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Исследование
The adversary is trying to figure out your environment.
Discovery consists of techniques an adversary may use to gain knowledge about the system and internal network. These techniques help adversaries observe the environment and orient themselves before deciding how to act. They also allow adversaries to explore what they can control and what’s around their entry point in order to discover how it could benefit their current objective. Native operating system tools are often used toward this post-compromise information-gathering objective.
ID: TA0007
Created: 2018-10-17 00:14:21.000000
Last Modified: 2019-07-19 17:44:13.000000
Techniques(31)
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| ID | Name | Description | |
| T1087 | Исследование учетных записей | Adversaries may attempt to get a listing of accounts on a system or within an environment. This information can help adversaries determine which accounts exist to aid in follow-on behavior. | |
| .001 | Local Account |
Adversaries may attempt to get a listing of local system accounts. This information can help adversaries determine which local accounts exist on a system to aid in follow-on behavior.
Commands such as net user and net localgroup of the Net utility and id and groupson macOS and Linux can list local users and groups. On Linux, local users can also be enumerated through the use of the /etc/passwd file. On macOS the dscl . list /Users command can be used to enumerate local accounts. |
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| .002 | Domain Account |
Adversaries may attempt to get a listing of domain accounts. This information can help adversaries determine which domain accounts exist to aid in follow-on behavior.
Commands such as net user /domain and net group /domain of the Net utility, dscacheutil -q groupon macOS, and ldapsearch on Linux can list domain users and groups. |
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| .003 | Email Account |
Adversaries may attempt to get a listing of email addresses and accounts. Adversaries may try to dump Exchange address lists such as global address lists (GALs).(Citation: Microsoft Exchange Address Lists)
In on-premises Exchange and Exchange Online, theGet-GlobalAddressList PowerShell cmdlet can be used to obtain email addresses and accounts from a domain using an authenticated session.(Citation: Microsoft getglobaladdresslist)(Citation: Black Hills Attacking Exchange MailSniper, 2016)
In Google Workspace, the GAL is shared with Microsoft Outlook users through the Google Workspace Sync for Microsoft Outlook (GWSMO) service. Additionally, the Google Workspace Directory allows for users to get a listing of other users within the organization.(Citation: Google Workspace Global Access List) |
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| .004 | Cloud Account |
Adversaries may attempt to get a listing of cloud accounts. Cloud accounts are those created and configured by an organization for use by users, remote support, services, or for administration of resources within a cloud service provider or SaaS application.
With authenticated access there are several tools that can be used to find accounts. The Get-MsolRoleMember PowerShell cmdlet can be used to obtain account names given a role or permissions group in Office 365.(Citation: Microsoft msolrolemember)(Citation: GitHub Raindance) The Azure CLI (AZ CLI) also provides an interface to obtain user accounts with authenticated access to a domain. The command az ad user list will list all users within a domain.(Citation: Microsoft AZ CLI)(Citation: Black Hills Red Teaming MS AD Azure, 2018)
The AWS command aws iam list-users may be used to obtain a list of users in the current account while aws iam list-roles can obtain IAM roles that have a specified path prefix.(Citation: AWS List Roles)(Citation: AWS List Users) In GCP, gcloud iam service-accounts list and gcloud projects get-iam-policy may be used to obtain a listing of service accounts and users in a project.(Citation: Google Cloud - IAM Servie Accounts List API) |
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| T1010 | Исследование открытых приложений | Adversaries may attempt to get a listing of open application windows. Window listings could convey information about how the system is used or give context to information collected by a keylogger.(Citation: Prevailion DarkWatchman 2021) | |
| T1217 | Исследование закладок в браузерах | Adversaries may enumerate browser bookmarks to learn more about compromised hosts. Browser bookmarks may reveal personal information about users (ex: banking sites, interests, social media, etc.) as well as details about internal network resources such as servers, tools/dashboards, or other related infrastructure. Browser bookmarks may also highlight additional targets after an adversary has access to valid credentials, especially Credentials In Files associated with logins cached by a browser. Specific storage locations vary based on platform and/or application, but browser bookmarks are typically stored in local files/databases. | |
| T1580 | Исследование облачной инфраструктуры |
An adversary may attempt to discover infrastructure and resources that are available within an infrastructure-as-a-service (IaaS) environment. This includes compute service resources such as instances, virtual machines, and snapshots as well as resources of other services including the storage and database services.
