overly permissive, SAS token for reconnaissance or lateral movement.
Detects access or search activity in SharePoint or OneDrive involving keywords related to gift cards, IT workflows, and remote access. This is a reconnaissance technique used by the Jingle Thief group (also tracked as Atlas Lion and STORM-0539) to find sensitive internal documentation.
This rule detects attempts to access non-existent AWS S3 buckets, indicated by the 'NoSuchBucket' error code in CloudTrail logs. This could signify reconnaissance activities by an attacker attempting to enumerate accessible S3 buckets or misconfigurations in applications trying to access buckets that no longer exist or have incorrect names. The rule extracts the bucket name and host from the request parameters for further investigation.
Detects potential data exfiltration from cloud storage or SaaS platforms based on a large volume of data transferred or a high number of distinct files accessed by a single user or application within a one-hour window. This is a common TTP for threat actors like ShinyHunters who aim to steal large datasets.
This rule detects potential enumeration of AWS S3 buckets by looking for the 'ListBuckets' API call in AWS CloudTrail logs. It specifically filters out activities performed by 'AssumedRole' identities to reduce false positives from legitimate automated processes or services.
Detects a single S3 object download event where the volume of data transferred exceeds a defined threshold. This can be an indicator of bulk data exfiltration. Attackers may download large archives or databases from compromised S3 buckets.
Looks for potential enumeration of AWS buckets via ListBuckets.
KQL Query
KQL Query from file: Azure Cloud Security Monitoring
KQL Query from file: Azure Storage Blob - Misconfiguration Check
KQL Query from file: AWS NoSuchBucket Check
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
'This query identifies attackers trying to enumerate the Storage keys as well as updating roles using AzureActivity,SigninLogs
and AuditLogs'
and AuditLogs'
"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 - Dropbox
The following analytic detects Google Drive or Google Docs files shared externally from an internal domain. It leverages GSuite Drive logs, extracting and comparing the source and destination email domains to identify external sharing. This activity is significant as it may indicate potential data exfiltration by an attacker or insider. If confirmed malicious, this could lead to unauthorized access to sensitive information, data leakage, and potential compliance violations. Monitoring this behavior helps in early detection and mitigation of data breaches.
'Looks for file uploads actions to Azure File and Blob Storage from known VPS provider network ranges.
This is not an exhaustive list of VPS provider ranges but covers some of the most prevalent providers observed.'
This is not an exhaustive list of VPS provider ranges but covers some of the most prevalent providers observed.'
'This hunting query will try to identify instances where a file us uploaded to file storage and then deleted
within a given threshold. By default the query will find instances where a file is uploaded and deleted within
5 minutes. This hunting query will help detect automated exfiltration.'
within a given threshold. By default the query will find instances where a file is uploaded and deleted within
5 minutes. This hunting query will help detect automated exfiltration.'
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