Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
150 detections
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This rule detects an unusually high volume of file sharing events from a single user in OneDrive within a one-hour window. Specifically, it looks for five or more 'SharingSet' or 'AnonymousLinkCreated' operations by the same UserId within an hour, which could indicate data exfiltration or unauthorized sharing.
This rule detects when a single process account initiates a high volume (10 or more) of file move operations to folders associated with cloud storage services (e.g., 'cloud', 'dropbox', 'drive') within a one-hour window. This behavior could indicate data exfiltration or staging for exfiltration.
Detects unusually large outbound network data transfers (over 1TB) from a single process account within an hour. This could indicate data exfiltration, unauthorized bulk data synchronization, or other malicious activity where large volumes of data are being moved out of the environment.
Detects unusually large outbound network data transfers (over 1TB) from a single process account within an hour. This could indicate data exfiltration, unauthorized bulk data synchronization, or other malicious activity where large volumes of data are being moved out of the environment.
This rule detects when a single process account initiates a high volume (10 or more) of file move operations to folders associated with cloud storage services (e.g., 'cloud', 'dropbox', 'drive') within a one-hour window. This behavior could indicate data exfiltration or staging for exfiltration.
This rule detects large HTTP PUT requests (over 50KB) directed towards common cloud storage services (Amazon S3, Azure Blob Storage, Google Cloud Storage). This activity could indicate data exfiltration to an external cloud account.
This rule detects HTTP PUT requests to s3.amazonaws.com that include the 'x-amz-copy-source' header and have a data size greater than 1000 bytes. This combination of indicators suggests an attempt to copy data from one S3 bucket to another, potentially indicating data exfiltration to an attacker-controlled AWS account.
https://www.microsoft.com/en-us/security/blog/2026/04/18/crosstenant-helpdesk-impersonation-data-exfiltration-human-operated-intrusion-playbook/
This rule detects the exposure of Kuwaiti Civil ID numbers in various log sources, including process command lines, additional device event fields, and email subjects/sender addresses. A Kuwaiti Civil ID is identified by a 12-digit number starting with 1, 2, or 3.
This rule detects the exposure of Kuwaiti Civil ID numbers in various log sources, including process command lines, additional device event fields, and email subjects/sender addresses. A Kuwaiti Civil ID is identified by a 12-digit number starting with 1, 2, or 3.
Detects emails where the subject line contains a 13-16 digit number, potentially indicating sensitive numerical patterns like a Credit Card. The rule looks for contiguous digits or common dashed/spaced credit card formats and filters out common automated email keywords to reduce false positives.
Detects emails where the subject line contains a 13-16 digit number, potentially indicating sensitive numerical patterns like a Credit Card. The rule looks for contiguous digits or common dashed/spaced credit card formats and filters out common automated email keywords to reduce false positives.
Detects the execution of S3 Browser or Office installation executables, followed by network traffic from the same host to known cloud storage or file-sharing sites within a short time window. This behavior aligns with Muddled Libra's method of staging and exfiltrating sensitive data, such as PST files, to attacker-controlled cloud buckets.
Detects specific log messages written to the iOS Unified Log by the DarkSword implant (GHOSTBLADE). These messages, which include tags like '[DarkSword-WIFI-DUMP]' and '[MAIN]', are unique to the malware and indicate that the data exfiltration modules are running. The GHOSTBLADE implant, used by UNC6353 in the DarkSword campaign, leaves distinct and high-confidence log messages in iOS Unified Logs during its operation. These logs are a clear indicator of a successful compromise.
KQL Query
This rule is meant to help analysts quickly spot a high-confidence indicator related to Google ShinyHunters SaaS Defense Guidance. It is written to be easy to understand and to keep false alarms low by focusing on a very specific match: AWS CLI performing S3 sync or copy commands that can be used for bulk export. A match does not automatically prove an attacker is currently active, and it does not prove a file was executed, but it does mean the event is important because it lines up with a public threat intelligence source. When this triggers, start by identifying the host, user, and timeframe involved, then decide whether the activity is expected for that system. If it is unexpected, preserve the related logs and any files, and look for nearby events that could explain how the indicator appeared, such as a download, a new process, or a new connection. If the same indicator appears on multiple systems, treat it as a scoping signal and expand the investigation window. Use the reference link (https://cloud.google.com/blog/topics/threat- intelligence/defense-against-shinyhunters-cybercrime-saas) to document where the indicator came from and to support incident notes and reporting.
Detects programmatic GitHub data exfiltration by identifying non-interactive repository exports, clones, artifact downloads, or gist staging performed using tokens, OAuth applications, or GitHub Apps. The detection focuses on bursty or multi-repository activity within a short time window, which can indicate automated source code collection, misuse of programmatic credentials, or post-compromise data extraction.
Detects the execution of S3 Browser or Office installation executables, followed by network traffic from the same host to known cloud storage or file-sharing sites within a short time window. This behavior aligns with Muddled Libra's method of staging and exfiltrating sensitive data, such as PST files, to attacker-controlled cloud buckets.
Detects large volumes of outbound data transfers using the Cyberduck application to known cloud storage providers. The Qilin ransomware group has been observed using Cyberduck for data exfiltration.
This rule detects the creation of a public GitHub repository with the specific description "Sha1-Hulud: The Second Coming". This is an indicator of compromise (IOC) associated with the Shai-Hulud 2.0 worm, which uses these repositories to exfiltrate stolen credentials.
This search detects the creation of a public GitHub repository with the description "Sha1-Hulud: The Second Coming". This is a specific indicator of compromise (IOC) associated with the Shai-Hulud 2.0 worm, which uses these repositories to exfiltrate stolen credentials.
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