chihhh/attack-tech-orig huggingface dataset:
Malware

Adversaries may buy, steal, or download malware that can be used during targeting. Malicious software can include payloads, droppers, post-compromise tools, backdoors, packers, and C2 protocols. Adversaries may acquire malware to support their operations, obtaining a means for maintaining control of remote machines, evading defenses, and executing post-compromise behaviors.

In addition to downloading free malware from the internet, adversaries may purchase these capabilities from third-party entities. Third-party entities can include technology companies that specialize in malware development, criminal marketplaces (including Malware-as-a-Service, or MaaS), or from individuals. In addition to purchasing malware, adversaries may steal and repurpose malware from third-party entities (including other adversaries).

Platforms: PRE
Tactics:
phase_name: resource-development

Detection:
Consider analyzing malware for features that may be associated with malware providers, such as compiler used, debugging artifacts, code similarities, or even group identifiers associated with specific MaaS offerings. Malware repositories can also be used to identify additional samples associated with the developers and the adversary utilizing their services. Identifying overlaps in malware use by different adversaries may indicate malware was obtained by the adversary rather than developed by them. In some cases, identifying overlapping characteristics in malware used by different adversaries may point to a shared quartermaster.(Citation: FireEyeSupplyChain)

Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on post-compromise phases of the adversary lifecycle.

References:
source_name: mitre-attack
description: FireEye. (2014). SUPPLY CHAIN ANALYSIS: From Quartermaster to SunshopFireEye. Retrieved March 6, 2017.
source_name: FireEyeSupplyChain
Component Firmware

Adversaries may modify component firmware to persist on systems. Some adversaries may employ sophisticated means to compromise computer components and install malicious firmware that will execute adversary code outside of the operating system and main system firmware or BIOS. This technique may be similar to [System Firmware](https://attack.mitre.org/techniques/T1542/001) but conducted upon other system components/devices that may not have the same capability or level of integrity checking.

Malicious component firmware could provide both a persistent level of access to systems despite potential typical failures to maintain access and hard disk re-images, as well as a way to evade host software-based defenses and integrity checks.

Platforms: Windows
Linux
macOS
Tactics:
phase_name: persistence
phase_name: defense-evasion

Detection:
Data and telemetry from use of device drivers (i.e. processes and API calls) and/or provided by SMART (Self-Monitoring, Analysis and Reporting Technology) disk monitoring may reveal malicious manipulations of components.(Citation: SanDisk SMART)(Citation: SmartMontools) Otherwise, this technique may be difficult to detect since malicious activity is taking place on system components possibly outside the purview of OS security and integrity mechanisms.

Disk check and forensic utilities may reveal indicators of malicious firmware such as strings, unexpected disk partition table entries, or blocks of otherwise unusual memory that warrant deeper investigation.(Citation: ITWorld Hard Disk Health Dec 2014) Also consider comparing components, including hashes of component firmware and behavior, against known good images.

References:
source_name: mitre-attack
description: SanDisk. (n.d.). Self-Monitoring, Analysis and Reporting Technology (S.M.A.R.T.). Retrieved October 2, 2018.
source_name: SanDisk SMART
description: smartmontools. (n.d.). smartmontools. Retrieved October 2, 2018.
source_name: SmartMontools
description: Pinola, M. (2014, December 14). 3 tools to check your hard drive's health and make sure it's not already dying on you. Retrieved October 2, 2018.
source_name: ITWorld Hard Disk Health Dec 2014
Indicator Removal

Adversaries may delete or modify artifacts generated within systems to remove evidence of their presence or hinder defenses. Various artifacts may be created by an adversary or something that can be attributed to an adversary’s actions. Typically these artifacts are used as defensive indicators related to monitored events, such as strings from downloaded files, logs that are generated from user actions, and other data analyzed by defenders. Location, format, and type of artifact (such as command or login history) are often specific to each platform.

Removal of these indicators may interfere with event collection, reporting, or other processes used to detect intrusion activity. This may compromise the integrity of security solutions by causing notable events to go unreported. This activity may also impede forensic analysis and incident response, due to lack of sufficient data to determine what occurred.

Platforms: Linux
macOS
Windows
Containers
Network
Office 365
Google Workspace
Tactics:
phase_name: defense-evasion

Detection:
File system monitoring may be used to detect improper deletion or modification of indicator files.  Events not stored on the file system may require different detection mechanisms.

References:
source_name: mitre-attack
Exfiltration Over Symmetric Encrypted Non-C2 Protocol

Adversaries may steal data by exfiltrating it over a symmetrically encrypted network protocol other 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. 

Symmetric encryption algorithms are those that use shared or the same keys/secrets on each end of the channel. This requires an exchange or pre-arranged agreement/possession of the value used to encrypt and decrypt data. 

