Forcepoint X-Labs researchers have demonstrated a new security flaw affecting AI-powered email assistants. The team showed that attackers can hide specific commands within standard emails using invisible HTML code. When an AI tool processes the message, it reads these hidden instructions instead of the visible text. This creates a disconnect between what the user sees and what the machine understands. The vulnerability allows silent manipulation of automated summaries without alerting the human recipient.
The attack exploits the way large language models parse input data. Attackers embed text elements that are visually concealed from humans but fully readable by software. These hidden prompts instruct the AI to alter its output or prioritize certain information. The visible email remains unchanged, preserving the illusion of normalcy for the user. This technique bypasses traditional visual inspection methods that rely on human oversight. It highlights a growing gap between human perception and machine interpretation in digital communication.
The core mechanism relies on the difference between rendering and parsing. Web browsers display emails based on CSS styles, which can make text transparent or zero-sized. However, AI models often strip away styling to focus on raw text content. This leaves the hidden instructions exposed to the algorithm. Forcepoint researchers noted that this discrepancy creates a reliable vector for prompt injection. The attacker does not need access to the user’s account or device. They only need to send a specially crafted email containing the embedded payload. Once the AI summarizes the message, the manipulated result appears natural and trustworthy.
Users may receive a summary that emphasizes irrelevant details or hides critical warnings. For example, an email about a meeting could be summarized to mention only the time, while ignoring a changed location specified in the hidden text. The AI follows the hidden directive to omit the location change. The user trusts the summary because it comes from a trusted assistant. This subtle alteration can lead to operational errors or compromised decision-making in professional settings.
Not all systems are equally vulnerable, but the risk is widespread. Any AI tool that ingests unstructured text from external sources faces this challenge. The issue stems from the fundamental design of current language models. They treat all input text as potential instruction unless explicitly constrained. Developers are working on sandboxing techniques to isolate user content from system prompts. However, these defenses are not yet universal across all commercial email platforms. Users should remain cautious when relying on automated summaries for high-stakes communications. Verifying key details against the original email remains a prudent safety measure until robust fixes are deployed.
The discovery underscores the need for stricter standards in AI data processing. As organizations adopt AI for productivity, the attack surface expands significantly. Security experts recommend treating AI outputs as suggestions rather than absolute truths. Future updates will likely include better filtering of non-visible characters before processing. Until then, the invisible layer of email communication poses a persistent blind spot for both users and developers.
Can users detect if their AI assistant has been manipulated? It is difficult to detect manually because the visible email looks normal. Users should compare the AI summary with the full text body to spot discrepancies.
Does this attack require the attacker to know the user’s password? No, the attack works through standard email delivery. The malicious code is embedded in the message itself, so no account credentials are needed.