T1087: Account Discovery
Adversaries may attempt to get a listing of valid accounts, usernames, or email addresses on a system or within a compromised environment. This information can help adversaries determine which accounts exist, which can aid in follow-on behavior such as brute-forcing, spear-phishing attacks, or account takeovers (e.g., Valid Accounts).
Adversaries may use several methods to enumerate accounts, including abuse of existing tools, built-in commands, and potential misconfigurations that leak account names and roles or permissions in the targeted environment.
For examples, cloud environments typically provide easily accessible interfaces to obtain user lists.[1][2] On hosts, adversaries can use default PowerShell and other command line functionality to identify accounts. Information about email addresses and accounts may also be extracted by searching an infected system’s files.
Security context for executives and security teams
T1087: Account Discovery describes Adversaries may attempt to get a listing of valid accounts, usernames, or email addresses on a system or within a compromised environment. This information can help adversaries determine which accounts exist, which can aid in follow-on behavior such as brute-forcing, spear-phishing attacks, or account takeovers (e.g., [Valid Accounts](https://attack.mitre.org/techniques/T1078)). Adversaries may use several methods to enumerate accounts, including abuse of existing tools, built-in commands, and potential misconfigur...
Executive priority
T1087: Account Discovery is an official MITRE ATT&CK technique. Glexia treats it as defensive behavior context for prioritizing monitoring, control validation, and response planning without using the object by itself as an attribution claim.
Technical view
Security teams should validate T1087: Account Discovery by reviewing the official ATT&CK relationships, mapped tactics (discovery), supported platforms (ESXi, IaaS, Identity Provider, Linux), and available local telemetry before making detection or mitigation decisions.
Likely telemetry
- Official ATT&CK relationships and object metadata
- Endpoint process, command-line, and script execution logs
- Cloud control-plane, SaaS audit, and container platform logs
- Network, endpoint, and security-tool telemetry
Detection direction
- Validate whether T1087: Account Discovery appears in your detection coverage and tabletop scenarios.
- Use the object to align executive risk language with SOC, incident response, and detection engineering work.
- Do not treat ATT&CK relationship context as attribution without corroborating evidence.
Mitigation priorities
- Map the object to existing controls and identify missing telemetry or response ownership.
- Prioritize mitigations that reduce exposure on the listed platforms and tactics.
- Review adjacent ATT&CK relationships before changing policy, detections, or reporting language.
Additional notes and limits
Baseline Glexia take generated from the official MITRE ATT&CK STIX object, source hash, tactics, platforms, and detection fields. It is safe to replace with a richer model-generated take for the same source hash later.
This baseline take is source-grounded and schema-validated, but it does not include environment-specific telemetry, incident evidence, or threat-intelligence corroboration.
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Account Discovery
Adversaries may attempt to get a listing of valid accounts, usernames, or email addresses on a system or within a compromised environment. This information can help adversaries determine which accounts exist, which can aid in follow-on behavior such as brute-forcing, spear-phishing attacks, or account takeovers (e.g., Valid Accounts).
Adversaries may use several methods to enumerate accounts, including abuse of existing tools, built-in commands, and potential misconfigurations that leak account names and roles or permissions in the targeted environment.
For examples, cloud environments typically provide easily accessible interfaces to obtain user lists.[1][2] On hosts, adversaries can use default PowerShell and other command line functionality to identify accounts. Information about email addresses and accounts may also be extracted by searching an infected system’s files.
How security teams should use this page
Treat this object as behavior context, not an attribution claim. Validate the related groups, software, data sources, and mitigations against official ATT&CK relationships and your own telemetry before making control-coverage decisions.
Related techniques
This mirrors the MITRE pattern of making group, software, campaign, and technique relationships scannable. Relationship notes come from mirrored ATT&CK relationship text when available.
| Domain | ID | Name | Relationship / procedure |
|---|---|---|---|
| Enterprise | T1087.002 | Domain AccountSub-technique | Domain Account subtechnique of this object. |
| Enterprise | T1087.001 | Local AccountSub-technique | Local Account subtechnique of this object. |
| Enterprise | T1087.003 | Email AccountSub-technique | Email Account subtechnique of this object. |
| Enterprise | T1087.004 | Cloud AccountSub-technique | Cloud Account subtechnique of this object. |
Groups, software, and campaigns
G1015: Scattered Spider
Scattered Spider is a native English-speaking cybercriminal group active since at least 2022. [1] [2] The group initially targeted customer relationship management (CRM) providers, business process outsourcing (BPO) firms, and telecommunications and technology companies before expanding in 2023 to gaming, hospitality, retail, managed service provider (MSP), manufacturing, and financial sectors. [2] Scattered Spider relies heavily on social engineering, including impersonating IT and help-desk staff, to gain initial access, bypass multi-factor authentication (MFA), and compromise enterprise networks. The group has adapted its tooling to evade endpoint detection and response (EDR) defenses and used ransomware for financial gain. [3] [4] [5] Scattered Spider had expanded into hybrid cloud and identity environments, using help-desk impersonation and MFA bypass to obtain administrator access in Okta, AWS, and Office 365. [6]
G0143: Aquatic Panda
Aquatic Panda is a suspected China-based threat group with a dual mission of intelligence collection and industrial espionage. Active since at least May 2020, Aquatic Panda has primarily targeted entities in the telecommunications, technology, and government sectors.[1]
G1016: FIN13
S1229: Havoc
Havoc is an open-source post-exploitation command and control (C2) framework first released on GitHub in October 2022 by C5pider (Paul Ungur), who continues to maintain and develop it with community contributors. Havoc provides a wide range of offensive security capabilities and has been adopted by multiple threat actors to establish and maintain control over compromised systems.
