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.
64th pctamong all ATT&CK techniques for number of groups
3 groups have been recorded using this technique. Newest first; each entry carries MITRE’s procedure text and a link to the group’s full record. Click a name to filter the rules below.
Modified DNS records at service providers to redirect traffic from legitimate resources to Sea Turtle-controlled servers to enable adversary-in-the-middle attacks for credential capture.12
Included interception of HTTP traffic to victim devices to identify and parse command and control information sent to the device.1
2023–2024
All 1 campaigns for this technique
5 software entries are documented implementing this technique. MITRE files each as a tool or as malware; newest first, then by how many groups carry them.
Has created obfuscated phishing landing pages that act as an adversary in the middle infrastructure that intercepts communications between the victim host and legitimate services to steal credentials and user sessions.123
Has the ability to act as an adversary-in-the-middle (AiTM) relay between a legitimate website and a phished user to capture all transmitted data including usernames, passwords, authentication tokens, and session cookies and tokens.1234
Intercepts HTTP requests to the victim Cisco ASA, looking for a request with a 32-character, victim dependent parameter. If that parameter matches a value in the malware, a contained payload is then written to a Lua script and executed.1
Opens a new network listener for the mpnotify.exe process that is typically contacted by the Winlogon process in Windows. A new, alternative RPC channel is set up with a malicious DLL recording plaintext credentials entered into Winlogon, effectively intercepting and redirecting the logon information.1
MITRE names one behaviour worth catching for this technique and breaks it into 4 analytics, one per platform. Each carries the log sources it needs and the fields you tune per environment.
Detect Adversary-in-the-Middle via Network and Configuration Anomalies
Enterprise
4 platforms
AN0823 · Windows
Detects suspicious DNS/ARP poisoning attempts, unauthorized modifications to registry/network configuration, or abnormal TLS downgrade activity. Correlates changes in system configuration with subsequent unusual network flows or authentication events.
Log sources
The data this analytic draws on. You do not need every component — each one you already collect covers part of it. Each links to its ATT&CK record.
MITRE calls these the analytic’s mutable elements: the thresholds and filters you set for your own environment.
Field
What you tune
MonitoredRegistryPaths
Specific network stack and DNS registry keys that vary by enterprise configuration.
DowngradeCipherList
List of weak/legacy ciphers tuned per environment for TLS downgrade detection.
TimeWindow
Correlation period between config changes and abnormal network connections.
AN0824 · Linux
Detects unauthorized edits to /etc/hosts, /etc/resolv.conf, or suspicious ARP broadcasts. Correlates file modifications with subsequent unexpected network sessions or service creation.
Log sources
The data this analytic draws on. You do not need every component — each one you already collect covers part of it. Each links to its ATT&CK record.
Unexpected ARP replies or DNS responses inconsistent with authoritative servers
Tunable fields
MITRE calls these the analytic’s mutable elements: the thresholds and filters you set for your own environment.
Field
What you tune
MonitoredFiles
List of system files shaping traffic flow (hosts, resolv.conf, PAM modules).
ARPThreshold
Rate/volume thresholds for ARP/DNS anomalies tuned per subnet.
AN0825 · macOS
Detects unauthorized edits to system configuration profiles, unexpected certificate trust changes, or abnormal ARP/DNS patterns indicative of interception.
Log sources
The data this analytic draws on. You do not need every component — each one you already collect covers part of it. Each links to its ATT&CK record.
Disable legacy network protocols that may be used to intercept network traffic if applicable, especially those that are not needed within an environment.
Ensure that all wired and/or wireless traffic is encrypted appropriately. Use best practices for authentication protocols, such as Kerberos, and ensure web traffic that may contain credentials is protected by SSL/TLS.
Use network appliances and host-based security software to block network traffic that is not necessary within the environment, such as legacy protocols that may be leveraged for AiTM conditions.
Network intrusion detection and prevention systems that can identify traffic patterns indicative of AiTM activity can be used to mitigate activity at the network level.
Network segmentation can be used to isolate infrastructure components that do not require broad network access. This may mitigate, or at least alleviate, the scope of AiTM activity.
Train users to be suspicious about certificate errors. Adversaries may use their own certificates in an attempt to intercept HTTPS traffic. Certificate errors may arise when the application’s certificate does not match the one expected by the host.
Adversary-in-the-Middle detections T1557
12 rules are mapped to this technique.
Top 21%of all ATT&CK techniques for number of rules
Showing 1-12 of 12 rules
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Detects sign-in attempts in Azure/Entra ID logs where the user agent contains "axios",
indicating po (...)