T1110: Brute Force
Adversaries may use brute force techniques to gain access to accounts when passwords are unknown or when password hashes are obtained.[1] Without knowledge of the password for an account or set of accounts, an adversary may systematically guess the password using a repetitive or iterative mechanism.[2] Brute forcing passwords can take place via interaction with a service that will check the validity of those credentials or offline against previously acquired credential data, such as password hashes.
Brute forcing credentials may take place at various points during a breach. For example, adversaries may attempt to brute force access to Valid Accounts within a victim environment leveraging knowledge gathered from other post-compromise behaviors such as OS Credential Dumping, Account Discovery, or Password Policy Discovery. Adversaries may also combine brute forcing activity with behaviors such as External Remote Services as part of Initial Access.
If an adversary guesses the correct password but fails to login to a compromised account due to location-based conditional access policies, they may change their infrastructure until they match the victim’s location and therefore bypass those policies.[3]
Analyst context for executives and security teams
Brute Force matters because it turns weak, reused, or poorly governed credentials into a direct path to valid account access across cloud, SaaS, identity providers, endpoints, network devices, ESXi, and container environments. For leaders, this is less a “password problem” than a resilience and identity assurance problem: if authentication telemetry, lockout policies, MFA, and account lifecycle controls are inconsistent, attackers may have many places to test credentials with limited visibility.
Executive priority
Treat T1110 as a priority control-validation area for identity security, remote access exposure, cloud access, and audit readiness. The ATT&CK relationships show this behavior is broad enough to appear across espionage, financially motivated, and critical infrastructure-related reporting, including a campaign associated with disruption of Ukrainian electric power substations. Executives should ask whether high-value accounts, external services, identity providers, SaaS, IaaS, and administrative interfaces are protected by MFA, sane account use policies, strong password policies, and accountable user lifecycle management.
Technical view
SOC and IR teams should validate coverage around credential-access activity rather than relying on a single failed-login rule. ATT&CK provides no official detection text for T1110, but the related detection strategy DET0463 points to brute force authentication failures with multi-platform log correlation. Detection engineering should distinguish single-account guessing, password spraying across many accounts, credential stuffing using reused credentials, and offline password cracking after credential material such as hashes is obtained. Investigations should also consider related context from the description: OS Credential Dumping, Account Discovery, Password Policy Discovery, External Remote Services, and attempts to bypass location-based conditional access by changing infrastructure.
Likely telemetry
- Identity provider authentication success and failure logs
- SaaS and office suite sign-in logs
- IaaS control plane authentication logs
- VPN, remote access, and external service authentication logs where available
- Windows, Linux, macOS, ESXi, network device, and container platform authentication logs
Detection direction
- Validate correlation across platforms, not only domain controller or endpoint logs, because the listed platforms include identity providers, SaaS, IaaS, ESXi, containers, network devices, and traditional operating systems.
- Tune for both high-volume failures against one account and low-and-slow spraying across many accounts to reduce blind spots created by account lockout avoidance.
- Track successful login after repeated failures, unusual source changes, or conditional access denials followed by later success from a different location or infrastructure.
- Separate likely user error from attack patterns by considering time window, account count, password reset activity, source diversity, asset criticality, and whether attempts target privileged or dormant accounts.
- For offline cracking, look for upstream evidence such as credential material access or OS Credential Dumping rather than expecting authentication-failure telemetry to show the cracking itself.
Mitigation priorities
- Prioritize Multi-factor Authentication for critical, privileged, remote, cloud, SaaS, and identity-provider-backed access paths.
- Enforce Account Use Policies such as lockout, login restrictions, and inactivity controls with care to avoid avoidable business disruption from denial-of-service via lockouts.
- Strengthen Password Policies to reduce guessability and reuse risk while validating that policies apply consistently across cloud, SaaS, endpoints, network devices, ESXi, and container-related authentication surfaces.
- Improve User Account Management by removing stale accounts, limiting privileges, and ensuring account creation, modification, and deactivation are governed and auditable.
