You ignored the suspicious email. You didn’t open the attachment, click the link, or reply to the sender.

Then you asked your AI assistant to summarize your inbox.

Could the message you wisely avoided find its way back onto your to-do list—only this time presented as an urgent recommendation from a tool you trust?

That’s the risk behind phishing emails containing hidden instructions aimed at AI assistants. Instead of relying only on persuading you, attackers are also trying to influence the software that reads your messages. Recent research from Barracuda describes emails designed to target both audiences at once.

For the human recipient, there was a password-protected attachment, with the password supplied in the email. For an AI assistant processing the message, there were hidden instructions intended to influence how it summarized or handled the content.

By including a prompt injection, attackers give themselves another way to reach you. The malicious instructions could try to make the assistant describe the email as legitimate or urgent, encouraging you to revisit it.

In another example, a hidden block instructed a summarizing AI to add a fake priority action: Change a vendor’s payment details. That could result in an employee sending money to an attacker’s account.

The attacker isn’t simply asking the AI to repeat a fraudulent request. They’re trying to turn that request into the assistant’s recommendation.

How prompt injection works

Prompt injection means planting instructions in material an AI system is supposed to read, hoping it will follow those instructions instead of treating them as part of the material. When the instructions arrive through an outside source, such as an email or webpage, it’s often called indirect prompt injection.

The malicious instructions don’t have to appear as ordinary, readable paragraphs. Barracuda identified concealment techniques including comments in the email’s underlying HTML code, text made invisible through styling, encoded content, and invisible “zero-width” characters. These can obscure instructions from a person viewing the message while leaving content available for an AI system to process. Whether that content actually reaches the model depends on how the particular tool extracts and prepares the email.

That means this problem cannot be solved simply by asking people to look more carefully at their emails. Part of the defense must sit inside the tools handling those messages.

Apollo Raines, developer of the AI code review service ShipItClean, explains:

“The real flaw is that the model can’t tell the difference between text it’s supposed to read and instructions it’s supposed to follow. Stripping hidden content before it reaches the model is worth doing, and every vendor should do it. But it’s an arms race. Each new encoding trick is a new hole.”

He adds:

“People have learned to distrust the email. They haven’t learned to distrust their AI assistant. So, the defense has to live inside the tools. I’d go one step further: some of it has to live inside the model itself. Wrappers, filters, sandboxing and human sign-off on payments are all necessary.”

Before taking action

An assistant that summarizes messages could mislead you about which email deserves attention or what action it requires.

An assistant with additional permissions could create a more serious problem. Depending on its capabilities and safeguards, malicious instructions might try to make it carry out unauthorized actions or disclose sensitive information.

You don’t need to abandon AI tools that help with email. But you do need to consider what you trust them to do and what permissions you give them.

The familiar phishing advice still applies. When an assistant reads your inbox on your behalf, check its recommendations before acting:

• Check the original message before acting on a recommendation involving money or sensitive information. If a summary tells you to pay an invoice, change account details, or share sensitive information, don’t treat the summary itself as verification.
• Always verify payment changes through a separate, established channel. Contact the person or organization using details you already trust, rather than relying on information supplied in the suspicious message.
• Keep your AI assistant’s permissions limited to what you need and, at work, what your organization allows. An assistant used to summarize emails should not need broad authority to carry out unrelated actions. Limiting access can reduce the consequences if it follows malicious instructions.
• Require human approval for high-impact actions like payments and changes to vendor payment details. Approval should include checking the underlying request, not simply accepting the assistant’s recommendation.

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From reporting threats to removing them.

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A new type of prompt injection attack shows why giving AI assistants access to browsers, code tools, and private data deserves extra caution.

AI researchers describe “Cryptographic Context Injection”—an attack that hides malicious instructions inside encrypted data. The AI is then persuaded to decrypt that data using its own code-execution tool. As a result, the AI may treat the resulting text as if it were trustworthy internal information.

A prompt injection is a bit like leaving a fake instruction inside a document for an AI assistant to read. Instead of following only the user’s request, the assistant may be tricked into following an attacker’s instructions hidden in a webpage, email, or file.

As we reported months ago, experts have warned that prompt injection attacks are a problem that may never be fixed. Prompt injection works because AI models can’t reliably tell the difference between the legitimate instructions and an attacker’s instructions, so they sometimes obey the wrong ones.

To reduce this risk, AI providers set up their models with guardrails: protections designed to stop AI systems from doing things they shouldn’t, either intentionally or unintentionally.

What the researchers found was that malicious instructions could be hidden from some AI guardrails by encrypting them. The AI itself could then be tricked into decrypting those instructions using its coding tools.

By the time the instructions became readable, they had already made it past the initial security checks. The AI could then mistake them for legitimate instructions and follow them.

It’s a bit like hiding malicious instructions in a language the security system can’t understand. The AI translates them only after they’ve passed the security checks, then may follow what they say.

The researchers tested their method against two AI agents, with different results. In Grok, the researchers say the attack could steal information including the user’s name, approximate location, subscription tier, and conversation history. In Gemini, they used the technique to bypass safety controls and generate content the model would normally not do.

“In Grok, an ordinary ‘summarize this page’ steals the user’s chat data with no click or warning. In Gemini, it produces content the model normally refuses. Both are live production systems.”

The researchers did not provide full details because xAI had not taken action after the flaw in Grok was reported to it in June 2026. Gemini, on the other hand, has made improvements, but has still not fully closed the hole.

How to stay safe

An AI assistant may be helpful, but it should not automatically be trusted with sensitive data or powerful tools.

• Treat AI summaries of unfamiliar webpages, documents, and shared links with caution, especially when the assistant can browse or run code.
• Do not paste passwords, recovery codes, API keys, financial information, or sensitive health and work details into AI chats unless you understand how that information will be handled.
• Review an AI assistant’s connected tools and permissions. Remove access it doesn’t need, particularly email, cloud storage, source-code repositories, and external integrations.
• Be skeptical if an AI tool asks to decrypt, decode, run a script, open a new link, or upload data as part of a seemingly ordinary task.
• Keep browser and AI applications updated, and check vendor security advisories when using features such as browsing, autonomous agents, or code execution.
• Use an up-to-date, real-time anti-malware solution to detect and block malicious downloads and suspicious connections.

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