{ "node_id": "mitre-atlas-llm-response-rendering", "title": "MITRE ATLAS LLM Response Rendering (AML.T0077) - Adversarial LLM Response Rendering threat to AI systems", "domain": "AI Governance & Law", "version": "1.0.1", "last_updated": "2026-07-22", "bluf": "This node addresses MITRE ATLAS technique AML.T0077 (LLM Response Rendering). An adversary may get a large language model (LLM) to respond with private information that is hidden from the user when the response is rendered by the user's client. The private information is then exfiltrated. This can take the form of rendered images, which automatically make a request to an adversary controlled server. The adversary gets AI to present an image to the user, which is rendered by the user's client application with no user clicks required. The image is hosted on an attacker-controlled website, allowing the adversary to exfiltrate data through image request parameters. Variants include HTML tags and markdown For example, an LLM may produce the following markdown: ``` !ATLAS ``` Which is rendered by the client as: ```