T1497.002: 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.[1]
Adversaries may search for user activity on the host based on variables such as the speed/frequency of mouse movements and clicks [2] , 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 [3] or waiting for a user to double click on an embedded image to activate.[4]
Security context for executives and security teams
T1497.002: User Activity Based Checks describes 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 th...
Executive priority
T1497.002: User Activity Based Checks 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 T1497.002: User Activity Based Checks by reviewing the official ATT&CK relationships, mapped tactics (stealth, discovery), supported platforms (Linux, macOS, Windows), 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
- Network, endpoint, and security-tool telemetry
Detection direction
- Validate whether T1497.002: User Activity Based Checks 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.
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.[1]
Adversaries may search for user activity on the host based on variables such as the speed/frequency of mouse movements and clicks [2] , 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 [3] or waiting for a user to double click on an embedded image to activate.[4]
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 | T1497 | Virtualization/Sandbox Evasion | This object subtechnique of Virtualization/Sandbox Evasion. |
Groups, software, and campaigns
G0046: FIN7
FIN7 is a financially-motivated threat group that has been active since 2013. FIN7 has targeted the retail, restaurant, hospitality, software, consulting, financial services, medical equipment, cloud services, media, food and beverage, transportation, pharmaceutical, and utilities industries in the United States. A portion of FIN7 was operated out of a front company called Combi Security and often used point-of-sale malware for targeting efforts. Since 2020, FIN7 shifted operations to big game hunting (BGH), including use of REvil ransomware and their own Ransomware-as-a-Service (RaaS), Darkside. FIN7 may be linked to the Carbanak Group, but multiple threat groups have been observed using Carbanak, leading these groups to be tracked separately.[1][2][3][4][5][6][7]
G0012: Darkhotel
Darkhotel is a suspected South Korean threat group that has targeted victims primarily in East Asia since at least 2004. The group's name is based on cyber espionage operations conducted via hotel Internet networks against traveling executives and other select guests. Darkhotel has also conducted spearphishing campaigns and infected victims through peer-to-peer and file sharing networks.[1][2][3]
S0543: Spark
S9026: ROAMINGHOUSE
ROAMINGHOUSE is a dropper malware used by MirrorFace to extract and execute embedded payloads including UPPERCUT components.[1]
S1239: TONESHELL
S0439: Okrum
S0154: Cobalt Strike
Cobalt Strike is a commercial, full-featured, remote access tool that bills itself as “adversary simulation software designed to execute targeted attacks and emulate the post-exploitation actions of advanced threat actors”. Cobalt Strike’s interactive post-exploit capabilities cover the full range of ATT&CK tactics, all executed within a single, integrated system.[1]
In addition to its own capabilities, Cobalt Strike leverages the capabilities of other well-known tools such as Metasploit and Mimikatz.[1]
All related ATT&CK context
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 | 2.0 | Current bundle | 261f9fe20d73… | ||
| 19.1 | 2.0 | Older bundle | 261f9fe20d73… |
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]Deloitte Environment Awareness
Torello, A. & Guibernau, F. (n.d.). Environment Awareness. Retrieved September 13, 2024.
Open source URL - [2]Sans Virtual Jan 2016
Keragala, D. (2016, January 16). Detecting Malware and Sandbox Evasion Techniques. Retrieved April 17, 2019.
Open source URL - [3]Unit 42 Sofacy Nov 2018
Falcone, R., Lee, B.. (2018, November 20). Sofacy Continues Global Attacks and Wheels Out New ‘Cannon’ Trojan. Retrieved April 23, 2019.
Open source URL - [4]FireEye FIN7 April 2017
Carr, N., et al. (2017, April 24). FIN7 Evolution and the Phishing LNK. Retrieved April 24, 2017.
Open source URL - [5]mitre-attackT1497.002Open source URL
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