T1557: Adversary-in-the-Middle
Adversaries may attempt to position themselves between two or more networked devices using an adversary-in-the-middle (AiTM) technique to support follow-on behaviors such as Network Sniffing, Transmitted Data Manipulation, or replay attacks (Exploitation for Credential Access). By abusing features of common networking protocols that can determine the flow of network traffic (e.g. ARP, DNS, LLMNR, etc.), adversaries may force a device to communicate through an adversary controlled system so they can collect information or perform additional actions.[1]
For example, adversaries may manipulate victim DNS settings to enable other malicious activities such as preventing/redirecting users from accessing legitimate sites and/or pushing additional malware.[2][3][4] Adversaries may also manipulate DNS and leverage their position in order to intercept user credentials, including access tokens (Steal Application Access Token) and session cookies (Steal Web Session Cookie).[5][6] Downgrade Attacks can also be used to establish an AiTM position, such as by negotiating a less secure, deprecated, or weaker version of communication protocol (SSL/TLS) or encryption algorithm.[7][8][9]
Adversaries may also leverage the AiTM position to attempt to monitor and/or modify traffic, such as in Transmitted Data Manipulation. Adversaries can setup a position similar to AiTM to prevent traffic from flowing to the appropriate destination, potentially to impair defenses and/or in support of a Network Denial of Service.
Security context for executives and security teams
T1557: Adversary-in-the-Middle describes Adversaries may attempt to position themselves between two or more networked devices using an adversary-in-the-middle (AiTM) technique to support follow-on behaviors such as [Network Sniffing](https://attack.mitre.org/techniques/T1040), [Transmitted Data Manipulation](https://attack.mitre.org/techniques/T1565/002), or replay attacks ([Exploitation for Credential Access](https://attack.mitre.org/techniques/T1212)). By abusing features of common networking protocols that can determine the flow of network traffic (e.g...
Executive priority
T1557: Adversary-in-the-Middle 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 T1557: Adversary-in-the-Middle by reviewing the official ATT&CK relationships, mapped tactics (credential-access, collection), supported platforms (Linux, macOS, Network Devices, Windows), and available local telemetry before making detection or mitigation decisions.
Likely telemetry
- Official ATT&CK relationships and object metadata
- Identity, privilege, and authentication events
- Network, endpoint, and security-tool telemetry
Detection direction
- Validate whether T1557: Adversary-in-the-Middle 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.
Adversary-in-the-Middle
Adversaries may attempt to position themselves between two or more networked devices using an adversary-in-the-middle (AiTM) technique to support follow-on behaviors such as Network Sniffing, Transmitted Data Manipulation, or replay attacks (Exploitation for Credential Access). By abusing features of common networking protocols that can determine the flow of network traffic (e.g. ARP, DNS, LLMNR, etc.), adversaries may force a device to communicate through an adversary controlled system so they can collect information or perform additional actions.[1]
For example, adversaries may manipulate victim DNS settings to enable other malicious activities such as preventing/redirecting users from accessing legitimate sites and/or pushing additional malware.[2][3][4] Adversaries may also manipulate DNS and leverage their position in order to intercept user credentials, including access tokens (Steal Application Access Token) and session cookies (Steal Web Session Cookie).[5][6] Downgrade Attacks can also be used to establish an AiTM position, such as by negotiating a less secure, deprecated, or weaker version of communication protocol (SSL/TLS) or encryption algorithm.[7][8][9]
Adversaries may also leverage the AiTM position to attempt to monitor and/or modify traffic, such as in Transmitted Data Manipulation. Adversaries can setup a position similar to AiTM to prevent traffic from flowing to the appropriate destination, potentially to impair defenses and/or in support of a Network Denial of Service.
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 | T1557.003 | DHCP SpoofingSub-technique | DHCP Spoofing subtechnique of this object. |
| Enterprise | T1557.002 | ARP Cache PoisoningSub-technique | ARP Cache Poisoning subtechnique of this object. |
| Enterprise | T1557.001 | Name Resolution Poisoning and SMB RelaySub-technique | Name Resolution Poisoning and SMB Relay subtechnique of this object. |
| Enterprise | T1557.004 | Evil TwinSub-technique | Evil Twin subtechnique of this object. |
Groups, software, and campaigns
G0094: Kimsuky
Kimsuky is a Democratic People's Republic of Korea (DPRK)-based cyber espionage group that has been active since at least 2012. The group initially targeted South Korean government agencies, think tanks, and subject-matter experts in various fields. Its operations expanded to include the United Nations and organizations in the government, education, business services, and manufacturing sectors across the United States, Japan, Russia, and Europe. Kimsuky has focused collection on foreign policy and national security issues tied to the Korean Peninsula, nuclear policy, and sanctions. Kimsuky operations have overlapped with those of other North Korean state-sponsored cyber espionage actors as a result of ad hoc collaborations or other limited resource sharing.[1][2][3][4][5][6]
Kimsuky was assessed to be responsible for the 2014 Korea Hydro & Nuclear Power Co. compromise; other notable campaigns include Operation STOLEN PENCIL (2018), Operation Kabar Cobra (2019), and Operation Smoke Screen (2019).[7][8][9] In 2023, Kimsuky was observed using commercial large language models (LLMs) to assist with vulnerability research, scripting, social engineering and reconnaissance.[10]
DPRK threat actor cluster boundaries overlap in open source reporting, with some security researchers consolidating all attributed North Korean state-sponsored cyber activity under Lazarus Group, rather than tracking operationally distinct subgroups.
