T1082: System Information Discovery
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 this information to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions. This behavior is distinct from Local Storage Discovery which is an adversary's discovery of local drive, disks and/or volumes.
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. Adversaries may leverage a Network Device CLI on network devices to gather detailed system information (e.g. show version).[1] On ESXi servers, threat actors may gather system information from various esxcli utilities, such as `system hostname get` and `system version get`.[2][3]
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.[4][5][6]
System Information Discovery combined with information gathered from other forms of discovery and reconnaissance can drive payload development and concealment.[7][8]
Analyst context for executives and security teams
System Information Discovery is the attacker behavior of checking what kind of machine, network device, hypervisor, or cloud instance they have reached before deciding what to do next. For leaders, this matters because it is often an early decision point in an intrusion: the information collected can influence payload choice, concealment, lateral movement planning, or whether the actor continues at all.
Executive priority
Treat this as a coverage-validation technique rather than a standalone high-severity event. It appears across many ATT&CK relationships and applies to Windows, Linux, macOS, ESXi, network devices, and IaaS environments, so the business question is whether SOC, cloud, endpoint, and network-device logging can show who queried system details, from where, and in what session context. It is especially relevant to resilience planning for cloud workloads, virtualization platforms, managed network infrastructure, and regulated environments where audit evidence depends on proving visibility into discovery activity.
Technical view
ATT&CK provides no official detection text for T1082, but it does identify a related detection strategy: DET0525, System Discovery via Native and Remote Utilities. Detection engineering should validate visibility into native system-information utilities, privileged macOS configuration queries, network device CLI activity such as version discovery, ESXi management utility usage, and authenticated IaaS API calls that return instance or VM metadata. Because legitimate administrators and management tools also perform these actions, detections should emphasize unusual user, host, privilege, timing, remote access path, sequence with other discovery activity, or execution from unexpected processes rather than command or API use alone.
Likely telemetry
- Endpoint process creation and command-line logging for native system information utilities
- macOS audit or endpoint telemetry for privileged configuration queries
- Linux and Windows host logs showing process execution and user context
- ESXi management and shell/CLI logs for system and version queries
- Network device command accounting, administrative session logs, and configuration/CLI audit trails
Detection direction
- Validate whether DET0525-style coverage exists across endpoints, cloud control planes, ESXi, and network devices rather than only traditional workstations and servers.
- Tune detections around context: newly observed accounts, non-administrative users, unusual source systems, scripted or remote execution, abnormal time windows, or discovery clustered with other reconnaissance behavior.
- Account for high false-positive potential from inventory agents, vulnerability scanners, configuration management, help desk activity, and cloud automation.
- Confirm cloud detections distinguish routine inventory collection from unusual API use by unexpected identities, regions, workloads, or service accounts.
- For network devices and ESXi, verify that administrative command logging is actually retained and forwarded; these platforms are common blind spots compared with endpoint telemetry.
Mitigation priorities
- Prioritize least-privilege access for administrative interfaces, cloud APIs, ESXi management, and network device CLIs so routine users and workloads cannot broadly enumerate system details.
- Ensure logging is enabled and centrally retained for endpoint process activity, cloud API calls, ESXi administration, and network device command sessions.
- Baseline approved inventory, asset management, vulnerability management, and configuration management activity to reduce false positives and expose abnormal discovery.
- Harden and monitor remote administration paths because this technique often becomes meaningful when paired with authenticated access or privileged sessions.
- Use asset inventory and patch/status management defensively: if adversaries can query versions and patch levels, defenders should be able to prove the same data is complete and current.
Analyst notes and limits
The object is an enterprise ATT&CK technique in the Discovery tactic with broad platform coverage: ESXi, IaaS, Linux, macOS, network devices, and Windows. MITRE’s description emphasizes operating system, hardware, version, patch, hotfix, service pack, architecture, ESXi, network device CLI, and cloud instance/VM information. Relationship data shows this behavior is used by multiple campaigns and groups and is detected by DET0525, but the supplied object does not provide a detailed official detection analytic.
Official detection guidance is not provided for this ATT&CK object, so detection recommendations are derived from the official description, platforms, external references, and the DET0525 relationship. This take does not assert active exploitation, current targeting, or guaranteed detection coverage. Local baselines, logging configuration, identity model, and administrative tooling are required to determine severity and alert logic.