Cloud providers offer methods such as APIs and commands issued through CLIs to serve information about infrastructure. For example, AWS provides a DescribeInstances API within the Amazon EC2 API that can return information about one or more instances within an account, the ListBuckets API that returns a list of all buckets owned by the authenticated sender of the request, the HeadBucket API to determine a bucket’s existence along with access permissions of the request sender, or the GetPublicAccessBlock API to retrieve access block configuration for a bucket.(Citation: Amazon Describe Instance)(Citation: Amazon Describe Instances API)(Citation: AWS Get Public Access Block)(Citation: AWS Head Bucket) Similarly, GCP's Cloud SDK CLI provides the gcloud compute instances list command to list all Google Compute Engine instances in a project (Citation: Google Compute Instances), and Azure's CLI command az vm list lists details of virtual machines.(Citation: Microsoft AZ CLI) In addition to API commands, adversaries can utilize open source tools to discover cloud storage infrastructure through Wordlist Scanning.(Citation: Malwarebytes OSINT Leaky Buckets - Hioureas)
An adversary may enumerate resources using a compromised user's access keys to determine which are available to that user.(Citation: Expel IO Evil in AWS) The discovery of these available resources may help adversaries determine their next steps in the Cloud environment, such as establishing Persistence.(Citation: Mandiant M-Trends 2020)An adversary may also use this information to change the configuration to make the bucket publicly accessible, allowing data to be accessed without authentication. Adversaries have also may use infrastructure discovery APIs such as DescribeDBInstances to determine size, owner, permissions, and network ACLs of database resources. (Citation: AWS Describe DB Instances) Adversaries can use this information to determine the potential value of databases and discover the requirements to access them. Unlike in Cloud Service Discovery, this technique focuses on the discovery of components of the provided services rather than the services themselves. |
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| T1538 | Панель управления облачной службы | An adversary may use a cloud service dashboard GUI with stolen credentials to gain useful information from an operational cloud environment, such as specific services, resources, and features. For example, the GCP Command Center can be used to view all assets, findings of potential security risks, and to run additional queries, such as finding public IP addresses and open ports.(Citation: Google Command Center Dashboard) Depending on the configuration of the environment, an adversary may be able to enumerate more information via the graphical dashboard than an API. This allows the adversary to gain information without making any API requests. | |
| T1526 | Исследование облачных служб | An adversary may attempt to enumerate the cloud services running on a system after gaining access. These methods can differ from platform-as-a-service (PaaS), to infrastructure-as-a-service (IaaS), or software-as-a-service (SaaS). Many services exist throughout the various cloud providers and can include Continuous Integration and Continuous Delivery (CI/CD), Lambda Functions, Azure AD, etc. Adversaries may attempt to discover information about the services enabled throughout the environment. Azure tools and APIs, such as the Azure AD Graph API and Azure Resource Manager API, can enumerate resources and services, including applications, management groups, resources and policy definitions, and their relationships that are accessible by an identity.(Citation: Azure - Resource Manager API)(Citation: Azure AD Graph API) Stormspotter is an open source tool for enumerating and constructing a graph for Azure resources and services, and Pacu is an open source AWS exploitation framework that supports several methods for discovering cloud services.(Citation: Azure - Stormspotter)(Citation: GitHub Pacu) | |
| T1619 | Выявление объектов облачного хранилища | Adversaries may enumerate objects in cloud storage infrastructure. Adversaries may use this information during automated discovery to shape follow-on behaviors, including requesting all or specific objects from cloud storage. Similar to File and Directory Discovery on a local host, after identifying available storage services (i.e. Cloud Infrastructure Discovery) adversaries may access the contents/objects stored in cloud infrastructure. Cloud service providers offer APIs allowing users to enumerate objects stored within cloud storage. Examples include ListObjectsV2 in AWS (Citation: ListObjectsV2) and List Blobs in Azure(Citation: List Blobs) . | |
| T1613 | Выявление контейнеров и ресурсов контейнеризации | Adversaries may attempt to discover containers and other resources that are available within a containers environment. Other resources may include images, deployments, pods, nodes, and other information such as the status of a cluster. These resources can be viewed within web applications such as the Kubernetes dashboard or can be queried via the Docker and Kubernetes APIs.(Citation: Docker API)(Citation: Kubernetes API) In Docker, logs may leak information about the environment, such as the environment’s configuration, which services are available, and what cloud provider the victim may be utilizing. The discovery of these resources may inform an adversary’s next steps in the environment, such as how to perform lateral movement and which methods to utilize for execution. | |
| T1622 | Обход отладчиков |
Adversaries may employ various means to detect and avoid debuggers. Debuggers are typically used by defenders to trace and/or analyze the execution of potential malware payloads.(Citation: ProcessHacker Github)
Debugger evasion may include changing behaviors based on the results of the checks for the presence of artifacts indicative of a debugged environment. Similar to Virtualization/Sandbox Evasion, if the adversary detects a debugger, they may alter their malware to disengage from the victim or conceal the core functions of the implant. They may also search for debugger artifacts before dropping secondary or additional payloads.