- Use detection results to identify control gaps: systems with missing logs, accounts without MFA, inconsistent lockout behavior, and externally reachable services with weak authentication protections.
Analyst notes and limits
The most useful Glexia assessment for T1110 is a control-and-telemetry coverage review: where can credentials be tested, what logs prove it, which accounts are protected by MFA and account policies, and where can an attacker avoid lockouts by distributing attempts. Relationship context to multiple groups and campaigns supports broad relevance, but local risk depends on exposed services, identity architecture, password practices, and logging maturity.
ATT&CK does not provide official detection guidance for this object in the supplied fields. The take is therefore based on the official description, listed platforms and tactic, the DET0463 detection-strategy relationship, mitigation relationships M1018, M1027, M1032, and M1036, and sub-technique relationships T1110.001 through T1110.004. It does not assert active exploitation, customer exposure, attribution, or guaranteed detection coverage.
Brute Force
Adversaries may use brute force techniques to gain access to accounts when passwords are unknown or when password hashes are obtained.[1] Without knowledge of the password for an account or set of accounts, an adversary may systematically guess the password using a repetitive or iterative mechanism.[2] Brute forcing passwords can take place via interaction with a service that will check the validity of those credentials or offline against previously acquired credential data, such as password hashes.
Brute forcing credentials may take place at various points during a breach. For example, adversaries may attempt to brute force access to Valid Accounts within a victim environment leveraging knowledge gathered from other post-compromise behaviors such as OS Credential Dumping, Account Discovery, or Password Policy Discovery. Adversaries may also combine brute forcing activity with behaviors such as External Remote Services as part of Initial Access.
If an adversary guesses the correct password but fails to login to a compromised account due to location-based conditional access policies, they may change their infrastructure until they match the victim’s location and therefore bypass those policies.[3]
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 | T1110.004 | Credential Stuffing Sub-technique | Credential Stuffing subtechnique of this object. |
| Enterprise | T1110.002 | Password Cracking Sub-technique | Password Cracking subtechnique of this object. |
| Enterprise | T1110.001 | Password Guessing Sub-technique | Password Guessing subtechnique of this object. |
| Enterprise | T1110.003 | Password Spraying Sub-technique | Password Spraying subtechnique of this object. |
Groups, software, and campaigns
G0117: Fox Kitten
Fox Kitten is threat actor with a suspected nexus to the Iranian government that has been active since at least 2017 against entities in the Middle East, North Africa, Europe, Australia, and North America. Fox Kitten has targeted multiple industrial verticals including oil and gas, technology, government, defense, healthcare, manufacturing, and engineering.[1][2][3][4]
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]
G1003: Ember Bear
Ember Bear is a Russian state-sponsored cyber espionage group that has been active since at least 2020, linked to Russia's General Staff Main Intelligence Directorate (GRU) 161st Specialist Training Center (Unit 29155).[1] Ember Bear has primarily focused operations against Ukrainian government and telecommunication entities, but has also operated against critical infrastructure entities in Europe and the Americas.[2] Ember Bear conducted the WhisperGate destructive wiper attacks against Ukraine in early 2022.[3][4][1] There is some confusion as to whether Ember Bear overlaps with another Russian-linked entity referred to as Saint Bear. At present available evidence strongly suggests these are distinct activities with different behavioral profiles.[2][5]
G0010: Turla
Turla is a cyber espionage threat group that has been attributed to Russia's Federal Security Service (FSB). They have compromised victims in over 50 countries since at least 2004, spanning a range of industries including government, embassies, military, education, research and pharmaceutical companies. Turla is known for conducting watering hole and spearphishing campaigns, and leveraging in-house tools and malware, such as Uroburos.[1][2][3][4][5]
G0105: DarkVishnya
DarkVishnya is a financially motivated threat actor targeting financial institutions in Eastern Europe. In 2017-2018 the group attacked at least 8 banks in this region.[1]
G0053: FIN5
FIN5 is a financially motivated threat group that has targeted personally identifiable information and payment card information. The group has been active since at least 2008 and has targeted the restaurant, gaming, and hotel industries. The group is made up of actors who likely speak Russian. [1] [2] [3]
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]
G0082: APT38
APT38 is a North Korean state-sponsored threat group that specializes in financial cyber operations; it has been attributed to the Reconnaissance General Bureau.[1] Active since at least 2014, APT38 has targeted banks, financial institutions, casinos, cryptocurrency exchanges, SWIFT system endpoints, and ATMs in at least 38 countries worldwide. Significant operations include the 2016 Bank of Bangladesh heist, during which APT38 stole $81 million, as well as attacks against Bancomext [2] and Banco de Chile [2]; some of their attacks have been destructive.[1][2][3][4]
North Korean group definitions are known to have significant overlap, and some security researchers report all North Korean state-sponsored cyber activity under the name Lazarus Group instead of tracking clusters or subgroups.
