T1027.018: 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 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.[1][2][3]
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.[2][4][5]
Adversaries may additionally exploit Private Use Area (PUA) characters, a range of code points reserved for custom assignment. PUA characters that are not defined by a font or application are typically rendered blank.[1]
Unicode characters may also be leveraged in support of other techniques such as Phishing, Right-to-Left Override, or User Execution. For example, some adversaries may embed artificial intelligence (AI) prompt injections using invisible Unicode characters in emails or documents that appear benign when processed by AI systems.[6][7]
Security context for executives and security teams
T1027.018: Invisible Unicode describes 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) Pro...
Executive priority
T1027.018: Invisible Unicode is an official MITRE ATT&CK technique. Glexia treats it as defensive behavior context for prioritizing monitoring, control validation, and response planning without using the object by itself as an attribution claim.
Technical view
Security teams should validate T1027.018: Invisible Unicode by reviewing the official ATT&CK relationships, mapped tactics (stealth), supported platforms (Linux, macOS, Windows), and available local telemetry before making detection or mitigation decisions.
Likely telemetry
- Official ATT&CK relationships and object metadata
- Network, endpoint, and security-tool telemetry
Detection direction
- Validate whether T1027.018: Invisible Unicode appears in your detection coverage and tabletop scenarios.
- Use the object to align executive risk language with SOC, incident response, and detection engineering work.
- Do not treat ATT&CK relationship context as attribution without corroborating evidence.
Mitigation priorities
- Map the object to existing controls and identify missing telemetry or response ownership.
- Prioritize mitigations that reduce exposure on the listed platforms and tactics.
- Review adjacent ATT&CK relationships before changing policy, detections, or reporting language.
Additional notes and limits
Baseline Glexia take generated from the official MITRE ATT&CK STIX object, source hash, tactics, platforms, and detection fields. It is safe to replace with a richer model-generated take for the same source hash later.
This baseline take is source-grounded and schema-validated, but it does not include environment-specific telemetry, incident evidence, or threat-intelligence corroboration.
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
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 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.[1][2][3]
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.[2][4][5]
Adversaries may additionally exploit Private Use Area (PUA) characters, a range of code points reserved for custom assignment. PUA characters that are not defined by a font or application are typically rendered blank.[1]
Unicode characters may also be leveraged in support of other techniques such as Phishing, Right-to-Left Override, or User Execution. For example, some adversaries may embed artificial intelligence (AI) prompt injections using invisible Unicode characters in emails or documents that appear benign when processed by AI systems.[6][7]
How security teams should use this page
Treat this object as behavior context, not an attribution claim. Validate the related groups, software, data sources, and mitigations against official ATT&CK relationships and your own telemetry before making control-coverage decisions.
Related techniques
This mirrors the MITRE pattern of making group, software, campaign, and technique relationships scannable. Relationship notes come from mirrored ATT&CK relationship text when available.
| Domain | ID | Name | Relationship / procedure |
|---|---|---|---|
| Enterprise | T1027 | Obfuscated Files or Information | This object subtechnique of Obfuscated Files or Information. |
Groups, software, and campaigns
S9010: GlassWorm
GlassWorm is a worm that propagated through supply chain attacks by compromising repository credentials from victim environments and having malicious payloads added to those compromised accounts for distribution to victims across the various development ecosystems.[1][2][3] GlassWorm has numerous variants, including Rust binaries, encrypted JavaScript and a variant leveraging invisible Unicode characters that made reverse engineering difficult.[4][1][5] GlassWorm has employed a unique command and control (C2) methodology using Solana blockchain.[6][1] GlassWorm was first reported in October 2025.[6][1][3]
All related ATT&CK context
Object version and sync metadata
The fields below describe the current mirrored snapshot. When Glexia retains multiple ATT&CK source imports, you can open the table to compare the same object across releases (hashes and MITRE timestamps). For MITRE’s own release notes and roadmap, see ATT&CK resources — Updates.
Imported snapshots across ATT&CK releases(2)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.2 | 1.0 | Current bundle | 8af55aa32ff1… | ||
| 19.1 | 1.0 | Older bundle | 8af55aa32ff1… |
Mirrored ATT&CK source object
The raw object is retained through the mirrored ATT&CK source bundle and object hash. The raw endpoint returns the exact object from the mirrored bundle when available.
External references and citations
MITRE external references are preserved separately from Glexia analysis so citations remain traceable to their original source records.
- [1]PUAs Unicode - Eriksen
Charlie Eriksen. (2025, May 13). You're Invited: Delivering malware via Google Calendar invites and PUAs. Retrieved April 21, 2026.
Open source URL - [2]Tycoon2FA - Unicode
Rodel Mendrez. (2025, April 10). Tycoon2FA New Evasion Technique for 2025. Retrieved April 21, 2026.
Open source URL - [3]Unicode - Veracode
Veracode Threat Research. (2025, June 9). Down the Rabbit Hole of Unicode Obfuscation. Retrieved April 21, 2026.
Open source URL - [4]GlassWorm - Unicode
Idan Dardikman. (2025, October 18). GlassWorm: First Self-Propagating Worm Using Invisible Code Hits OpenVSX Marketplace. Retrieved April 21, 2026.
Open source URL - [5]Unicode and Hidden Prompts - Perets
Shaked Perets. (2025, December 7). Invisible Code & Hidden Prompts – How Attackers Weaponize Unicode in Repos (and How SAST Can Help). Retrieved April 21, 2026.
Open source URL - [6]LLMs and Unicode - Medium
Idan Habler. (2025, September 12). Hiding in Plain Sight: Weaponizing Invisible Unicode to Attack LLMs. Retrieved April 21, 2026.
Open source URL - [7]Invisible Prompt Injection - Trend Micro
Ian Ch Lui. (2025, January 22). Invisible Prompt Injection: A Threat to AI Security. Retrieved April 21, 2026.
Open source URL - [8]mitre-attackT1027.018Open source URL
Source: MITRE ATT&CK®. © 2026 The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation. MITRE ATT&CK and ATT&CK are registered trademarks of The MITRE Corporation. Glexia is not affiliated with or endorsed by MITRE.