Specific checks will vary based on the target and/or adversary, but may involve Native API function calls such as IsDebuggerPresent() and NtQueryInformationProcess(), or manually checking the BeingDebugged flag of the Process Environment Block (PEB). Other checks for debugging artifacts may also seek to enumerate hardware breakpoints, interrupt assembly opcodes, time checks, or measurements if exceptions are raised in the current process (assuming a present debugger would “swallow” or handle the potential error).(Citation: hasherezade debug)(Citation: AlKhaser Debug)(Citation: vxunderground debug)
Adversaries may use the information learned from these debugger checks during automated discovery to shape follow-on behaviors. Debuggers can also be evaded by detaching the process or flooding debug logs with meaningless data via messages produced by looping Native API function calls such as OutputDebugStringW().(Citation: wardle evilquest partii)(Citation: Checkpoint Dridex Jan 2021) |
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| T1482 | Исследование доверительных отношений между доменами | Adversaries may attempt to gather information on domain trust relationships that may be used to identify lateral movement opportunities in Windows multi-domain/forest environments. Domain trusts provide a mechanism for a domain to allow access to resources based on the authentication procedures of another domain.(Citation: Microsoft Trusts) Domain trusts allow the users of the trusted domain to access resources in the trusting domain. The information discovered may help the adversary conduct SID-History Injection, Pass the Ticket, and Kerberoasting.(Citation: AdSecurity Forging Trust Tickets)(Citation: Harmj0y Domain Trusts) Domain trusts can be enumerated using the `DSEnumerateDomainTrusts()` Win32 API call, .NET methods, and LDAP.(Citation: Harmj0y Domain Trusts) The Windows utility Nltest is known to be used by adversaries to enumerate domain trusts.(Citation: Microsoft Operation Wilysupply) | |
| T1083 | Исследование файлов и каталогов |
Adversaries may enumerate files and directories or may search in specific locations of a host or network share for certain information within a file system. Adversaries may use the information from File and Directory Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.
Many command shell utilities can be used to obtain this information. Examples include dir, tree, ls, find, and locate.(Citation: Windows Commands JPCERT) Custom tools may also be used to gather file and directory information and interact with the Native API. Adversaries may also leverage a Network Device CLI on network devices to gather file and directory information (e.g. dir, show flash, and/or nvram).(Citation: US-CERT-TA18-106A) |
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| T1615 | Выявление состава групповой политики |
Adversaries may gather information on Group Policy settings to identify paths for privilege escalation, security measures applied within a domain, and to discover patterns in domain objects that can be manipulated or used to blend in the environment. Group Policy allows for centralized management of user and computer settings in Active Directory (AD). Group policy objects (GPOs) are containers for group policy settings made up of files stored within a predicable network path \.(Citation: TechNet Group Policy Basics)(Citation: ADSecurity GPO Persistence 2016)
Adversaries may use commands such as gpresult or various publicly available PowerShell functions, such as Get-DomainGPO and Get-DomainGPOLocalGroup, to gather information on Group Policy settings.(Citation: Microsoft gpresult)(Citation: Github PowerShell Empire) Adversaries may use this information to shape follow-on behaviors, including determining potential attack paths within the target network as well as opportunities to manipulate Group Policy settings (i.e. Domain Policy Modification) for their benefit. |
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| T1046 | Сканирование сетевых служб |
Adversaries may attempt to get a listing of services running on remote hosts and local network infrastructure devices, including those that may be vulnerable to remote software exploitation. Common methods to acquire this information include port and/or vulnerability scans using tools that are brought onto a system.(Citation: CISA AR21-126A FIVEHANDS May 2021)
Within cloud environments, adversaries may attempt to discover services running on other cloud hosts. Additionally, if the cloud environment is connected to a on-premises environment, adversaries may be able to identify services running on non-cloud systems as well.
