voyagar/mitre_cit_v14 huggingface dataset:
T1074: Data Staged
Tactics: Collection
Platforms: IaaS, Linux, Windows, macOS

Adversaries may stage collected data in a central location or directory prior to Exfiltration. Data may be kept in separate files or combined into one file through techniques such as Archive Collected Data. Interactive command shells may be used, and common functionality within cmd and bash may be used to copy data into a staging location. In cloud environments, adversaries may stage data within a particular instance or virtual machine before exfiltration. An adversary may Create Cloud Instance and stage data in that instance. Adversaries may choose to stage data from a victim network in a centralized location prior to Exfiltration to minimize the number of connections made to their C2 server and better evade detection.

Detection: Processes that appear to be reading files from disparate locations and writing them to the same directory or file may be an indication of data being staged, especially if they are suspected of performing encryption or compression on the files, such as 7zip, RAR, ZIP, or zlib. Monitor publicly writeable directories, central locations, and commonly used staging directories (recycle bin, temp folders, etc.) to regularly check for compressed or encrypted data that may be indicative of staging. Monitor processes and command-line arguments for actions that could be taken to collect and combine files. Remote access tools with built-in features may interact directly with the Windows API to gather and copy to a location. Data may also be acquired and staged through Windows system management tools such as Windows Management Instrumentation and PowerShell. Consider monitoring accesses and modifications to storage repositories (such as the Windows Registry), especially from suspicious processes that could be related to malicious data collection.
Data sources: Command: Command Execution, File: File Access, File: File Creation, Windows Registry: Windows Registry Key Modification
T1074.002: Data Staged: Remote Data Staging
Tactics: Collection
Platforms: IaaS, Linux, Windows, macOS
Sub-technique of: T1074

Adversaries may stage data collected from multiple systems in a central location or directory on one system prior to Exfiltration. Data may be kept in separate files or combined into one file through techniques such as Archive Collected Data. Interactive command shells may be used, and common functionality within cmd and bash may be used to copy data into a staging location. In cloud environments, adversaries may stage data within a particular instance or virtual machine before exfiltration. An adversary may Create Cloud Instance and stage data in that instance. By staging data on one system prior to Exfiltration, adversaries can minimize the number of connections made to their C2 server and better evade detection.

Detection: Processes that appear to be reading files from disparate locations and writing them to the same directory or file may be an indication of data being staged, especially if they are suspected of performing encryption or compression on the files, such as 7zip, RAR, ZIP, or zlib. Monitor publicly writeable directories, central locations, and commonly used staging directories (recycle bin, temp folders, etc.) to regularly check for compressed or encrypted data that may be indicative of staging. Monitor processes and command-line arguments for actions that could be taken to collect and combine files. Remote access tools with built-in features may interact directly with the Windows API to gather and copy to a location. Data may also be acquired and staged through Windows system management tools such as Windows Management Instrumentation and PowerShell.
Data sources: Command: Command Execution, File: File Access, File: File Creation
T1530: Data from Cloud Storage
Tactics: Collection
Platforms: Google Workspace, IaaS, Office 365, SaaS

Adversaries may access data from cloud storage. Many IaaS providers offer solutions for online data object storage such as Amazon S3, Azure Storage, and Google Cloud Storage. Similarly, SaaS enterprise platforms such as Office 365 and Google Workspace provide cloud-based document storage to users through services such as OneDrive and Google Drive, while SaaS application providers such as Slack, Confluence, Salesforce, and Dropbox may provide cloud storage solutions as a peripheral or primary use case of their platform. In some cases, as with IaaS-based cloud storage, there exists no overarching application (such as SQL or Elasticsearch) with which to interact with the stored objects: instead, data from these solutions is retrieved directly though the Cloud API. In SaaS applications, adversaries may be able to collect this data directly from APIs or backend cloud storage objects, rather than through their front-end application or interface (i.e., Data from Information Repositories). Adversaries may collect sensitive data from these cloud storage solutions. Providers typically offer security guides to help end users configure systems, though misconfigurations are a common problem. There have been numerous incidents where cloud storage has been improperly secured, typically by unintentionally allowing public access to unauthenticated users, overly-broad access by all users, or even access for any anonymous person outside the control of the Identity Access Management system without even needing basic user permissions. This open access may expose various types of sensitive data, such as credit cards, personally identifiable information, or medical records. Adversaries may also obtain then abuse leaked credentials from source repositories, logs, or other means as a way to gain access to cloud storage objects.

