Identifies the creation or modification of an S3 bucket replication configuration that sends data to a bucket in a different AWS account. Cross-account replication can be used legitimately for backup, disaster recovery, and multi-account architectures, but adversaries with write access to an S3 bucket may abuse replication rules to silently exfiltrate large volumes of data to attacker-controlled accounts. This rule detects "PutBucketReplication" events where the configured destination account differs from the source bucket's account, indicating potential unauthorized cross-account data movement.

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Detects the use of curl to upload files to an internet server. Threat actors often will collect and exfiltrate data on a system to their C2 server for review. Many threat actors have been observed using curl to upload the collected data. Use of curl in this way, while not inherently malicious, should be considered highly abnormal and suspicious activity.

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Claude artifacts can be shared with specific audiences. Making an artifact public exposes its contents to unauthenticated viewers on the internet. An attacker with access to sensitive artifacts can publish them publicly to push intellectual property, credentials embedded in prompts, or other confidential material outside organizational controls.

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Detects an unusually high number of successful Claude chat snapshot creation events for the same user email within a rolling 24-hour window. Chat snapshots package conversation content into shareable exports; sustained creation volume can indicate staging of organizational chat data for exfiltration via Anthropic's web service or automated bulk export of sensitive prompts and responses.

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Detects an unusually high volume of Claude file uploads from the same user email and source IP within a rolling 24-hour period. Sustained upload activity can indicate staging of sensitive documents in Claude chats for later retrieval, automated ingestion of data into LLM workflows, or abuse of organizational Claude access to move files into the cloud service.

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Starting an organization data export only signals intent. Accessing the export archive via its signed URL means the actor actually downloaded chats, projects, user metadata, and configuration. An attacker with administrative access can use this to exfiltrate intellectual property and credentials at scale.

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Identifies an AWS principal performing a high volume of Amazon Bedrock inference API calls against a single model within a short window. Membership inference attacks require hundreds to thousands of statistically similar queries whose prompts and responses are intentionally content-benign, making guardrail- and content-based rules ineffective. This rule detects the high-frequency single-model probing pattern that precedes membership inference and related exfiltration via the inference API. It is a behavioral / volumetric precursor: it does not observe model confidence scores and a fixed call-count threshold only catches the loud variant, so paced, low-and-slow, or credential-distributed probing will evade it. Definitive membership inference detection requires ML anomaly analysis over per-entity inference-rate and response-distribution baselines.

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Detects when GenAI processes perform encoding or chunking (base64, gzip, tar, zip) followed by outbound network activity. This sequence indicates data preparation for exfiltration. Attackers encode or compress sensitive data before transmission to obfuscate contents and evade detection. Legitimate GenAI workflows rarely encode data before network communications.

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Detects non-allowlisted curl activity on Linux, macOS, and Windows hosts and uses an LLM to assess whether the activity is malicious, benign, or requires investigation. The rule parses and normalizes the destination, redacts sensitive command-line values, and aggregates activity by host and destination before invoking the ES|QL COMPLETION command. Only true positive or suspicious verdicts with confidence above 0.7 generate alerts.

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Detects non-allowlisted curl activity on Linux hosts via Auditd Manager or Auditbeat and uses an LLM to assess whether the activity is malicious, benign, or requires investigation. The rule parses and normalizes the destination, redacts sensitive command-line values, and aggregates activity by host and destination before invoking the ES|QL COMPLETION command. Only true positive or suspicious verdicts with confidence above 0.7 generate alerts.

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Detects non-allowlisted wget activity on Linux, macOS, and Windows hosts and uses an LLM to assess whether the activity is malicious, benign, or requires investigation. The rule parses and normalizes the destination, redacts sensitive command-line values, and aggregates activity by host and destination before invoking the ES|QL COMPLETION command. Only true positive or suspicious verdicts with confidence above 0.7 generate alerts.

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Detects non-allowlisted wget activity on Linux hosts via Auditd Manager or Auditbeat and uses an LLM to assess whether the activity is malicious, benign, or requires investigation. The rule parses and normalizes the destination, redacts sensitive command-line values, and aggregates activity by host and destination before invoking the ES|QL COMPLETION command. Only true positive or suspicious verdicts with confidence above 0.7 generate alerts.

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Identifies execution of a third-party S3 or object-storage client (S3 Browser, s5cmd, s3cmd, MinIO mc, rclone, Cyberduck, s3fs, goofys, juicefs) launched by a script interpreter, a shell one-liner, or from a temporary or user-writable path. After stealing cloud credentials, adversaries switch from the AWS CLI to these clients to enumerate and drain buckets in bulk. Gating on a scripted context separates post-exploitation automation from interactive developer use.

