User Training involves educating employees and contractors on recognizing, reporting, and preventing cyber threats that rely on human interaction, such as phishing, social engineering, and other manipulative techniques. Comprehensive training programs create a human firewall by empowering users to be an active component of the organization's cybersecurity defenses. This mitigation can be implemented through the following measures: Create Comprehensive Training Programs: - Design training modules tailored to the organization's risk profile, covering topics such as phishing, password management, and incident reporting. - Provide role-specific training for high-risk employees, such as helpdesk staff or executives. Use Simulated Exercises: - Conduct phishing simulations to measure user susceptibility and provide targeted follow-up training. - Run social engineering drills to evaluate employ…
MITRE mitigation sourceAdversaryGraph public intelligence page
This page is part of Threat Matrix, the public browser workspace for the main AdversaryGraph platform. Use it for ATT&CK pivots, actor and technique context, similarity leads, detection coverage review, and analyst-ready investigation paths.
Validation disclaimer: TTP overlap, actor similarity, generated summaries, and coverage findings are investigation leads, not attribution proof or operational validation without analyst review.
Main AdversaryGraph project Documentation Malware Analysis GitHub
Multi-Factor Authentication Interception
Adversaries may target multi-factor authentication (MFA) mechanisms, (i.e., smart cards, token generators, etc.) to gain access to credentials that can be used to access systems, services, and network resources. Use of MFA is recommended and provides a higher level of security than usernames and passwords alone, but organizations should be aware of techniques that could be used to intercept and bypass these security mechanisms. If a smart card is used for multi-factor authentication, then a keylogger will need to be used to obtain the password associated with a smart card during normal use. With both an inserted card and access to the smart card password, an adversary can connect to a network resource using the infected system to proxy the authentication with the inserted hardware token. Adversaries may also employ a keylogger to similarly target other hardware tokens, such as RSA SecurID. Capturing token input (including a user's personal identification code) may provide temporary access (i.e. replay the one-time passcode until the next value rollover) as well as possibly enabling adversaries to reliably predict future authentication values (given access to both the algorithm and any seed values used to generate appended temporary codes). Other methods of MFA may be intercepted and used by an adversary to authenticate. It is common for one-time codes to be sent via out-of-band communications (email, SMS). If the device and/or service is not secured, then it may be vulnerable to interception. Service providers can also be targeted: for example, an adversary may compromise an SMS messaging service in order to steal MFA codes sent to users’ phones.
Open detection, hunting, mitigation, and evidence workspace
Detection logic
Detecting use of proxied smart card connections by an adversary may be difficult because it requires the token to be inserted into a system; thus it is more likely to be in use by a legitimate user and blend in with other network behavior. Similar to Input Capture, keylogging activity can take various forms but can may be detected via installation of a driver, setting a hook, or usage of particular API calls associated with polling to intercept keystrokes.
Observed actors
Correlated CTI and IR reports
Cyber Knowledge context
Use these routes to move from the ATT&CK behavior into explanation, implementation, evidence handling, validation, and defensive operations. Relevance is generated from explicit identifiers/names and governed topic mappings; it is not attribution evidence.
Secure Code & Application Security · Governed topic match · 39/100Module 5 — Threat hunting
Blue Team & Defensive Security · Tactic learning route · 24/100Human, workload, pipeline, and emergency identity
Cloud Security · Tactic learning route · 24/100Disk, file-system, and persistence forensics
Digital Forensics & Incident Response (DFIR) · Tactic learning route · 24/100
MITRE mitigations
MITRE detection strategies and analytics
- AN0687 · Analytic 0687 — Behavior chain involving unexpected API calls to capture keyboard input, driver loads for keyloggers, or remote use of smart card authentication via logon sessions not initiated by local user interaction
- AN0688 · Analytic 0688 — Detection of unauthorized keylogger behavior through access to `/dev/input`, loading kernel modules (e.g., via insmod), or polling user input devices from non-user shells
- AN0689 · Analytic 0689 — Processes accessing TCC-protected input APIs or polling HID services without user interaction, or dynamically loaded keylogging frameworks using accessibility privileges