Network protocols that use asymmetric encryption often utilize symmetric encryption once keys are exchanged, but adversaries may opt to manually share keys and implement symmetric cryptographic algorithms (ex: RC4, AES) vice using mechanisms that are baked into a protocol. This may result in multiple layers of encryption (in protocols that are natively encrypted such as HTTPS) or encryption in protocols that not typically encrypted (such as HTTP or FTP). 

Platforms: Linux
macOS
Windows
Tactics:
phase_name: exfiltration

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.(Citation: University of Birmingham C2) 

Artifacts and evidence of symmetric key exchange may be recoverable by analyzing network traffic or looking for hard-coded values within malware. If recovered, these keys can be used to decrypt network data from command and control channels. 

References:
source_name: mitre-attack
description: Gardiner, J.,  Cova, M., Nagaraja, S. (2014, February). Command & Control Understanding, Denying and Detecting. Retrieved April 20, 2016.
source_name: University of Birmingham C2
Virtual Private Server

Adversaries may rent Virtual Private Servers (VPSs) that can be used during targeting. There exist a variety of cloud service providers that will sell virtual machines/containers as a service. By utilizing a VPS, adversaries can make it difficult to physically tie back operations to them. The use of cloud infrastructure can also make it easier for adversaries to rapidly provision, modify, and shut down their infrastructure.

Acquiring a VPS for use in later stages of the adversary lifecycle, such as Command and Control, can allow adversaries to benefit from the ubiquity and trust associated with higher reputation cloud service providers. Adversaries may also acquire infrastructure from VPS service providers that are known for renting VPSs with minimal registration information, allowing for more anonymous acquisitions of infrastructure.(Citation: TrendmicroHideoutsLease)

Platforms: PRE
Tactics:
phase_name: resource-development

Detection:
Once adversaries have provisioned a VPS (ex: for use as a command and control server), internet scans may reveal servers that adversaries have acquired. Consider looking for identifiable patterns such as services listening, certificates in use, SSL/TLS negotiation features, or other response artifacts associated with adversary C2 software.(Citation: ThreatConnect Infrastructure Dec 2020)(Citation: Mandiant SCANdalous Jul 2020)(Citation: Koczwara Beacon Hunting Sep 2021)

Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Command and Control.

References:
source_name: mitre-attack
description: Max Goncharov. (2015, July 15). Criminal Hideouts for Lease: Bulletproof Hosting Services. Retrieved March 6, 2017.
source_name: TrendmicroHideoutsLease
description: ThreatConnect. (2020, December 15). Infrastructure Research and Hunting: Boiling the Domain Ocean. Retrieved October 12, 2021.
source_name: ThreatConnect Infrastructure Dec 2020
description: Stephens, A. (2020, July 13). SCANdalous! (External Detection Using Network Scan Data and Automation). Retrieved October 12, 2021.
source_name: Mandiant SCANdalous Jul 2020
description: Koczwara, M. (2021, September 7). Hunting Cobalt Strike C2 with Shodan. Retrieved October 12, 2021.
source_name: Koczwara Beacon Hunting Sep 2021
Confluence


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


Platforms: SaaS
Tactics:
phase_name: collection

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. (Citation: Atlassian Confluence Logging) Additional log storage and analysis infrastructure will likely be required for more robust detection capabilities.

References:
source_name: mitre-attack
description: Atlassian. (2018, January 9). How to Enable User Access Logging. Retrieved April 4, 2018.
source_name: Atlassian Confluence Logging
Container Administration Command

Adversaries may abuse a container administration service to execute commands within a container. A container administration service such as the Docker daemon, the Kubernetes API server, or the kubelet may allow remote management of containers within an environment.(Citation: Docker Daemon CLI)(Citation: Kubernetes API)(Citation: Kubernetes Kubelet)

In Docker, adversaries may specify an entrypoint during container deployment that executes a script or command, or they may use a command such as <code>docker exec</code> to execute a command within a running container.(Citation: Docker Entrypoint)(Citation: Docker Exec) In Kubernetes, if an adversary has sufficient permissions, they may gain remote execution in a container in the cluster via interaction with the Kubernetes API server, the kubelet, or by running a command such as <code>kubectl exec</code>.(Citation: Kubectl Exec Get Shell)

Platforms: Containers
Tactics:
phase_name: execution

Detection:
Container administration service activities and executed commands can be captured through logging of process execution with command-line arguments on the container and the underlying host. In Docker, the daemon log provides insight into events at the daemon and container service level. Kubernetes system component logs may also detect activities running in and out of containers in the cluster. 