Within macOS environments, adversaries may use the native Bonjour application to discover services running on other macOS hosts within a network. The Bonjour mDNSResponder daemon automatically registers and advertises a host’s registered services on the network. For example, adversaries can use a mDNS query (such as dns-sd -B _ssh._tcp .) to find other systems broadcasting the ssh service.(Citation: apple doco bonjour description)(Citation: macOS APT Activity Bradley) |
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| T1135 | Исследование общих сетевых ресурсов |
Adversaries may look for folders and drives shared on remote systems as a means of identifying sources of information to gather as a precursor for Collection and to identify potential systems of interest for Lateral Movement. Networks often contain shared network drives and folders that enable users to access file directories on various systems across a network.
File sharing over a Windows network occurs over the SMB protocol. (Citation: Wikipedia Shared Resource) (Citation: TechNet Shared Folder) Net can be used to query a remote system for available shared drives using the net view \\\\remotesystem command. It can also be used to query shared drives on the local system using net share. For macOS, the sharing -l command lists all shared points used for smb services. |
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| T1040 | Прослушивание сетевого трафика | Adversaries may sniff network traffic to capture information about an environment, including authentication material passed over the network. Network sniffing refers to using the network interface on a system to monitor or capture information sent over a wired or wireless connection. An adversary may place a network interface into promiscuous mode to passively access data in transit over the network, or use span ports to capture a larger amount of data. Data captured via this technique may include user credentials, especially those sent over an insecure, unencrypted protocol. Techniques for name service resolution poisoning, such as LLMNR/NBT-NS Poisoning and SMB Relay, can also be used to capture credentials to websites, proxies, and internal systems by redirecting traffic to an adversary. Network sniffing may also reveal configuration details, such as running services, version numbers, and other network characteristics (e.g. IP addresses, hostnames, VLAN IDs) necessary for subsequent Lateral Movement and/or Defense Evasion activities. In cloud-based environments, adversaries may still be able to use traffic mirroring services to sniff network traffic from virtual machines. For example, AWS Traffic Mirroring, GCP Packet Mirroring, and Azure vTap allow users to define specified instances to collect traffic from and specified targets to send collected traffic to.(Citation: AWS Traffic Mirroring) (Citation: GCP Packet Mirroring) (Citation: Azure Virtual Network TAP) Often, much of this traffic will be in cleartext due to the use of TLS termination at the load balancer level to reduce the strain of encrypting and decrypting traffic.(Citation: Rhino Security Labs AWS VPC Traffic Mirroring) (Citation: SpecterOps AWS Traffic Mirroring) The adversary can then use exfiltration techniques such as Transfer Data to Cloud Account in order to access the sniffed traffic. (Citation: Rhino Security Labs AWS VPC Traffic Mirroring) | |
| T1201 | Исследование парольной политики |
Adversaries may attempt to access detailed information about the password policy used within an enterprise network or cloud environment. Password policies are a way to enforce complex passwords that are difficult to guess or crack through Brute Force. This information may help the adversary to create a list of common passwords and launch dictionary and/or brute force attacks which adheres to the policy (e.g. if the minimum password length should be 8, then not trying passwords such as 'pass123'; not checking for more than 3-4 passwords per account if the lockout is set to 6 as to not lock out accounts).
Password policies can be set and discovered on Windows, Linux, and macOS systems via various command shell utilities such as net accounts (/domain), Get-ADDefaultDomainPasswordPolicy, chage -l , cat /etc/pam.d/common-password, and pwpolicy getaccountpolicies (Citation: Superuser Linux Password Policies) (Citation: Jamf User Password Policies). Adversaries may also leverage a Network Device CLI on network devices to discover password policy information (e.g. show aaa, show aaa common-criteria policy all).(Citation: US-CERT-TA18-106A)
Password policies can be discovered in cloud environments using available APIs such as GetAccountPasswordPolicy in AWS (Citation: AWS GetPasswordPolicy). |
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| T1120 | Исследование периферийных устройств | Adversaries may attempt to gather information about attached peripheral devices and components connected to a computer system.(Citation: Peripheral Discovery Linux)(Citation: Peripheral Discovery macOS) Peripheral devices could include auxiliary resources that support a variety of functionalities such as keyboards, printers, cameras, smart card readers, or removable storage. The information may be used to enhance their awareness of the system and network environment or may be used for further actions. | |
| T1069 | Исследование групп разрешений | Adversaries may attempt to find group and permission settings. This information can help adversaries determine which user accounts and groups are available, the membership of users in particular groups, and which users and groups have elevated permissions. | |
| .001 | Local Groups |
Adversaries may attempt to find local system groups and permission settings. The knowledge of local system permission groups can help adversaries determine which groups exist and which users belong to a particular group. Adversaries may use this information to determine which users have elevated permissions, such as the users found within the local administrators group.