System Information Discovery
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 this information to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions. This behavior is distinct from Local Storage Discovery which is an adversary's discovery of local drive, disks and/or volumes.
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. Adversaries may leverage a Network Device CLI on network devices to gather detailed system information (e.g. show version).[1] On ESXi servers, threat actors may gather system information from various esxcli utilities, such as `system hostname get` and `system version get`.[2][3]
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.[4][5][6]
System Information Discovery combined with information gathered from other forms of discovery and reconnaissance can drive payload development and concealment.[7][8]
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.
Groups, software, and campaigns
G0124: Windigo
G1043: BlackByte
BlackByte is a ransomware threat actor operating since at least 2021. BlackByte is associated with several versions of ransomware also labeled BlackByte Ransomware. BlackByte ransomware operations initially used a common encryption key allowing for the development of a universal decryptor, but subsequent versions such as BlackByte 2.0 Ransomware use more robust encryption mechanisms. BlackByte is notable for operations targeting critical infrastructure entities among other targets across North America.[1][2][3][4][5]
G0049: OilRig
OilRig is a suspected Iranian threat group that has targeted Middle Eastern and international victims since at least 2014. The group has targeted a variety of sectors, including financial, government, energy, chemical, and telecommunications. It appears the group carries out supply chain attacks, leveraging the trust relationship between organizations to attack their primary targets. The group works on behalf of the Iranian government based on infrastructure details that contain references to Iran, use of Iranian infrastructure, and targeting that aligns with nation-state interests.[1][2][3][4][5][6][7]
G0128: ZIRCONIUM
G0096: APT41
APT41 is a threat group that researchers have assessed as Chinese state-sponsored espionage group that also conducts financially-motivated operations. Active since at least 2012, APT41 has been observed targeting various industries, including but not limited to healthcare, telecom, technology, finance, education, retail and video game industries in 14 countries.[1] Notable behaviors include using a wide range of malware and tools to complete mission objectives. APT41 overlaps at least partially with public reporting on groups including BARIUM and Winnti Group.[2][3]
G0108: Blue Mockingbird
Blue Mockingbird is a cluster of observed activity involving Monero cryptocurrency-mining payloads in dynamic-link library (DLL) form on Windows systems. The earliest observed Blue Mockingbird tools were created in December 2019.[1]
G1001: HEXANE
HEXANE is a cyber espionage threat group that has targeted oil & gas, telecommunications, aviation, and internet service provider organizations since at least 2017. Targeted companies have been located in the Middle East and Africa, including Israel, Saudi Arabia, Kuwait, Morocco, and Tunisia. HEXANE's TTPs appear similar to APT33 and OilRig but due to differences in victims and tools it is tracked as a separate entity.[1][2][3][4]
S0339: Micropsia
S0385: njRAT
S1111: DarkGate
DarkGate first emerged in 2018 and has evolved into an initial access and data gathering tool associated with various criminal cyber operations. Written in Delphi and named "DarkGate" by its author, DarkGate is associated with credential theft, cryptomining, cryptotheft, and pre-ransomware actions.[1] DarkGate use increased significantly starting in 2022 and is under active development by its author, who provides it as a Malware-as-a-Service offering.[2]
S1242: Qilin
Qilin is a ransomware family operated as a ransomware-as-a-service (RaaS) that has been active since at least 2022. It includes variants written in Go and Rust capable of targeting Windows, Linux, and VMware ESXi environments. Qilin shares functionality overlaps with Black Basta, REvil, and BlackCat ransomware. Qilin affiliates have targeted multiple entities worldwide with the majority of victims in the US, France, Canada, and the UK, primarily in the manufacturing, technology, financial services, and healthcare sectors.[1][2][3][4][5]
S1249: HexEval Loader
HexEval Loader is a hex-encoded loader that collects host data, decodes follow-on scripts and acts as a downloader for the BeaverTail malware. HexEval Loader was first reported in April 2025. HexEval Loader has previously been leveraged by North Korea-affiliated threat actors identified as Contagious Interview. HexEval Loader has been delivered to victims through code repository sites utilizing typosquatting naming conventions of various npm packages.[1][2][3]