G0129: Mustang Panda
Mustang Panda is a China-based cyber espionage threat actor that has been conducting operations since at least 2012. Mustang Panda has been known to use tailored phishing lures and decoy documents to deliver malicious payloads. Mustang Panda has targeted government, diplomatic, and non-governmental organizations, including think tanks, religious institutions, and research entities, across the United States, Europe, and Asia, with notable activity in Russia, Mongolia, Myanmar, Pakistan, and Vietnam. [1][2][3][4][5][6][7][8][9][10][11][12][13]
G1041: Sea Turtle
Sea Turtle is a Türkiye-linked threat actor active since at least 2017 performing espionage and service provider compromise operations against victims in Asia, Europe, and North America. Sea Turtle is notable for targeting registrars managing ccTLDs and complex DNS-based intrusions where the threat actor compromised DNS providers to hijack DNS resolution for ultimate victims, enabling Sea Turtle to spoof log in portals and other applications for credential collection.[1][2][3][4]
S1188: Line Runner
Line Runner is a persistent backdoor and web shell allowing threat actors to upload and execute arbitrary Lua scripts. Line Runner is associated with the ArcaneDoor campaign.[1][2]
S0281: Dok
Dok is a Trojan application disguised as a .zip file that is able to collect user credentials and install a malicious proxy server to redirect a user's network traffic (i.e. Adversary-in-the-Middle).[1][2][3]
S1131: NPPSPY
NPPSPY is an implementation of a theoretical mechanism first presented in 2004 for capturing credentials submitted to a Windows system via a rogue Network Provider API item. NPPSPY captures credentials following submission and writes them to a file on the victim system for follow-on exfiltration.[1][2]
S9003: evilginx2
S9044: Kali365
Kali365 is a Phishing-as-a-Service (PHaaS) kit first observed in April 2026 that generates victim-targeted lures across multiple operating systems to induce users into copying and pasting actor-controlled commands for local execution.[1][2][3][4] Kali365 incorporates on-demand device code generation and mirrors the copy-paste execution tradecraft associated with ClickFix. [3] Operators have used Kali365 to harvest victims' OAuth tokens and session cookies through adversary-in-the-middle (AiTM) interception, enabling account takeover.[1][5][2][3][4] Kali365 PHaaS was first observed in April 2026.[1] Kali365 has also been affiliated with other branding to include Octopi365 and Freedom365.[3]
C0046: ArcaneDoor
ArcaneDoor is a campaign targeting networking devices from Cisco and other vendors between July 2023 and April 2024, primarily focused on government and critical infrastructure networks. ArcaneDoor is associated with the deployment of the custom backdoors Line Runner and Line Dancer. ArcaneDoor is attributed to a group referred to as UAT4356 or STORM-1849, and is assessed to be a state-sponsored campaign.[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(2)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.2 | 2.5 | Current bundle | 0dd83b905042… | ||
| 19.1 | 2.5 | Older bundle | 0dd83b905042… |
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]Rapid7 MiTM Basics
Rapid7. (n.d.). Man-in-the-Middle (MITM) Attacks. Retrieved March 2, 2020.
Open source URL - [2]ttint_rat
Tu, L. Ma, Y. Ye, G. (2020, October 1). Ttint: An IoT Remote Access Trojan spread through 2 0-day vulnerabilities. Retrieved October 28, 2021.
Open source URL - [3]dns_changer_trojans
Abendan, O. (2012, June 14). How DNS Changer Trojans Direct Users to Threats. Retrieved October 28, 2021.
Open source URL - [4]ad_blocker_with_miner
Kuzmenko, A.. (2021, March 10). Ad blocker with miner included. Retrieved October 28, 2021.
Open source URL - [5]volexity_0day_sophos_FW
Adair, S., Lancaster, T., Volexity Threat Research. (2022, June 15). DriftingCloud: Zero-Day Sophos Firewall Exploitation and an Insidious Breach. Retrieved July 1, 2022.
Open source URL - [6]Token tactics
Microsoft Incident Response. (2022, November 16). Token tactics: How to prevent, detect, and respond to cloud token theft. Retrieved December 26, 2023.
Open source URL - [7]mitm_tls_downgrade_att
praetorian Editorial Team. (2014, August 19). Man-in-the-Middle TLS Protocol Downgrade Attack. Retrieved December 8, 2021.
Open source URL - [8]taxonomy_downgrade_att_tls
Alashwali, E. S., Rasmussen, K. (2019, January 26). What's in a Downgrade? A Taxonomy of Downgrade Attacks in the TLS Protocol and Application Protocols Using TLS. Retrieved December 7, 2021.
Open source URL - [9]tlseminar_downgrade_att
Team Cinnamon. (2017, February 3). Downgrade Attacks. Retrieved December 9, 2021.
Open source URL - [10]mitre-attackT1557Open source URL
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