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]
G1030: Agrius
G0087: APT39
APT39 is one of several names for cyber espionage activity conducted by the Iranian Ministry of Intelligence and Security (MOIS) through the front company Rana Intelligence Computing since at least 2014. APT39 has primarily targeted the travel, hospitality, academic, and telecommunications industries in Iran and across Asia, Africa, Europe, and North America to track individuals and entities considered to be a threat by the MOIS.[1][2][3][4][5]
G0035: Dragonfly
Dragonfly is a cyber espionage group that has been attributed to Russia's Federal Security Service (FSB) Center 16.[1][2] Active since at least 2010, Dragonfly has targeted defense and aviation companies, government entities, companies related to industrial control systems, and critical infrastructure sectors worldwide through supply chain, spearphishing, and drive-by compromise attacks.[3][4][5][6][7][8][9]
S0220: Chaos
S0572: Caterpillar WebShell
Caterpillar WebShell is a self-developed Web Shell tool created by the group Volatile Cedar.[1]
S0599: Kinsing
S0378: PoshC2
PoshC2 is an open source remote administration and post-exploitation framework that is publicly available on GitHub. The server-side components of the tool are primarily written in Python, while the implants are written in PowerShell. Although PoshC2 is primarily focused on Windows implantation, it does contain a basic Python dropper for Linux/macOS.[1]
S0650: QakBot
S0583: Pysa
S0488: CrackMapExec
CrackMapExec, or CME, is a post-exploitation tool developed in Python and designed for penetration testing against networks. CrackMapExec collects Active Directory information to conduct lateral movement through targeted networks.[1]
C0022: Operation Dream Job
Operation Dream Job was a cyber espionage operation likely conducted by Lazarus Group that targeted the defense, aerospace, government, and other sectors in the United States, Israel, Australia, Russia, and India. In at least one case, the cyber actors tried to monetize their network access to conduct a business email compromise (BEC) operation. In 2020, security researchers noted overlapping TTPs, to include fake job lures and code similarities, between Operation Dream Job, Operation North Star, and Operation Interception; by 2022 security researchers described Operation Dream Job as an umbrella term covering both Operation Interception and Operation North Star.[1][2][3][4]
C0025: 2016 Ukraine Electric Power Attack
2016 Ukraine Electric Power Attack was a Sandworm Team campaign during which they used Industroyer malware to target and disrupt distribution substations within the Ukrainian power grid. This campaign was the second major public attack conducted against Ukraine by Sandworm Team.[1][2]
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 (1)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.1 | 2.8 | Current bundle | 7dd9d94dbd63… |
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]
TrendMicro Pawn Storm Dec 2020
Hacquebord, F., Remorin, L. (2020, December 17). Pawn Storm’s Lack of Sophistication as a Strategy. Retrieved January 13, 2021.
Open source URL -
[2]
Dragos Crashoverride 2018
Joe Slowik. (2018, October 12). Anatomy of an Attack: Detecting and Defeating CRASHOVERRIDE. Retrieved December 18, 2020.
Open source URL -
[3]
ReliaQuest Health Care Social Engineering Campaign 2024
Hayden Evans. (2024, April 4). Health Care Social Engineering Campaign. Retrieved May 22, 2025.
Open source URL -
[4]
mitre-attack T1110Open source URL
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