S1245: InvisibleFerret
InvisibleFerret is a modular python malware that is leveraged for data exfiltration and remote access capabilities.[1][2][3] InvisibleFerret consists of four modules: main, payload, browser, and AnyDesk.[1] InvisibleFerret malware has been leveraged by North Korea-affiliated threat actors identified as DeceptiveDevelopment or Contagious Interview since 2023.[4][2][3][5] InvisibleFerret has historically been introduced to the victim environment through the use of the BeaverTail malware.[6][1][2][3][5]
S0266: TrickBot
TrickBot is a Trojan spyware program written in C++ that first emerged in September 2016 as a possible successor to Dyre. TrickBot was developed and initially used by Wizard Spider for targeting banking sites in North America, Australia, and throughout Europe; it has since been used against all sectors worldwide as part of "big game hunting" ransomware campaigns.[1][2][3][4]
S0553: MoleNet
S0388: YAHOYAH
YAHOYAH is a Trojan used by Tropic Trooper as a second-stage backdoor.[1]
S0464: SYSCON
S0130: Unknown Logger
Unknown Logger is a publicly released, free backdoor. Version 1.5 of the backdoor has been used by the actors responsible for the MONSOON campaign. [1]
S1039: Bumblebee
Bumblebee is a custom loader written in C++ that has been used by multiple threat actors, including possible initial access brokers, to download and execute additional payloads since at least March 2022. Bumblebee has been linked to ransomware operations including Conti, Quantum, and Mountlocker and derived its name from the appearance of "bumblebee" in the user-agent.[1][2][3]
C0060: Operation AkaiRyū
Operation AkaiRyū (Japanese for RedDragon) was a cyberespionage spearphishing campaign conducted by MirrorFace between June and September 2024 against entities in Japan and Central Europe. Operation AkaiRyū notably included the first reported targeting of a European entity by MirrorFace, as well as their use of UPPERCUT, which was thought to be exclusive to menuPass.[1][2]
C0001: Frankenstein
Frankenstein was described by security researchers as a highly-targeted campaign conducted by moderately sophisticated and highly resourceful threat actors in early 2019. The unidentified actors primarily relied on open source tools, including Empire. The campaign name refers to the actors' ability to piece together several unrelated open-source tool components.[1]
C0012: Operation CuckooBees
Operation CuckooBees was a cyber espionage campaign targeting technology and manufacturing companies in East Asia, Western Europe, and North America since at least 2019. Security researchers noted the goal of Operation CuckooBees, which was still ongoing as of May 2022, was likely the theft of proprietary information, research and development documents, source code, and blueprints for various technologies. Researchers assessed Operation CuckooBees was conducted by actors affiliated with Winnti Group, APT41, and BARIUM.[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 (1)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.1 | 3.0 | Current bundle | 5f2d907bcc26… |
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.
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[1]
US-CERT-TA18-106A
US-CERT. (2018, April 20). Alert (TA18-106A) Russian State-Sponsored Cyber Actors Targeting Network Infrastructure Devices. Retrieved October 19, 2020.
Open source URL -
[2]
Crowdstrike Hypervisor Jackpotting Pt 2 2021
Michael Dawson. (2021, August 30). Hypervisor Jackpotting, Part 2: eCrime Actors Increase Targeting of ESXi Servers with Ransomware. Retrieved March 26, 2025.
Open source URL -
[3]
Varonis
Jason Hill. (2023, February 8). VMware ESXi in the Line of Ransomware Fire. Retrieved March 26, 2025.
Open source URL -
[4]
Amazon Describe Instance
Amazon. (n.d.). describe-instance-information. Retrieved March 3, 2020.
Open source URL -
[5]
Google Instances Resource
Google. (n.d.). Rest Resource: instance. Retrieved March 3, 2020.
Open source URL -
[6]
Microsoft Virutal Machine API
Microsoft. (2019, March 1). Virtual Machines - Get. Retrieved October 8, 2019.
Open source URL -
[7]
OSX.FairyTale
Phile Stokes. (2018, September 20). On the Trail of OSX.FairyTale | Adware Playing at Malware. Retrieved August 24, 2021.
Open source URL -
[8]
20 macOS Common Tools and Techniques
Phil Stokes. (2021, February 16). 20 Common Tools & Techniques Used by macOS Threat Actors & Malware. Retrieved August 23, 2021.
Open source URL -
[9]
mitre-attack T1082Open source URL
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