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Identifies DNS query patterns associated with tunneling, including rare NULL queries, repeated TXT queries with unusually long names, and clients generating many unique, long subdomains under one registered domain within a five-minute window.

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This rule detects network events that may indicate the use of Windows file sharing (also called SMB or CIFS) traffic to the Internet. SMB is commonly used within networks to share files, printers, and other system resources amongst trusted systems. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector or for data exfiltration.

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Identifies AWS API activity originating from uncommon desktop client applications based on the user agent string. This rule detects S3 Browser and Cyberduck, which are graphical S3 management tools that provide bulk upload/download capabilities. While legitimate, these tools are rarely used in enterprise environments and have been observed in use by threat actors for data exfiltration. Any activity from these clients should be validated against authorized data transfer workflows.

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Identifies when an AWS DynamoDB table is scanned by a user who does not typically perform this action. Adversaries may use the Scan operation to collect sensitive information or exfiltrate data from DynamoDB tables. This rule detects unusual user activity by monitoring for the Scan action in CloudTrail logs. This is a New Terms rule that only flags when this behavior is observed by a user or role for the first time.

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Identifies when an AWS DynamoDB table is exported to S3. Adversaries may use the ExportTableToPointInTime operation to collect sensitive information or exfiltrate data from DynamoDB tables. This rule detects unusual user activity by monitoring for the ExportTableToPointInTime action in CloudTrail logs. This is a New Terms rule that only flags when this behavior is observed by a user or role for the first time.

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Identifies an AWS Amazon Machine Image (AMI) being shared with another AWS account. Adversaries with access may share an AMI with an external AWS account as a means of data exfiltration. AMIs can contain secrets, bash histories, code artifacts, and other sensitive data that adversaries may abuse if shared with unauthorized accounts. AMIs can be made publicly available accidentally as well.

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Detects when an Amazon Elastic Block Store (EBS) snapshot is shared with another AWS account or made public. EBS snapshots contain copies of data volumes that may include sensitive or regulated information. Adversaries may exploit ModifySnapshotAttribute to share snapshots with external accounts or the public, allowing them to copy and access data in an environment they control. This activity often precedes data exfiltration or persistence operations, where the attacker transfers stolen data out of the victim account or prepares a staging area for further exploitation.

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Identifies successful export tasks of EC2 instances via the APIs CreateInstanceExportTask, ExportImage, or CreateStoreImageTask. These exports can be used by administrators for legitimate VM migration or backup workflows however, an attacker with access to an EC2 instance or AWS credentials can export a VM or its image and then transfer it off-account for exfiltration of data.

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Detects successful creation of an Amazon EC2 Traffic Mirroring session. A session copies full packets from a source Elastic Network Interface (ENI) to a mirror target (e.g., an ENI or NLB) using a mirror filter (ingress/egress rules). While used for diagnostics and NDR/IDS tooling, adversaries can abuse sessions to covertly capture and exfiltrate sensitive, potentially unencrypted, traffic from instances or subnets.

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Detects when an Amazon ECR repository or registry policy is modified to grant public access using a wildcard principal (Principal:"") statement. This rule analyzes SetRepositoryPolicy and PutRegistryPolicy events whose policy document grants an Allow effect to a wildcard ("") principal, indicating that pull (and potentially push) permissions were extended to all identities, including unauthenticated users. A public container registry can expose proprietary images and any secrets baked into their layers, and, if push is allowed, enables supply-chain implantation. Public ECR access is sometimes intentional for image distribution, so the granting principal and the permissions should be validated.

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Identifies when an AWS RDS DB snapshot is shared with another AWS account or made public. DB snapshots contain complete backups of database instances, including schemas, table data, and sensitive application content. When shared externally, snapshots can be restored in another AWS environment, enabling unauthorized access, offline analysis, or data exfiltration. Adversaries who obtain valid credentials or exploit misconfigurations may modify snapshot attributes to grant access to accounts they control, bypassing network, IAM, and monitoring controls.

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Identifies the export of a DB snapshot or DB cluster data to Amazon S3. Snapshot exports can be used for analytics or migration workflows, but adversaries may abuse them to exfiltrate sensitive data outside of RDS-managed storage. Exporting a snapshot creates a portable copy of the database contents, which, if performed without authorization, can indicate data theft, staging for exfiltration, or operator misconfiguration that exposes regulated information.

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Detects when an Amazon S3 bucket policy is modified to grant public access using a wildcard (Principal:"") statement. This rule analyzes PutBucketPolicy events that include both Effect=Allow and Principal:"" in the request parameters, indicating that permissions were extended to all identities, potentially making the bucket or its contents publicly accessible. Publicly exposing an S3 bucket is one of the most common causes of sensitive data leaks in AWS environments. Adversaries or misconfigurations can leverage this exposure to exfiltrate data, host malicious content, or collect credentials and logs left in open storage.