S1239: TONESHELL
S1065: Woody RAT
S0658: XCSSET
XCSSET is a modular macOS malware family delivered through infected Xcode projects and executed when the project is compiled. Active since August 2020, it has been observed installing backdoors, spoofed browsers, collecting data, and encrypting user files. It is composed of SHC-compiled shell scripts and run-only AppleScripts, often hiding in apps that mimic system tools (such as Xcode, Mail, or Notes) or use familiar icons (like Launchpad) to avoid detection.[1][2][3]
S0445: ShimRatReporter
ShimRatReporter is a tool used by suspected Chinese adversary Mofang to automatically conduct initial discovery. The details from this discovery are used to customize follow-on payloads (such as ShimRat) as well as set up faux infrastructure which mimics the adversary's targets. ShimRatReporter has been used in campaigns targeting multiple countries and sectors including government, military, critical infrastructure, automobile, and weapons development.[1]
C0062: Anthropic AI-orchestrated Campaign
The Anthropic AI-orchestrated Campaign was conducted in September 2025 by a likely China nexus espionage actor identified as GTG-1002. The Anthropic AI-orchestrated Campaign was a highly coordinated operation that manipulated Claude Code to perform reconnaissance, vulnerability discovery, exploitation, lateral movement, credential harvesting, data analysis, and exfiltration operations at approximately 30 entities in the technology, financial, chemical, and government sectors. During the Anthropic AI-orchestrated Campaign, human operators used Claude Code agents and Model Context Protocol (MCP) tools to automate cyber operations. Operators broke attacks into discrete tasks, used crafted prompts, and established personas to bypass AI guardrails, enabling the agents to execute the operations with minimal human involvement.[1][2]
C0024: SolarWinds Compromise
The SolarWinds Compromise was a sophisticated supply chain cyber operation conducted by APT29 that was discovered in mid-December 2020. APT29 used customized malware to inject malicious code into the SolarWinds Orion software build process that was later distributed through a normal software update; they also used password spraying, token theft, API abuse, spear phishing, and other supply chain attacks to compromise user accounts and leverage their associated access. Victims of this campaign included government, consulting, technology, telecom, and other organizations in North America, Europe, Asia, and the Middle East. This activity has been labled the StellarParticle campaign in industry reporting.[1] Industry reporting also initially referred to the actors involved in this campaign as UNC2452, NOBELIUM, Dark Halo, and SolarStorm.[2][3][4][5][1][6][7][8]
In April 2021, the US and UK governments attributed the SolarWinds Compromise to Russia's Foreign Intelligence Service (SVR); public statements included citations to APT29, Cozy Bear, and The Dukes.[9][10][11] The US government assessed that of the approximately 18,000 affected public and private sector customers of Solar Winds’ Orion product, a much smaller number were compromised by follow-on APT29 activity on their systems.[12]
All related ATT&CK context
Mitigation direction
Object version and sync metadata
The fields below describe the current mirrored snapshot. When Glexia retains multiple ATT&CK source imports, you can open the table to compare the same object across releases (hashes and MITRE timestamps). For MITRE’s own release notes and roadmap, see ATT&CK resources — Updates.
Imported snapshots across ATT&CK releases(2)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.2 | 2.6 | Current bundle | be431b2c00ce… | ||
| 19.1 | 2.6 | Older bundle | be431b2c00ce… |
Mirrored ATT&CK source object
The raw object is retained through the mirrored ATT&CK source bundle and object hash. The raw endpoint returns the exact object from the mirrored bundle when available.
External references and citations
MITRE external references are preserved separately from Glexia analysis so citations remain traceable to their original source records.
- [1]AWS List Users
Amazon. (n.d.). List Users. Retrieved August 11, 2020.
Open source URL - [2]Google Cloud - IAM Servie Accounts List API
Google. (2020, June 23). gcloud iam service-accounts list. Retrieved August 4, 2020.
Open source URL - [3]Elastic - Koadiac Detection with EQL
Stepanic, D.. (2020, January 13). Embracing offensive tooling: Building detections against Koadic using EQL. Retrieved November 17, 2024.
Open source URL - [4]mitre-attackT1087Open source URL
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