Detection: Monitor for unusual queries to the cloud provider's storage service. Activity originating from unexpected sources may indicate improper permissions are set that is allowing access to data. Additionally, detecting failed attempts by a user for a certain object, followed by escalation of privileges by the same user, and access to the same object may be an indication of suspicious activity.
Data sources: Cloud Storage: Cloud Storage Access
T1213: Data from Information Repositories
Tactics: Collection
Platforms: Google Workspace, IaaS, Linux, Office 365, SaaS, Windows, macOS

Adversaries may leverage information repositories to mine valuable information. Information repositories are tools that allow for storage of information, typically to facilitate collaboration or information sharing between users, and can store a wide variety of data that may aid adversaries in further objectives, or direct access to the target information. Adversaries may also abuse external sharing features to share sensitive documents with recipients outside of the organization. The following is a brief list of example information that may hold potential value to an adversary and may also be found on an information repository:  Policies, procedures, and standards  Physical / logical network diagrams  System architecture diagrams  Technical system documentation  Testing / development credentials  Work / project schedules  Source code snippets  Links to network shares and other internal resources Information stored in a repository may vary based on the specific instance or environment. Specific common information repositories include web-based platforms such as Sharepoint and Confluence, specific services such as Code Repositories, IaaS databases, enterprise databases, and other storage infrastructure such as SQL Server.

Detection: As information repositories generally have a considerably large user base, detection of malicious use can be non-trivial. At minimum, access to information repositories performed by privileged users (for example, Active Directory Domain, Enterprise, or Schema Administrators) should be closely monitored and alerted upon, as these types of accounts should generally not be used to access information repositories. If the capability exists, it may be of value to monitor and alert on users that are retrieving and viewing a large number of documents and pages; this behavior may be indicative of programmatic means being used to retrieve all data within the repository. In environments with high-maturity, it may be possible to leverage User-Behavioral Analytics (UBA) platforms to detect and alert on user based anomalies. The user access logging within Microsoft's SharePoint can be configured to report access to certain pages and documents. Sharepoint audit logging can also be configured to report when a user shares a resource. The user access logging within Atlassian's Confluence can also be configured to report access to certain pages and documents through AccessLogFilter. Additional log storage and analysis infrastructure will likely be required for more robust detection capabilities.
Data sources: Application Log: Application Log Content, Logon Session: Logon Session Creation
T1213.003: Data from Information Repositories: Code Repositories
Tactics: Collection
Platforms: SaaS
Sub-technique of: T1213

Adversaries may leverage code repositories to collect valuable information. Code repositories are tools/services that store source code and automate software builds. They may be hosted internally or privately on third party sites such as Github, GitLab, SourceForge, and BitBucket. Users typically interact with code repositories through a web application or command-line utilities such as git. Once adversaries gain access to a victim network or a private code repository, they may collect sensitive information such as proprietary source code or credentials contained within software's source code. Having access to software's source code may allow adversaries to develop Exploits, while credentials may provide access to additional resources using Valid Accounts. Note: This is distinct from Code Repositories, which focuses on conducting Reconnaissance via public code repositories.

Detection: Monitor access to code repositories, especially performed by privileged users such as Active Directory Domain or Enterprise Administrators as these types of accounts should generally not be used to access code repositories. In environments with high-maturity, it may be possible to leverage User-Behavioral Analytics (UBA) platforms to detect and alert on user-based anomalies.
Data sources: Application Log: Application Log Content, Logon Session: Logon Session Creation
T1213.001: Data from Information Repositories: Confluence
Tactics: Collection
Platforms: SaaS
Sub-technique of: T1213

Adversaries may leverage Confluence repositories to mine valuable information. Often found in development environments alongside Atlassian JIRA, Confluence is generally used to store development-related documentation, however, in general may contain more diverse categories of useful information, such as:  Policies, procedures, and standards  Physical / logical network diagrams  System architecture diagrams  Technical system documentation  Testing / development credentials  Work / project schedules  Source code snippets  Links to network shares and other internal resources

Detection: Monitor access to Confluence repositories performed by privileged users (for example, Active Directory Domain, Enterprise, or Schema Administrators) as these types of accounts should generally not be used to access information repositories. If the capability exists, it may be of value to monitor and alert on users that are retrieving and viewing a large number of documents and pages; this behavior may be indicative of programmatic means being used to retrieve all data within the repository. In environments with high-maturity, it may be possible to leverage User-Behavioral Analytics (UBA) platforms to detect and alert on user based anomalies. User access logging within Atlassian's Confluence can be configured to report access to certain pages and documents through AccessLogFilter. Additional log storage and analysis infrastructure will likely be required for more robust detection capabilities.
Data sources: Application Log: Application Log Content, Logon Session: Logon Session Creation
T1213.002: Data from Information Repositories: Sharepoint
Tactics: Collection
Platforms: Office 365, Windows
Sub-technique of: T1213