Commands such as net localgroup of the Net utility, dscl . -list /Groups on macOS, and groups on Linux can list local groups. |
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| .002 | Domain Groups |
Adversaries may attempt to find domain-level groups and permission settings. The knowledge of domain-level permission groups can help adversaries determine which groups exist and which users belong to a particular group. Adversaries may use this information to determine which users have elevated permissions, such as domain administrators.
Commands such as net group /domain of the Net utility, dscacheutil -q group on macOS, and ldapsearch on Linux can list domain-level groups. |
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| .003 | Cloud Groups |
Adversaries may attempt to find cloud groups and permission settings. The knowledge of cloud permission groups can help adversaries determine the particular roles of users and groups within an environment, as well as which users are associated with a particular group.
With authenticated access there are several tools that can be used to find permissions groups. The Get-MsolRole PowerShell cmdlet can be used to obtain roles and permissions groups for Exchange and Office 365 accounts (Citation: Microsoft Msolrole)(Citation: GitHub Raindance).
Azure CLI (AZ CLI) and the Google Cloud Identity Provider API also provide interfaces to obtain permissions groups. The command az ad user get-member-groups will list groups associated to a user account for Azure while the API endpoint GET https://cloudidentity.googleapis.com/v1/groups lists group resources available to a user for Google.(Citation: Microsoft AZ CLI)(Citation: Black Hills Red Teaming MS AD Azure, 2018)(Citation: Google Cloud Identity API Documentation)
Adversaries may attempt to list ACLs for objects to determine the owner and other accounts with access to the object, for example, via the AWS GetBucketAcl API (Citation: AWS Get Bucket ACL). Using this information an adversary can target accounts with permissions to a given object or leverage accounts they have already compromised to access the object. |
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| T1057 | Исследование процессов |
Adversaries may attempt to get information about running processes on a system. Information obtained could be used to gain an understanding of common software/applications running on systems within the network. Adversaries may use the information from Process Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.
In Windows environments, adversaries could obtain details on running processes using the Tasklist utility via cmd or Get-Process via PowerShell. Information about processes can also be extracted from the output of Native API calls such as CreateToolhelp32Snapshot. In Mac and Linux, this is accomplished with the ps command. Adversaries may also opt to enumerate processes via /proc. |
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| T1012 | Запросы к реестру | Adversaries may interact with the Windows Registry to gather information about the system, configuration, and installed software. The Registry contains a significant amount of information about the operating system, configuration, software, and security.(Citation: Wikipedia Windows Registry) Information can easily be queried using the Reg utility, though other means to access the Registry exist. Some of the information may help adversaries to further their operation within a network. Adversaries may use the information from Query Registry during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions. | |
| T1018 | Исследование удаленных систем |
Adversaries may attempt to get a listing of other systems by IP address, hostname, or other logical identifier on a network that may be used for Lateral Movement from the current system. Functionality could exist within remote access tools to enable this, but utilities available on the operating system could also be used such as Ping or net view using Net.
Adversaries may also analyze data from local host files (ex: C:\Windows\System32\Drivers\etc\hosts or /etc/hosts) or other passive means (such as local Arp cache entries) in order to discover the presence of remote systems in an environment.
Adversaries may also target discovery of network infrastructure as well as leverage Network Device CLI commands on network devices to gather detailed information about systems within a network (e.g. show cdp neighbors, show arp).(Citation: US-CERT-TA18-106A)(Citation: CISA AR21-126A FIVEHANDS May 2021)
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| T1063 | Исследование средств защиты |
Adversaries may attempt to get a listing of security software, configurations, defensive tools, and sensors that are installed on the system. This may include things such as local firewall rules and anti-virus. Adversaries may use the information from Security Software Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.
### Windows
Example commands that can be used to obtain security software information are netsh, reg query with Reg, dir with cmd, and Tasklist, but other indicators of discovery behavior may be more specific to the type of software or security system the adversary is looking for.
### Mac
It's becoming more common to see macOS malware perform checks for LittleSnitch and KnockKnock software. |
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| T1518 | Исследование установленного ПО | Adversaries may attempt to get a listing of software and software versions that are installed on a system or in a cloud environment. Adversaries may use the information from Software Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions. Adversaries may attempt to enumerate software for a variety of reasons, such as figuring out what security measures are present or if the compromised system has a version of software that is vulnerable to Exploitation for Privilege Escalation. | |
| .001 | Security Software Discovery |
Adversaries may attempt to get a listing of security software, configurations, defensive tools, and sensors that are installed on a system or in a cloud environment. This may include things such as firewall rules and anti-virus. Adversaries may use the information from Security Software Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.