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Detects when an Amazon S3 bucket policy is modified to share access with an external AWS account. This rule analyzes PutBucketPolicy events and compares the S3 bucket’s account ID to any account IDs referenced in the policy’s Effect=Allow statements. If the policy includes principals from accounts other than the bucket owner’s, the rule triggers an alert. This behavior may indicate an adversary backdooring a bucket for data exfiltration or cross-account persistence. For example, an attacker who compromises credentials could attach a policy allowing access from an external AWS account they control, enabling continued access even after credentials are rotated. Note: This rule will not alert if the account ID is part of the bucket’s name or appears in the resource ARN. Such cases are common in standardized naming conventions (e.g., “mybucket-123456789012”). To ensure full coverage, use complementary rules to monitor for suspicious PutBucketPolicy API requests targeting buckets with account IDs embedded in their names or resources.

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Identifies when a user subscribes to an SNS topic using a new protocol type (ie. email, http, lambda, etc.). SNS allows users to subscribe to recieve topic messages across a broad range of protocols like email, sms, lambda functions, http endpoints, and applications. Adversaries may subscribe to an SNS topic to collect sensitive information or exfiltrate data via an external email address, cross-account AWS service or other means. This rule identifies a new protocol subscription method for a particular user.

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Identifies when an SNS topic message is published by a rare user in AWS. Adversaries may publish messages to SNS topics for phishing campaigns, data exfiltration, or lateral movement within the AWS environment. SNS topics are used to send notifications and messages to subscribed endpoints such as applications, mobile devices or email addresses, making them a valuable target for adversaries to distribute malicious content or exfiltrate sensitive data. This is a New Terms rule that only flags when this behavior is observed for the first time by a user or role.

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Identifies the first time, in a historical window, a host runs AzCopy copy or sync to Azure Blob, Data Lake, or File storage, or starts Azure Storage Explorer. These Microsoft utilities are legitimate data-transfer tools; ransomware and cloud-ransomware operators drop portable copies and use SAS-authenticated jobs to pull data from victim storage and push it to attacker-controlled accounts.

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Identifies successful GetBlob operations on Azure Storage Accounts using AzCopy user agent with SAS token authentication. AzCopy is a command-line utility for copying data to and from Azure Storage. While legitimate for data migration, adversaries may abuse AzCopy with compromised SAS tokens to exfiltrate data from Azure Storage Accounts. This rule detects the first occurrence of GetBlob operations from a specific storage account using this pattern.

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This rule detects the execution of curl or wget binaries through a GTFOBin (living-off-the-land) technique in Linux environments. Attackers may exploit these utilities to download and execute malicious files from the internet while attempting to evade detection. The rule specifically targets binaries that are capable of executing shell commands directly from the proxied binary, rather than just spawning a shell.

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This rule leverages ESQL to detect the execution of unusual file transfer utilities on Linux systems. Attackers may use these utilities to exfiltrate data from a compromised system. ESQL rules have limited fields available in its alert documents. Make sure to review the original documents to aid in the investigation of this alert.

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Identifies newly seen removable devices by device friendly name using registry modification events. While this activity is not inherently malicious, analysts can use those events to aid monitoring for data exfiltration over those devices.

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Identifies a modification to a Logging sink in Google Cloud Platform (GCP). Logging compares the log entry to the sinks in that resource. Each sink whose filter matches the log entry writes a copy of the log entry to the sink's export destination. An adversary may update a Logging sink to exfiltrate logs to a different export destination.

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Detects a high number of repository cloning actions by a single user within a short time frame. Adversaries may clone multiple repositories to exfiltrate sensitive data.

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Detects when a private GitHub repository is changed to public visibility. Adversaries may change repository visibility to public in order to exfiltrate sensitive code or data, potentially indicating a compromise or unauthorized access.

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Detects when Google Workspace administrators initiate bulk movement or export of user Drive data. This includes admin data transfer requests that reassign a user's Drive files to another account, and Customer Takeout export jobs that package organizational data for download or off-platform transfer. Adversaries with administrative access may abuse these mechanisms to stage or exfiltrate sensitive files.

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Detects a high number of closed pull requests by a single user within a short time frame. Adversaries may close multiple pull requests to disrupt development workflows or hide malicious changes.

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Detects a high number of force push actions to protected branches by a single user within a short time frame. Adversaries may perform force pushes to overwrite commit history on protected branches, potentially leading to data loss or disruption of development workflows.

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Identifies a transport rule creation in Microsoft 365. As a best practice, Exchange Online mail transport rules should not be set to forward email to domains outside of your organization. An adversary may create transport rules to exfiltrate data.