References:
source_name: mitre-attack
description: Docker. (n.d.). Docker Exec. Retrieved March 29, 2021.
source_name: Docker Exec
description: Docker. (n.d.). Docker run reference. Retrieved March 29, 2021.
source_name: Docker Entrypoint
description: Docker. (n.d.). DockerD CLI. Retrieved March 29, 2021.
source_name: Docker Daemon CLI
description: The Kubernetes Authors. (n.d.). Get a Shell to a Running Container. Retrieved March 29, 2021.
source_name: Kubectl Exec Get Shell
description: The Kubernetes Authors. (n.d.). Kubelet. Retrieved March 29, 2021.
source_name: Kubernetes Kubelet
description: The Kubernetes Authors. (n.d.). The Kubernetes API. Retrieved March 29, 2021.
source_name: Kubernetes API
File and Directory Discovery

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](https://attack.mitre.org/techniques/T1083) 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 <code>dir</code>, <code>tree</code>, <code>ls</code>, <code>find</code>, and <code>locate</code>.(Citation: Windows Commands JPCERT) Custom tools may also be used to gather file and directory information and interact with the [Native API](https://attack.mitre.org/techniques/T1106). Adversaries may also leverage a [Network Device CLI](https://attack.mitre.org/techniques/T1059/008) on network devices to gather file and directory information (e.g. <code>dir</code>, <code>show flash</code>, and/or <code>nvram</code>).(Citation: US-CERT-TA18-106A)

Some files and directories may require elevated or specific user permissions to access.

Platforms: Linux
macOS
Windows
Network
Tactics:
phase_name: discovery

Detection:
System and network discovery techniques normally occur throughout an operation as an adversary learns the environment. Data and events should not be viewed in isolation, but as part of a chain of behavior that could lead to other activities, such as Collection and Exfiltration, based on the information obtained.

Monitor processes and command-line arguments for actions that could be taken to gather system and network information. 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](https://attack.mitre.org/techniques/T1047) and [PowerShell](https://attack.mitre.org/techniques/T1059/001). Further, [Network Device CLI](https://attack.mitre.org/techniques/T1059/008) commands may also be used to gather file and directory information with built-in features native to the network device platform.  Monitor CLI activity for unexpected or unauthorized use of commands being run by non-standard users from non-standard locations.  

References:
source_name: mitre-attack
description: Tomonaga, S. (2016, January 26). Windows Commands Abused by Attackers. Retrieved February 2, 2016.
source_name: Windows Commands JPCERT
description: US-CERT. (2018, April 20). Alert (TA18-106A) Russian State-Sponsored Cyber Actors Targeting Network Infrastructure Devices. Retrieved October 19, 2020.
source_name: US-CERT-TA18-106A
Dynamic Resolution

Adversaries may dynamically establish connections to command and control infrastructure to evade common detections and remediations. This may be achieved by using malware that shares a common algorithm with the infrastructure the adversary uses to receive the malware's communications. These calculations can be used to dynamically adjust parameters such as the domain name, IP address, or port number the malware uses for command and control.

Adversaries may use dynamic resolution for the purpose of [Fallback Channels](https://attack.mitre.org/techniques/T1008). When contact is lost with the primary command and control server malware may employ dynamic resolution as a means to reestablishing command and control.(Citation: Talos CCleanup 2017)(Citation: FireEye POSHSPY April 2017)(Citation: ESET Sednit 2017 Activity)

Platforms: Linux
macOS
Windows
Tactics:
phase_name: command-and-control

Detection:
Detecting dynamically generated C2 can be challenging due to the number of different algorithms, constantly evolving malware families, and the increasing complexity of the algorithms. There are multiple approaches to detecting a pseudo-randomly generated domain name, including using frequency analysis, Markov chains, entropy, proportion of dictionary words, ratio of vowels to other characters, and more (Citation: Data Driven Security DGA). CDN domains may trigger these detections due to the format of their domain names. In addition to detecting algorithm generated domains based on the name, another more general approach for detecting a suspicious domain is to check for recently registered names or for rarely visited domains.

References:
source_name: mitre-attack
description: Brumaghin, E. et al. (2017, September 18). CCleanup: A Vast Number of Machines at Risk. Retrieved March 9, 2018.
source_name: Talos CCleanup 2017
description: Dunwoody, M.. (2017, April 3). Dissecting One of APT29’s Fileless WMI and PowerShell Backdoors (POSHSPY). Retrieved April 5, 2017.
source_name: FireEye POSHSPY April 2017
description: ESET. (2017, December 21). Sednit update: How Fancy Bear Spent the Year. Retrieved February 18, 2019.
source_name: ESET Sednit 2017 Activity
description: Jacobs, J. (2014, October 2). Building a DGA Classifier: Part 2, Feature Engineering. Retrieved February 18, 2019.
source_name: Data Driven Security DGA
Masquerade Task or Service

Adversaries may attempt to manipulate the name of a task or service to make it appear legitimate or benign. Tasks/services executed by the Task Scheduler or systemd will typically be given a name and/or description.(Citation: TechNet Schtasks)(Citation: Systemd Service Units) Windows services will have a service name as well as a display name. Many benign tasks and services exist that have commonly associated names. Adversaries may give tasks or services names that are similar or identical to those of legitimate ones.

