Prevent the execution of unauthorized or malicious code on systems by implementing application control, script blocking, and other execution prevention mechanisms. This ensures that only trusted and authorized code is executed, reducing the risk of malware and unauthorized actions. This mitigation can be implemented through the following measures: Application Control: - Use Case: Use tools like AppLocker or Windows Defender Application Control (WDAC) to create whitelists of authorized applications and block unauthorized ones. On Linux, use tools like SELinux or AppArmor to define mandatory access control policies for application execution. - Implementation: Allow only digitally signed or pre-approved applications to execute on servers and endpoints. (e.g., `New-AppLockerPolicy -PolicyType Enforced -FilePath "C:\Policies\AppLocker.xml"`) Script Blocking: - Use Case: Use script control me…
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
Native API
Adversaries may interact with the native OS application programming interface (API) to execute behaviors. Native APIs provide a controlled means of calling low-level OS services within the kernel, such as those involving hardware/devices, memory, and processes. These native APIs are leveraged by the OS during system boot (when other system components are not yet initialized) as well as carrying out tasks and requests during routine operations. Adversaries may abuse these OS API functions as a means of executing behaviors. Similar to Command and Scripting Interpreter, the native API and its hierarchy of interfaces provide mechanisms to interact with and utilize various components of a victimized system. Native API functions (such as NtCreateProcess) may be directed invoked via system calls / syscalls, but these features are also often exposed to user-mode applications via interfaces and libraries. For example, functions such as the Windows API CreateProcess() or GNU fork() will allow programs and scripts to start other processes. This may allow API callers to execute a binary, run a CLI command, load modules, etc. as thousands of similar API functions exist for various system operations. Higher level software frameworks, such as Microsoft .NET and macOS Cocoa, are also available to interact with native APIs. These frameworks typically provide language wrappers/abstractions to API functionalities and are designed for ease-of-use/portability of code. Adversaries may use assembly to directly or in-directly invoke syscalls in an attempt to subvert defensive sensors and detection signatures such as user mode API-hooks. Adversaries may also attempt to tamper with sensors and defensive tools associated with API monitoring, such as unhooking monitored functions via Disable or Modify Tools.
Open detection, hunting, mitigation, and evidence workspace
Detection logic
Monitoring API calls may generate a significant amount of data and may not be useful for defense unless collected under specific circumstances, since benign use of API functions are common and may be difficult to distinguish from malicious behavior. Correlation of other events with behavior surrounding API function calls using API monitoring will provide additional context to an event that may assist in determining if it is due to malicious behavior. Correlation of activity by process lineage by process ID may be sufficient. Utilization of the Windows APIs may involve processes loading/accessing system DLLs associated with providing called functions (ex: ntdll.dll, kernel32.dll, advapi32.dll, user32.dll, and gdi32.dll). Monitoring for DLL loads, especially to abnormal/unusual or potentially malicious processes, may indicate abuse of the Windows API. Though noisy, this data can be combined with other indicators to identify adversary activity.
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.
Vulnerability Research & Exploit Development · Governed topic match · 57/100Module 5 — Cloud, containers, and Kubernetes
Red Team & Offensive Security · Tactic learning route · 24/100Static triage: strings, imports, resources, and capabilities
Malware Analysis & Reverse Engineering · Tactic learning route · 24/100Module 4 — Detection engineering and detection as code
Blue Team & Defensive Security · Tactic learning route · 24/100
MITRE mitigations
Behavior Prevention on Endpoint refers to the use of technologies and strategies to detect and block potentially malicious activities by analyzing the behavior of processes, files, API calls, and other endpoint events. Rather than relying solely on known signatures, this approach leverages heuristics, machine learning, and real-time monitoring to identify anomalous patterns indicative of an attack. This mitigation can be implemented through the following measures: Suspicious Process Behavior: - Implementation: Use Endpoint Detection and Response (EDR) tools to monitor and block processes exhibiting unusual behavior, such as privilege escalation attempts. - Use Case: An attacker uses a known vulnerability to spawn a privileged process from a user-level application. The endpoint tool detects the abnormal parent-child process relationship and blocks the action. Unauthorized File Access: -…
MITRE mitigation sourceMITRE detection strategies and analytics
- AN1465 · Analytic 1465 — Unusual or suspicious processes loading critical native API DLLs (e.g., ntdll.dll, kernel32.dll) followed by direct syscall behavior, memory manipulation, or hollowing.
- AN1466 · Analytic 1466 — Userland processes invoking syscall-heavy libraries (libc, glibc) followed by fork, mmap, or ptrace behavior commonly associated with code injection or memory manipulation.
- AN1467 · Analytic 1467 — Execution of processes that link to CoreServices or Foundation APIs followed by creation of memory regions, code execution, or abnormal library injection.