Example commands that can be used to obtain security software information are netsh, reg query with Reg, dir with cmd, and Tasklist, but other indicators of discovery behavior may be more specific to the type of software or security system the adversary is looking for. It is becoming more common to see macOS malware perform checks for LittleSnitch and KnockKnock software.
Adversaries may also utilize cloud APIs to discover the configurations of firewall rules within an environment.(Citation: Expel IO Evil in AWS) For example, the permitted IP ranges, ports or user accounts for the inbound/outbound rules of security groups, virtual firewalls established within AWS for EC2 and/or VPC instances, can be revealed by the DescribeSecurityGroups action with various request parameters. (Citation: DescribeSecurityGroups - Amazon Elastic Compute Cloud) |
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| T1082 | Исследование системы |
An adversary may attempt to get detailed information about the operating system and hardware, including version, patches, hotfixes, service packs, and architecture. Adversaries may use the information from System Information Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.
Tools such as Systeminfo can be used to gather detailed system information. If running with privileged access, a breakdown of system data can be gathered through the systemsetup configuration tool on macOS. As an example, adversaries with user-level access can execute the df -aH command to obtain currently mounted disks and associated freely available space. Adversaries may also leverage a Network Device CLI on network devices to gather detailed system information (e.g. show version).(Citation: US-CERT-TA18-106A) System Information Discovery combined with information gathered from other forms of discovery and reconnaissance can drive payload development and concealment.(Citation: OSX.FairyTale)(Citation: 20 macOS Common Tools and Techniques)
Infrastructure as a Service (IaaS) cloud providers such as AWS, GCP, and Azure allow access to instance and virtual machine information via APIs. Successful authenticated API calls can return data such as the operating system platform and status of a particular instance or the model view of a virtual machine.(Citation: Amazon Describe Instance)(Citation: Google Instances Resource)(Citation: Microsoft Virutal Machine API) |
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| T1614 | Выявление местоположения системы |
Adversaries may gather information in an attempt to calculate the geographical location of a victim host. Adversaries may use the information from System Location Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.
Adversaries may attempt to infer the location of a system using various system checks, such as time zone, keyboard layout, and/or language settings.(Citation: FBI Ragnar Locker 2020)(Citation: Sophos Geolocation 2016)(Citation: Bleepingcomputer RAT malware 2020) Windows API functions such as GetLocaleInfoW can also be used to determine the locale of the host.(Citation: FBI Ragnar Locker 2020) In cloud environments, an instance's availability zone may also be discovered by accessing the instance metadata service from the instance.(Citation: AWS Instance Identity Documents)(Citation: Microsoft Azure Instance Metadata 2021)
Adversaries may also attempt to infer the location of a victim host using IP addressing, such as via online geolocation IP-lookup services.(Citation: Securelist Trasparent Tribe 2020)(Citation: Sophos Geolocation 2016) |
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| .001 | System Language Discovery |
Adversaries may attempt to gather information about the system language of a victim in order to infer the geographical location of that host. This information may be used to shape follow-on behaviors, including whether the adversary infects the target and/or attempts specific actions. This decision may be employed by malware developers and operators to reduce their risk of attracting the attention of specific law enforcement agencies or prosecution/scrutiny from other entities.(Citation: Malware System Language Check)
There are various sources of data an adversary could use to infer system language, such as system defaults and keyboard layouts. Specific checks will vary based on the target and/or adversary, but may involve behaviors such as Query Registry and calls to Native API functions.(Citation: CrowdStrike Ryuk January 2019)
For example, on a Windows system adversaries may attempt to infer the language of a system by querying the registry key HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\Nls\Language or parsing the outputs of Windows API functions GetUserDefaultUILanguage, GetSystemDefaultUILanguage, GetKeyboardLayoutList and GetUserDefaultLangID.(Citation: Darkside Ransomware Cybereason)(Citation: Securelist JSWorm)(Citation: SecureList SynAck Doppelgänging May 2018)
On a macOS or Linux system, adversaries may query locale to retrieve the value of the $LANG environment variable. |
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| T1016 | Исследование конфигурации сети |
Adversaries may look for details about the network configuration and settings, such as IP and/or MAC addresses, of systems they access or through information discovery of remote systems. Several operating system administration utilities exist that can be used to gather this information. Examples include Arp, ipconfig/ifconfig, nbtstat, and route.