Tasks or services contain other fields, such as a description, that adversaries may attempt to make appear legitimate.(Citation: Palo Alto Shamoon Nov 2016)(Citation: Fysbis Dr Web Analysis)

Platforms: Windows
Linux
macOS
Tactics:
phase_name: defense-evasion

Detection:
Look for changes to tasks and services that do not correlate with known software, patch cycles, etc. Suspicious program execution through scheduled tasks or services may show up as outlier processes that have not been seen before when compared against historical data. Monitor processes and command-line arguments for actions that could be taken to create tasks or services. Data and events should not be viewed in isolation, but as part of a chain of behavior that could lead to other activities, such as network connections made for Command and Control, learning details about the environment through Discovery, and Lateral Movement.

References:
source_name: mitre-attack
description: Doctor Web. (2014, November 21). Linux.BackDoor.Fysbis.1. Retrieved December 7, 2017.
source_name: Fysbis Dr Web Analysis
description: Falcone, R.. (2016, November 30). Shamoon 2: Return of the Disttrack Wiper. Retrieved January 11, 2017.
source_name: Palo Alto Shamoon Nov 2016
description: Freedesktop.org. (n.d.). systemd.service — Service unit configuration. Retrieved March 16, 2020.
source_name: Systemd Service Units
description: Microsoft. (n.d.). Schtasks. Retrieved April 28, 2016.
source_name: TechNet Schtasks
Traffic Duplication

Adversaries may leverage traffic mirroring in order to automate data exfiltration over compromised infrastructure. Traffic mirroring is a native feature for some devices, often used for network analysis. For example, devices may be configured to forward network traffic to one or more destinations for analysis by a network analyzer or other monitoring device. (Citation: Cisco Traffic Mirroring)(Citation: Juniper Traffic Mirroring)

Adversaries may abuse traffic mirroring to mirror or redirect network traffic through other infrastructure they control. Malicious modifications to network devices to enable traffic redirection may be possible through [ROMMONkit](https://attack.mitre.org/techniques/T1542/004) or [Patch System Image](https://attack.mitre.org/techniques/T1601/001).(Citation: US-CERT-TA18-106A)(Citation: Cisco Blog Legacy Device Attacks)

Many cloud-based environments also support traffic mirroring. 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)

Adversaries may use traffic duplication in conjunction with [Network Sniffing](https://attack.mitre.org/techniques/T1040), [Input Capture](https://attack.mitre.org/techniques/T1056), or [Adversary-in-the-Middle](https://attack.mitre.org/techniques/T1557) depending on the goals and objectives of the adversary.

Platforms: Network
IaaS
Tactics:
phase_name: exfiltration

Detection:
Monitor network traffic for uncommon data flows (e.g. unusual network communications, suspicious communications that have never been seen before, communications sending fixed size data packets at regular intervals).  Analyze packet contents to detect communications that do not follow the expected protocol behavior for the port that is being used. 

References:
source_name: mitre-attack
description: Amazon Web Services. (n.d.). How Traffic Mirroring works. Retrieved March 17, 2022.
source_name: AWS Traffic Mirroring
description: Cisco. (n.d.). Cisco IOS XR Interface and Hardware Component Configuration Guide for the Cisco CRS Router, Release 5.1.x. Retrieved October 19, 2020.
source_name: Cisco Traffic Mirroring
description: Google Cloud. (n.d.). Packet Mirroring overview. Retrieved March 17, 2022.
source_name: GCP Packet Mirroring
description: Juniper. (n.d.). Understanding Port Mirroring on EX2200, EX3200, EX3300, EX4200, EX4500, EX4550, EX6200, and EX8200 Series Switches. Retrieved October 19, 2020.
source_name: Juniper Traffic Mirroring
description: Microsoft. (2022, February 9). Virtual network TAP. Retrieved March 17, 2022.
source_name: Azure Virtual Network TAP
description: Omar Santos. (2020, October 19). Attackers Continue to Target Legacy Devices. Retrieved October 20, 2020.
source_name: Cisco Blog Legacy Device Attacks
description: US-CERT. (2018, April 20). Alert (TA18-106A) Russian State-Sponsored Cyber Actors Targeting Network Infrastructure Devices. Retrieved October 19, 2020.
source_name: US-CERT-TA18-106A