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 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
Masquerade File Type
Adversaries may masquerade malicious payloads as legitimate files through changes to the payload's formatting, including the file’s signature, extension, and contents. Various file types have a typical standard format, including how they are encoded and organized. For example, a file’s signature (also known as header or magic bytes) is the beginning bytes of a file and is often used to identify the file’s type. For example, the header of a JPEG file, is 0xFF 0xD8 and the file extension is either `.JPE`, `.JPEG` or `.JPG`. Adversaries may edit the header’s hex code and/or the file extension of a malicious payload in order to bypass file validation checks and/or input sanitization. This behavior is commonly used when payload files are transferred (e.g., Ingress Tool Transfer) and stored (e.g., Upload Malware) so that adversaries may move their malware without triggering detections. Common non-executable file types and extensions, such as text files (`.txt`) and image files (`.jpg`, `.gif`, etc.) may be typically treated as benign. Based on this, adversaries may use a file extension to disguise malware, such as naming a PHP backdoor code with a file name of test.gif. A user may not know that a file is malicious due to the benign appearance and file extension. Polygot files, which are files that have multiple different file types and that function differently based on the application that will execute them, may also be used to disguise malicious malware and capabilities.
Open detection, hunting, mitigation, and evidence workspace
Detection logic
Use behavior-focused telemetry and validate findings against surrounding 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.
Malware Analysis & Reverse Engineering · Tactic learning route · 24/100Module 4 — Detection engineering and detection as code
Blue Team & Defensive Security · Tactic learning route · 24/100Disk, file-system, and persistence forensics
Digital Forensics & Incident Response (DFIR) · Tactic learning route · 24/100
MITRE mitigations
Antivirus/Antimalware solutions utilize signatures, heuristics, and behavioral analysis to detect, block, and remediate malicious software, including viruses, trojans, ransomware, and spyware. These solutions continuously monitor endpoints and systems for known malicious patterns and suspicious behaviors that indicate compromise. Antivirus/Antimalware software should be deployed across all devices, with automated updates to ensure protection against the latest threats. This mitigation can be implemented through the following measures: Signature-Based Detection: - Implementation: Use predefined signatures to identify known malware based on unique patterns such as file hashes, byte sequences, or command-line arguments. This method is effective against known threats. - Use Case: When malware like "Emotet" is detected, its signature (such as a specific file hash) matches a known database of…
MITRE mitigation sourcePrevent 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 sourceMITRE detection strategies and analytics
- AN0630 · Analytic 0630 — Detects behavior where files with non-executable or misleading extensions (e.g., .jpg, .txt) are created or modified but subsequently executed as binaries based on internal file headers or abnormal parent process lineage. This includes identifying polyglot files or malformed magic bytes indicative of masquerading attempts.
- AN0631 · Analytic 0631 — Detects when a script or binary is named with misleading or benign-looking extensions (.jpg, .doc) and is then executed via command line or a scheduled task. Includes ELF header mismatches and content-type inconsistencies on disk.
- AN0632 · Analytic 0632 — Detects binaries disguised as media or document types through extension-only masquerading or by modifying the file signature. Observes execution of files whose extension is not typically executable (.jpg, .txt), yet have valid Mach-O headers or execute via Terminal or launch services.