Adversaries may also leverage a Network Device CLI on network devices to gather information about configurations and settings, such as IP addresses of configured interfaces and static/dynamic routes (e.g. show ip route, show ip interface).(Citation: US-CERT-TA18-106A)(Citation: Mandiant APT41 Global Intrusion )
Adversaries may use the information from System Network Configuration Discovery during automated discovery to shape follow-on behaviors, including determining certain access within the target network and what actions to do next. |
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| .001 | Internet Connection Discovery |
Adversaries may check for Internet connectivity on compromised systems. This may be performed during automated discovery and can be accomplished in numerous ways such as using Ping, tracert, and GET requests to websites.
Adversaries may use the results and responses from these requests to determine if the system is capable of communicating with their C2 servers before attempting to connect to them. The results may also be used to identify routes, redirectors, and proxy servers. |
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| T1049 | Исследование сетевых подключений |
Adversaries may attempt to get a listing of network connections to or from the compromised system they are currently accessing or from remote systems by querying for information over the network.
An adversary who gains access to a system that is part of a cloud-based environment may map out Virtual Private Clouds or Virtual Networks in order to determine what systems and services are connected. The actions performed are likely the same types of discovery techniques depending on the operating system, but the resulting information may include details about the networked cloud environment relevant to the adversary's goals. Cloud providers may have different ways in which their virtual networks operate.(Citation: Amazon AWS VPC Guide)(Citation: Microsoft Azure Virtual Network Overview)(Citation: Google VPC Overview) Similarly, adversaries who gain access to network devices may also perform similar discovery activities to gather information about connected systems and services.
Utilities and commands that acquire this information include netstat, "net use," and "net session" with Net. In Mac and Linux, netstat and lsof can be used to list current connections. who -a and w can be used to show which users are currently logged in, similar to "net session". Additionally, built-in features native to network devices and Network Device CLI may be used (e.g. show ip sockets, show tcp brief).(Citation: US-CERT-TA18-106A) |
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| T1033 | Исследование владельца или пользователей системы |
Adversaries may attempt to identify the primary user, currently logged in user, set of users that commonly uses a system, or whether a user is actively using the system. They may do this, for example, by retrieving account usernames or by using OS Credential Dumping. The information may be collected in a number of different ways using other Discovery techniques, because user and username details are prevalent throughout a system and include running process ownership, file/directory ownership, session information, and system logs. Adversaries may use the information from System Owner/User Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.
Various utilities and commands may acquire this information, including whoami. In macOS and Linux, the currently logged in user can be identified with w and who. On macOS the dscl . list /Users | grep -v '_' command can also be used to enumerate user accounts. Environment variables, such as %USERNAME% and $USER, may also be used to access this information. |
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| T1007 | Исследование системных служб |
Adversaries may try to gather information about registered local system services. Adversaries may obtain information about services using tools as well as OS utility commands such as sc query, tasklist /svc, systemctl --type=service, and net start.
Adversaries may use the information from System Service Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions. |
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| T1124 | Исследование системного времени |
An adversary may gather the system time and/or time zone from a local or remote system. The system time is set and stored by the Windows Time Service within a domain to maintain time synchronization between systems and services in an enterprise network. (Citation: MSDN System Time) (Citation: Technet Windows Time Service)
System time information may be gathered in a number of ways, such as with Net on Windows by performing net time \\hostname to gather the system time on a remote system. The victim's time zone may also be inferred from the current system time or gathered by using w32tm /tz. (Citation: Technet Windows Time Service)
This information could be useful for performing other techniques, such as executing a file with a Scheduled Task/Job (Citation: RSA EU12 They're Inside), or to discover locality information based on time zone to assist in victim targeting (i.e. System Location Discovery). Adversaries may also use knowledge of system time as part of a time bomb, or delaying execution until a specified date/time.(Citation: AnyRun TimeBomb) |