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Identifies when a transport rule has been disabled or deleted in Microsoft 365. Mail flow rules (also known as transport rules) are used to identify and take action on messages that flow through your organization. An adversary or insider threat may modify a transport rule to exfiltrate data or evade defenses.

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Identifies when an excessive number of files are downloaded from OneDrive or SharePoint by an authorized user or application in a short period of time. This may indicate a potential data exfiltration event, especially if the downloads are performed using OAuth authentication which could suggest an OAuth phishing attack such as Device Code Authentication phishing.

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Identifies file downloads or access from OneDrive or SharePoint using PowerShell-based user agents. Adversaries may use native PowerShell cmdlets like Invoke-WebRequest or Invoke-RestMethod with Microsoft Graph API to exfiltrate data after compromising OAuth tokens via device code phishing or other credential theft techniques. This rule detects both direct PowerShell access and PnP PowerShell module usage for file operations. FileAccessed events are included to detect adversaries reading file content via API and saving locally, bypassing traditional download methods. Normal users access SharePoint/OneDrive via browsers or sync clients, making PowerShell-based file access inherently suspicious.

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Identifies newly seen removable devices by device.serial_number and host.id using the Elastic Defend device mount events. While this activity is not inherently malicious, analysts can use those events to aid monitoring for data exfiltration over those devices.

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A machine learning job has detected data exfiltration to a particular destination port. Data transfer patterns that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.

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A machine learning job has detected data exfiltration to a particular geo-location (by IP address). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.

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A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.

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A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.

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Detects the use of wget to upload files to an internet server. Threat actors often will collect data on a system and attempt to exfiltrate it back to their command and control servers. Use of wget in this way, while not inherently malicious, should be considered highly abnormal and suspicious activity.

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Identifies abuse of rclone (or a renamed copy, e.g. disguised as a security or backup utility) to exfiltrate data to cloud storage or remote endpoints. Rclone is a legitimate file sync tool; threat actors rename it to blend with administrative traffic and use copy/sync with cloud backends (e.g. :s3:) and include filters to exfiltrate specific file types.

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This rule looks for the usage of common data splitting utilities with specific arguments that indicate data splitting for exfiltration on Linux systems. Data splitting is a technique used by adversaries to split data into smaller parts to avoid detection and exfiltrate data.

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This rule detects the use of database dumping utilities to exfiltrate data from a database. Attackers may attempt to dump the database to a file on the system and then exfiltrate the file to a remote server.

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Identifies potential DNS exfiltration on Windows hosts by detecting a high volume of DNS queries whose subdomain labels follow a chunked encoding pattern (index-payload.base_domain). Attackers split stolen data across many DNS queries to evade volume-based detection; this rule aggregates queries per process, base domain, and five-minute window and flags sessions with many distinct chunk indices and sufficiently long encoded payloads.

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Identifies Certreq making an HTTP Post request. Adversaries could abuse Certreq to download files or upload data to a remote URL.

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This rule detects rare internet network connections via the SMB protocol. SMB is commonly used to leak NTLM credentials via rogue UNC path injection.

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Detects a high number of failed force push attempts to protected branches by a single user within a short time frame. Adversaries may attempt multiple force pushes to overwrite commit history on protected branches, potentially leading to data loss or disruption of development workflows.

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This rule detects events that may indicate use of SMTP on TCP port 26 from an internal host to an external destination. This port is commonly used by several popular mail transfer agents to deconflict with the default SMTP port 25. This port has also been used by a malware family called BadPatch for command and control of Windows systems. The rule is scoped to outbound traffic (internal source to external destination) to focus on the command and control and exfiltration use cases, rather than benign internal mail relays or unrelated transit traffic observed by the sensor.

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A machine learning job has detected high bytes of data written to an external device. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities.

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A machine learning job has detected high bytes of data written to an external device via Airdrop. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities.

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This rule detects unusual DNS queries to commonly abused top level domains. Malware authors may use these domains to host command and control infrastructure, exfiltrate data, or to download payloads for later execution.

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A machine learning job has detected a rare process writing data to an external device. Malicious actors often use benign-looking processes to mask their data exfiltration activities. The discovery of such a process that has no legitimate reason to write data to external devices can indicate exfiltration.

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Identifies an attempt to export an AWS EC2 instance. A virtual machine (VM) export may indicate an attempt to extract or exfiltrate information.

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An attempt was made to modify AWS EC2 snapshot attributes. Snapshots are sometimes shared by threat actors in order to exfiltrate bulk data from an EC2 fleet. If the permissions were modified, verify the snapshot was not shared with an unauthorized or unexpected AWS account.

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