Adversaries may leverage the SharePoint repository as a source to mine valuable information. SharePoint will often contain useful information for an adversary to learn about the structure and functionality of the internal network and systems. For example, the following is a list of example information that may hold potential value to an adversary and may also be found on SharePoint:  Policies, procedures, and standards  Physical / logical network diagrams  System architecture diagrams  Technical system documentation  Testing / development credentials  Work / project schedules  Source code snippets  Links to network shares and other internal resources

Detection: The user access logging within Microsoft's SharePoint can be configured to report access to certain pages and documents. . As information repositories generally have a considerably large user base, detection of malicious use can be non-trivial. At minimum, access to information repositories performed by privileged users (for example, Active Directory Domain, Enterprise, or Schema Administrators) should be closely monitored and alerted upon, as these types of accounts should generally not be used to access information repositories. If the capability exists, it may be of value to monitor and alert on users that are retrieving and viewing a large number of documents and pages; this behavior may be indicative of programmatic means being used to retrieve all data within the repository. In environments with high-maturity, it may be possible to leverage User-Behavioral Analytics (UBA) platforms to detect and alert on user based anomalies.
Data sources: Application Log: Application Log Content, Logon Session: Logon Session Creation
T1114: Email Collection
Tactics: Collection
Platforms: Google Workspace, Linux, Office 365, Windows, macOS

Adversaries may target user email to collect sensitive information. Emails may contain sensitive data, including trade secrets or personal information, that can prove valuable to adversaries. Adversaries can collect or forward email from mail servers or clients.

Detection: There are likely a variety of ways an adversary could collect email from a target, each with a different mechanism for detection. File access of local system email files for Exfiltration, unusual processes connecting to an email server within a network, or unusual access patterns or authentication attempts on a public-facing webmail server may all be indicators of malicious activity. Monitor processes and command-line arguments for actions that could be taken to gather local email files. Remote access tools with built-in features may interact directly with the Windows API to gather information. Information may also be acquired through Windows system management tools such as Windows Management Instrumentation and PowerShell. Detection is challenging because all messages forwarded because of an auto-forwarding rule have the same presentation as a manually forwarded message. It is also possible for the user to not be aware of the addition of such an auto-forwarding rule and not suspect that their account has been compromised; email-forwarding rules alone will not affect the normal usage patterns or operations of the email account. Auto-forwarded messages generally contain specific detectable artifacts that may be present in the header; such artifacts would be platform-specific. Examples include X-MS-Exchange-Organization-AutoForwarded set to true, X-MailFwdBy and X-Forwarded-To. The forwardingSMTPAddress parameter used in a forwarding process that is managed by administrators and not by user actions. All messages for the mailbox are forwarded to the specified SMTP address. However, unlike typical client-side rules, the message does not appear as forwarded in the mailbox; it appears as if it were sent directly to the specified destination mailbox. High volumes of emails that bear the X-MS-Exchange-Organization-AutoForwarded header (indicating auto-forwarding) without a corresponding number of emails that match the appearance of a forwarded message may indicate that further investigation is needed at the administrator level rather than user-level.
Data sources: Application Log: Application Log Content, Command: Command Execution, File: File Access, Logon Session: Logon Session Creation, Network Traffic: Network Connection Creation
T1114.002: Email Collection: Remote Email Collection
Tactics: Collection
Platforms: Google Workspace, Office 365, Windows
Sub-technique of: T1114

Adversaries may target an Exchange server, Office 365, or Google Workspace to collect sensitive information. Adversaries may leverage a user's credentials and interact directly with the Exchange server to acquire information from within a network. Adversaries may also access externally facing Exchange services, Office 365, or Google Workspace to access email using credentials or access tokens. Tools such as MailSniper can be used to automate searches for specific keywords.

Detection: Monitor for unusual login activity from unknown or abnormal locations, especially for privileged accounts (ex: Exchange administrator account).
Data sources: Application Log: Application Log Content, Command: Command Execution, Logon Session: Logon Session Creation, Network Traffic: Network Connection Creation
T1048: Exfiltration Over Alternative Protocol
Tactics: Exfiltration
Platforms: Google Workspace, IaaS, Linux, Network, Office 365, SaaS, Windows, macOS

Adversaries may steal data by exfiltrating it over a different protocol than that of the existing command and control channel. The data may also be sent to an alternate network location from the main command and control server. Alternate protocols include FTP, SMTP, HTTP/S, DNS, SMB, or any other network protocol not being used as the main command and control channel. Adversaries may also opt to encrypt and/or obfuscate these alternate channels. Exfiltration Over Alternative Protocol can be done using various common operating system utilities such as Net/SMB or FTP. On macOS and Linux curl may be used to invoke protocols such as HTTP/S or FTP/S to exfiltrate data from a system. Many IaaS and SaaS platforms (such as Microsoft Exchange, Microsoft SharePoint, GitHub, and AWS S3) support the direct download of files, emails, source code, and other sensitive information via the web console or Cloud API.

