- AN2063 · Analytic 2063 — Detection identifies execution of scripts or files that appear visually benign (low printable character ratio) but result in runtime decoding, dynamic evaluation, and subsequent process or network activity. Correlation links script execution with abnormal Unicode density and follow-on behavior such as child process creation or outbound connections.
- AN2064 · Analytic 2064 — Detection identifies execution of scripts containing high concentrations of invisible Unicode characters followed by decoding or interpretation behaviors (e.g., base64 decode, eval) and subsequent process or network activity. Emphasis is placed on mismatch between file entropy/structure and execution output.
- AN2065 · Analytic 2065 — Detection identifies execution of scripts or applications containing invisible Unicode payloads reconstructed at runtime, correlated with abnormal AppleScript, JavaScript for Automation, or shell execution and subsequent process or network behavior inconsistent with visible file content.
Invisible Unicode
Adversaries may abuse invisible or non-printing Unicode characters to conceal malicious content within files, scripts, or text. By inserting characters that do not visibly render, adversaries may hide data, alter how content is interpreted, or make malicious code appear as benign text or whitespace. Adversaries may encode these malicious payloads, using binary, Base64, or custom schemes, to be reconstructed at runtime through scripting features such as [JavaScript](https://attack.mitre.org/techniques/T1059/007) Proxy traps, `eval()`, or other dynamic execution methods. This technique enables adversaries to evade visual inspection and basic static analysis by hiding malicious encoded content in innocuous text.(Citation: PUAs Unicode - Eriksen)(Citation: Tycoon2FA - Unicode)(Citation: Unicode - Veracode) Unicode is a standardized character encoding model that assigns a unique numerical value, known as a code point, to every character across writing systems, enabling consistent text representation across platforms, applications, and languages. Code points are represented as `U+` followed by a hexadecimal value and may be encoded using formats such as `UTF-8` or `UTF-16`. Adversaries may abuse the valid code points in Unicode that are not visibly rendered but still take up bytes, such as zero-width spaces, variation selectors, or bidirectional formatting controls, to conceal malicious payloads.(Citation: Tycoon2FA - Unicode)(Citation: GlassWorm - Unicode)(Citation: Unicode and Hidden Prompts - Perets) Adversaries may additionally exploit Private Use Area (PUA) characters, a ra…
Open in the interactive knowledge mesh
Detection overview
Use the published detection strategies below and validate required telemetry in the target environment.
Observed groups
No current Enterprise group relationship is published in this bundle.
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.
Controlled dynamic behavior and differential observation
Malware Analysis & Reverse Engineering · tactic-route · 24/100Module 4 — Detection engineering and detection as code
Blue Team & Defensive Security · tactic-route · 24/100Disk, file-system, and persistence forensics
Digital Forensics & Incident Response (DFIR) · tactic-route · 24/100
Malware Analysis & Reverse Engineering · tactic-route · 24/100Module 4 — Detection engineering and detection as code
Blue Team & Defensive Security · tactic-route · 24/100Disk, file-system, and persistence forensics
Digital Forensics & Incident Response (DFIR) · tactic-route · 24/100
MITRE mitigations
No ATT&CK mitigation relationship is published for this technique. Apply risk-based controls and verify scope.