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Technique ID: T1080
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Name: Taint Shared Content
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Description: Adversaries may deliver payloads to remote systems by adding content to shared storage locations, such as network drives or internal code repositories. Content stored on network drives or in other shared locations may be tainted by adding malicious programs, scripts, or exploit code to otherwise valid files. Once a user opens the shared tainted content, the malicious portion can be executed to run the adversary's code on a remote system. Adversaries may use tainted shared content to move laterally. A directory share pivot is a variation on this technique that uses several other techniques to propagate malware when users access a shared network directory. It uses Shortcut Modification of directory .LNK files that use Masquerading to look like the real directories, which are hidden through Hidden Files and Directories. The malicious .LNK-based directories have an embedded command that executes the hidden malware file in the directory and then opens the real intended directory so that the user's expected action still occurs. When used with frequently used network directories, the technique may result in frequent reinfections and broad access to systems and potentially to new and higher privileged accounts. Adversaries may also compromise shared network directories through binary infections by appending or prepending its code to the healthy binary on the shared network directory. The malware may modify the original entry point (OEP) of the healthy binary to ensure that it is executed before the legitimate code. The infection could continue to spread via the newly infected file when it is executed by a remote system. These infections may target both binary and non-binary formats that end with extensions including, but not limited to, .EXE, .DLL, .SCR, .BAT, and/or .VBS.
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Tactics: Lateral Movement
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Platforms Affected: Linux, Office 365, SaaS, Windows, macOS
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Detection Strategies: Processes that write or overwrite many files to a network shared directory may be suspicious. Monitor processes that are executed from removable media for malicious or abnormal activity such as network connections due to Command and Control and possible network Discovery techniques. Frequently scan shared network directories for malicious files, hidden files, .LNK files, and other file types that may not typical exist in directories used to share specific types of content.
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More Information: https://attack.mitre.org/techniques/T1080
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Technique ID: T1119
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Name: Automated Collection
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Description: Once established within a system or network, an adversary may use automated techniques for collecting internal data. Methods for performing this technique could include use of a Command and Scripting Interpreter to search for and copy information fitting set criteria such as file type, location, or name at specific time intervals. In cloud-based environments, adversaries may also use cloud APIs, command line interfaces, or extract, transform, and load (ETL) services to automatically collect data. This functionality could also be built into remote access tools. This technique may incorporate use of other techniques such as File and Directory Discovery and Lateral Tool Transfer to identify and move files, as well as Cloud Service Dashboard and Cloud Storage Object Discovery to identify resources in cloud environments.
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Tactics: Collection
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Platforms Affected: IaaS, Linux, SaaS, Windows, macOS
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Detection Strategies: Depending on the method used, actions could include common file system commands and parameters on the command-line interface within batch files or scripts. A sequence of actions like this may be unusual, depending on the system and network environment. Automated collection may occur along with other techniques such as Data Staged. As such, file access monitoring that shows an unusual process performing sequential file opens and potentially copy actions to another location on the file system for many files at once may indicate automated collection behavior. Remote access tools with built-in features may interact directly with the Windows API to gather data. Data may also be acquired through Windows system management tools such as Windows Management Instrumentation and PowerShell, as well as through cloud APIs and command line interfaces.
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More Information: https://attack.mitre.org/techniques/T1119
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Technique ID: T1074
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Name: Data Staged
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Description: 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.
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Tactics: Collection
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Platforms Affected: IaaS, Linux, Windows, macOS
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Detection Strategies: 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.
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More Information: https://attack.mitre.org/techniques/T1074
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Technique ID: T1074.002
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Name: Data Staged: Remote Data Staging
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Description: 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.
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Tactics: Collection
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Platforms Affected: IaaS, Linux, Windows, macOS
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Detection Strategies: 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.
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More Information: https://attack.mitre.org/techniques/T1074/002
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Technique ID: T1530
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Name: Data from Cloud Storage
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Description: 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.
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Tactics: Collection
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Platforms Affected: Google Workspace, IaaS, Office 365, SaaS
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Detection Strategies: 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.
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More Information: https://attack.mitre.org/techniques/T1530
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Technique ID: T1213
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Name: Data from Information Repositories
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Description: 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.
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Tactics: Collection
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Platforms Affected: Google Workspace, IaaS, Linux, Office 365, SaaS, Windows, macOS
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Detection Strategies: 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.
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More Information: https://attack.mitre.org/techniques/T1213
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Technique ID: T1213.003
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Name: Data from Information Repositories: Code Repositories
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Description: 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.
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Tactics: Collection
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Platforms Affected: SaaS
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Detection Strategies: 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.
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More Information: https://attack.mitre.org/techniques/T1213/003
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Technique ID: T1213.001
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Name: Data from Information Repositories: Confluence
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Description: 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
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Tactics: Collection
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Platforms Affected: SaaS
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Detection Strategies: 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.
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More Information: https://attack.mitre.org/techniques/T1213/001
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Technique ID: T1213.002
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Name: Data from Information Repositories: Sharepoint
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Description: 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
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Tactics: Collection
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Platforms Affected: Office 365, Windows
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Detection Strategies: 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.
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More Information: https://attack.mitre.org/techniques/T1213/002
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Technique ID: T1114
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Name: Email Collection
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Description: 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.
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Tactics: Collection
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Platforms Affected: Google Workspace, Linux, Office 365, Windows, macOS
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Detection Strategies: 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.
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More Information: https://attack.mitre.org/techniques/T1114
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Technique ID: T1114.003
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Name: Email Collection: Email Forwarding Rule
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Description: Adversaries may setup email forwarding rules to collect sensitive information. Adversaries may abuse email forwarding rules to monitor the activities of a victim, steal information, and further gain intelligence on the victim or the victim’s organization to use as part of further exploits or operations. Furthermore, email forwarding rules can allow adversaries to maintain persistent access to victim's emails even after compromised credentials are reset by administrators. Most email clients allow users to create inbox rules for various email functions, including forwarding to a different recipient. These rules may be created through a local email application, a web interface, or by command-line interface. Messages can be forwarded to internal or external recipients, and there are no restrictions limiting the extent of this rule. Administrators may also create forwarding rules for user accounts with the same considerations and outcomes. Any user or administrator within the organization (or adversary with valid credentials) can create rules to automatically forward all received messages to another recipient, forward emails to different locations based on the sender, and more. Adversaries may also hide the rule by making use of the Microsoft Messaging API (MAPI) to modify the rule properties, making it hidden and not visible from Outlook, OWA or most Exchange Administration tools. In some environments, administrators may be able to enable email forwarding rules that operate organization-wide rather than on individual inboxes. For example, Microsoft Exchange supports transport rules that evaluate all mail an organization receives against user-specified conditions, then performs a user-specified action on mail that adheres to those conditions. Adversaries that abuse such features may be able to enable forwarding on all or specific mail an organization receives.
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Tactics: Collection
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Platforms Affected: Google Workspace, Linux, Office 365, Windows, macOS
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Detection Strategies: 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. This is especially true in cases with hidden auto-forwarding rules. This makes it only possible to reliably detect the existence of a hidden auto-forwarding rule by examining message tracking logs or by using a MAPI editor to notice the modified rule property values. 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.
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More Information: https://attack.mitre.org/techniques/T1114/003
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