Detection: Analyze network data for uncommon data flows (e.g., a client sending significantly more data than it receives from a server). Processes utilizing the network that do not normally have network communication or have never been seen before are suspicious. Analyze packet contents to detect communications that do not follow the expected protocol behavior for the port that is being used.
Data sources: Application Log: Application Log Content, Cloud Storage: Cloud Storage Access, Command: Command Execution, File: File Access, Network Traffic: Network Connection Creation, Network Traffic: Network Traffic Content, Network Traffic: Network Traffic Flow
T1567: Exfiltration Over Web Service
Tactics: Exfiltration
Platforms: Google Workspace, Linux, Office 365, SaaS, Windows, macOS

Adversaries may use an existing, legitimate external Web service to exfiltrate data rather than their primary command and control channel. Popular Web services acting as an exfiltration mechanism may give a significant amount of cover due to the likelihood that hosts within a network are already communicating with them prior to compromise. Firewall rules may also already exist to permit traffic to these services. Web service providers also commonly use SSL/TLS encryption, giving adversaries an added level of protection.

Detection: Analyze network data for uncommon data flows (e.g., a client sending significantly more data than it receives from a server). Processes utilizing the network that do not normally have network communication or have never been seen before are suspicious. User behavior monitoring may help to detect abnormal patterns of activity.
Data sources: Application Log: Application Log Content, Command: Command Execution, File: File Access, Network Traffic: Network Connection Creation, Network Traffic: Network Traffic Content, Network Traffic: Network Traffic Flow
T1567.004: Exfiltration Over Web Service: Exfiltration Over Webhook
Tactics: Exfiltration
Platforms: Google Workspace, Linux, Office 365, SaaS, Windows, macOS
Sub-technique of: T1567

Adversaries may exfiltrate data to a webhook endpoint rather than over their primary command and control channel. Webhooks are simple mechanisms for allowing a server to push data over HTTP/S to a client without the need for the client to continuously poll the server. Many public and commercial services, such as Discord, Slack, and `webhook.site`, support the creation of webhook endpoints that can be used by other services, such as Github, Jira, or Trello. When changes happen in the linked services (such as pushing a repository update or modifying a ticket), these services will automatically post the data to the webhook endpoint for use by the consuming application. Adversaries may link an adversary-owned environment to a victim-owned SaaS service to achieve repeated Automated Exfiltration of emails, chat messages, and other data. Alternatively, instead of linking the webhook endpoint to a service, an adversary can manually post staged data directly to the URL in order to exfiltrate it. Access to webhook endpoints is often over HTTPS, which gives the adversary an additional level of protection. Exfiltration leveraging webhooks can also blend in with normal network traffic if the webhook endpoint points to a commonly used SaaS application or collaboration service.

Detection: No detection description provided.
Data sources: Application Log: Application Log Content, Command: Command Execution, File: File Access, Network Traffic: Network Traffic Content, Network Traffic: Network Traffic Flow
T1537: Transfer Data to Cloud Account
Tactics: Exfiltration
Platforms: IaaS

Adversaries may exfiltrate data by transferring the data, including backups of cloud environments, to another cloud account they control on the same service to avoid typical file transfers/downloads and network-based exfiltration detection. A defender who is monitoring for large transfers to outside the cloud environment through normal file transfers or over command and control channels may not be watching for data transfers to another account within the same cloud provider. Such transfers may utilize existing cloud provider APIs and the internal address space of the cloud provider to blend into normal traffic or avoid data transfers over external network interfaces. Incidents have been observed where adversaries have created backups of cloud instances and transferred them to separate accounts.

Detection: Monitor account activity for attempts to share data, snapshots, or backups with untrusted or unusual accounts on the same cloud service provider. Monitor for anomalous file transfer activity between accounts and to untrusted VPCs. In AWS, sharing an Elastic Block Store (EBS) snapshot, either with specified users or publicly, generates a ModifySnapshotAttribute event in CloudTrail logs. Similarly, in Azure, creating a Shared Access Signature (SAS) URI for a Virtual Hard Disk (VHS) snapshot generates a "Get Snapshot SAS URL" event in Activity Logs.
Data sources: Cloud Storage: Cloud Storage Creation, Cloud Storage: Cloud Storage Metadata, Cloud Storage: Cloud Storage Modification, Network Traffic: Network Traffic Content, Snapshot: Snapshot Creation, Snapshot: Snapshot Metadata, Snapshot: Snapshot Modification