AIDE-002 Context Manipulation Coverage C ATT&CK Aligned Defense Evasion

Steganographic Instruction Embedding

AIDE-002 | ATT&CK: T1027

Description

Adversary Behavior: An adversary embeds prompt injection payloads within project files, documentation, or AI configuration files using Unicode control characters that are invisible to human reviewers but processed by the LLM tokenizer.

AI/IDE Mechanism: LLM tokenizers process the full Unicode spectrum, including zero-width joiners (U+200D), zero-width spaces (U+200B), bidirectional text override characters (U+202E, U+202C), and other non-printing characters. Standard text editors, diff viewers, and code review interfaces do not render these characters, creating a gap between what the human reviewer sees and what the LLM processes.

Execution Path: The adversary encodes malicious instructions as sequences of invisible Unicode characters and inserts them into files that will be ingested by the LLM during context assembly. The LLM decodes these character sequences as valid instructions while the file appears benign in all standard review tools.

Security Impact: The injected instructions evade human review, automated linting, and standard code review processes, allowing adversary commands to persist undetected in repositories and influence LLM behavior whenever the containing files are included in context.

Platforms

Windows macOS Linux

Detection

Implement byte-level scanning of committed files for Unicode control characters (U+200B-U+200F, U+202A-U+202E, U+2060-U+2064, U+FEFF). Flag files where the rendered text length differs significantly from the byte length. Integrate non-printing character detection into CI/CD pipelines and pre-commit hooks.

Detecting Data Components (2)

Configuration File Modification
Events capturing modifications to AI-relevant configuration files within the IDE and project workspace.
Prompt Content
Full text of prompts sent to the LLM including system prompts, user instructions, and assembled context.

Mitigations (1)

AI Configuration File Integrity Monitoring
Implement file integrity monitoring and diff analysis for AI configuration files (.cursorrules, .github/copilot-instructions, MCP configs). Flag non-obvious instruction content and enforce review requirements for AI configuration changes in repositories.

Data Sources

File File Modification
File File Content

References

mitre-attack
Maps to Obfuscated Files or Information. Coverage Level C — detection guidance insufficient for Unicode steganography in IDE configs.
https://attack.mitre.org/techniques/T1027
Pillar Security Rules File Backdoor
New Vulnerability in GitHub Copilot and Cursor: How Hackers Can Weaponize Code Agents Through Compromised Rule Files
https://www.pillar.security/blog/new-vulnerability-in-github-copilot-and-cursor-how-hackers-can-weaponize-code-agents
Guardrail Bypassing
Character injection evasion achieves up to 100% bypass against 6 protection systems while maintaining attack utility (arXiv:2504.11168, 2025)
https://arxiv.org/abs/2504.11168

STIX Metadata

type attack-pattern
id attack-pattern--e63afebf-1b90-480a-87d1-6792414c9ca0
spec_version 2.1
created 2026-02-23T00:00:00.000Z
modified 2026-02-23T00:00:00.000Z
created_by_ref identity--f5b5ec62-ffbd-4afd-9ee5-7c648406e189
x_mitre_is_subtechnique False
x_mitre_version 0.1
x_mitre_status mapped
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