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| T1497 | Обход виртуализации или песочницы | Adversaries may employ various means to detect and avoid virtualization and analysis environments. This may include changing behaviors based on the results of checks for the presence of artifacts indicative of a virtual machine environment (VME) or sandbox. If the adversary detects a VME, they may alter their malware to disengage from the victim or conceal the core functions of the implant. They may also search for VME artifacts before dropping secondary or additional payloads. Adversaries may use the information learned from Virtualization/Sandbox Evasion during automated discovery to shape follow-on behaviors.(Citation: Deloitte Environment Awareness) Adversaries may use several methods to accomplish Virtualization/Sandbox Evasion such as checking for security monitoring tools (e.g., Sysinternals, Wireshark, etc.) or other system artifacts associated with analysis or virtualization. Adversaries may also check for legitimate user activity to help determine if it is in an analysis environment. Additional methods include use of sleep timers or loops within malware code to avoid operating within a temporary sandbox.(Citation: Unit 42 Pirpi July 2015) | |
| .001 | System Checks | Adversaries may employ various system checks to detect and avoid virtualization and analysis environments. This may include changing behaviors based on the results of checks for the presence of artifacts indicative of a virtual machine environment (VME) or sandbox. If the adversary detects a VME, they may alter their malware to disengage from the victim or conceal the core functions of the implant. They may also search for VME artifacts before dropping secondary or additional payloads. Adversaries may use the information learned from Virtualization/Sandbox Evasion during automated discovery to shape follow-on behaviors.(Citation: Deloitte Environment Awareness) Specific checks will vary based on the target and/or adversary, but may involve behaviors such as Windows Management Instrumentation, PowerShell, System Information Discovery, and Query Registry to obtain system information and search for VME artifacts. Adversaries may search for VME artifacts in memory, processes, file system, hardware, and/or the Registry. Adversaries may use scripting to automate these checks into one script and then have the program exit if it determines the system to be a virtual environment. Checks could include generic system properties such as host/domain name and samples of network traffic. Adversaries may also check the network adapters addresses, CPU core count, and available memory/drive size. Other common checks may enumerate services running that are unique to these applications, installed programs on the system, manufacturer/product fields for strings relating to virtual machine applications, and VME-specific hardware/processor instructions.(Citation: McAfee Virtual Jan 2017) In applications like VMWare, adversaries can also use a special I/O port to send commands and receive output. Hardware checks, such as the presence of the fan, temperature, and audio devices, could also be used to gather evidence that can be indicative a virtual environment. Adversaries may also query for specific readings from these devices.(Citation: Unit 42 OilRig Sept 2018) | |
| .002 | User Activity Based Checks | Adversaries may employ various user activity checks to detect and avoid virtualization and analysis environments. This may include changing behaviors based on the results of checks for the presence of artifacts indicative of a virtual machine environment (VME) or sandbox. If the adversary detects a VME, they may alter their malware to disengage from the victim or conceal the core functions of the implant. They may also search for VME artifacts before dropping secondary or additional payloads. Adversaries may use the information learned from Virtualization/Sandbox Evasion during automated discovery to shape follow-on behaviors.(Citation: Deloitte Environment Awareness) Adversaries may search for user activity on the host based on variables such as the speed/frequency of mouse movements and clicks (Citation: Sans Virtual Jan 2016) , browser history, cache, bookmarks, or number of files in common directories such as home or the desktop. Other methods may rely on specific user interaction with the system before the malicious code is activated, such as waiting for a document to close before activating a macro (Citation: Unit 42 Sofacy Nov 2018) or waiting for a user to double click on an embedded image to activate.(Citation: FireEye FIN7 April 2017) | |
| .003 | Time Based Evasion | Adversaries may employ various time-based methods to detect and avoid virtualization and analysis environments. This may include enumerating time-based properties, such as uptime or the system clock, as well as the use of timers or other triggers to avoid a virtual machine environment (VME) or sandbox, specifically those that are automated or only operate for a limited amount of time. Adversaries may employ various time-based evasions, such as delaying malware functionality upon initial execution using programmatic sleep commands or native system scheduling functionality (ex: Scheduled Task/Job). Delays may also be based on waiting for specific victim conditions to be met (ex: system time, events, etc.) or employ scheduled Multi-Stage Channels to avoid analysis and scrutiny.(Citation: Deloitte Environment Awareness) Benign commands or other operations may also be used to delay malware execution. Loops or otherwise needless repetitions of commands, such as Pings, may be used to delay malware execution and potentially exceed time thresholds of automated analysis environments.(Citation: Revil Independence Day)(Citation: Netskope Nitol) Another variation, commonly referred to as API hammering, involves making various calls to Native API functions in order to delay execution (while also potentially overloading analysis environments with junk data).(Citation: Joe Sec Nymaim)(Citation: Joe Sec Trickbot) Adversaries may also use time as a metric to detect sandboxes and analysis environments, particularly those that attempt to manipulate time mechanisms to simulate longer elapses of time. For example, an adversary may be able to identify a sandbox accelerating time by sampling and calculating the expected value for an environment's timestamp before and after execution of a sleep function.(Citation: ISACA Malware Tricks) | |
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