SOLUTIONS

Prompt Injection

Data Leakage & PII

Employee AI Use

Agentic AI Risk

Brand Protection

SOLUTIONS

Prompt Injection

The chatbot says something it shouldn't. The agent takes an action it shouldn't. The model leaks something it shouldn't. The same technique can sit behind all three: prompt injection, the most common and fastest-changing attack on AI systems today.

Someone's going to make our AI do something it shouldn't.

We inspect every prompt, file, and document your AI reads, in real time, and stop the injection before the model can act.

WHAT IT IS

Three types of Prompt Injection

Prompt injection happens when your model takes in text and treats it as instructions, even though those instructions were never supposed to be there.

Direct injection

A user types instructions designed to override the model's behaviour. "Pretend you're an unrestricted model."

Direct injection

A user types instructions designed to override the model's behaviour. "Pretend you're an unrestricted model."

Indirect injection via content

Instructions buried in something you've pointed your AI at: a web page, an email, a support ticket, a document to summarise.

Indirect injection via content

Instructions buried in something you've pointed your AI at: a web page, an email, a support ticket, a document to summarise.

Indirect injection via files

Instructions hidden inside files the AI ingests. Invisible white-on-white text in a PDF. Comments inside an SVG. EXIF metadata in an image.

Indirect injection via files

Instructions hidden inside files the AI ingests. Invisible white-on-white text in a PDF. Comments inside an SVG. EXIF metadata in an image.

Direct User Prompts

"Ignore your instructions…"

Content to read

WEB PAGE

EMAILS

TICKETS

Files to open

PDFs

IMAGES

LLM

Unintended Action

DATA LEAK

BRAND HARM

REAL INCIDENTS

It's already happening

Prompt injection left the research lab two years ago. The three cases below are documented, public, and hit production systems. The methods have only sharpened since.

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A chatbot turned against its own brand.

A sales bot that gave away the store.

An AI assistant hijacked by one email

PROBLEM

Why your existing controls don't catch it.

You already run firewalls, DLP, and WAFs. Each is built to read the form of an attack: bad traffic, bad patterns, bad code. Prompt injection is plain language that hides in the meaning, where none of them look.

Firewalls read traffic, not meaning

On the wire, a request to make the model leak its system prompt looks identical to a request for a recipe.

Firewalls read traffic, not meaning

On the wire, a request to make the model leak its system prompt looks identical to a request for a recipe.

DLP reads patterns, not paraphrase

It flags a credit card number in an attachment, but not a reworded question that coaxes the same number out of the model mid-conversation.

DLP reads patterns, not paraphrase

It flags a credit card number in an attachment, but not a reworded question that coaxes the same number out of the model mid-conversation.

WAFs read code, not language

They catch SQL injection and XSS, not a sentence that reads as harmless to a person and as a command to the model.

WAFs read code, not language

They catch SQL injection and XSS, not a sentence that reads as harmless to a person and as a command to the model.

Content filters read strings, not intent

Anything that relies on matching specific strings or patterns has a finite lifespan against an adversary who can rewrite their attack a million different ways.

Content filters read strings, not intent

Anything that relies on matching specific strings or patterns has a finite lifespan against an adversary who can rewrite their attack a million different ways.

THE FIX

How we stop all three

Prompt injection isn't one problem with one fix. It's three pathways, direct, content-borne, and file-borne, and a real defence has to cover all three at once.

Direct Injections

AI Guard

For attacks typed straight into the prompt, including multi-step and encoded ones.

Workflow

A user sends a prompt.

Our AI Guard intercepts the prompt before it can reach the core LLM.

We run every prompt through a detection model that reads it for hidden manipulation, then block anything malicious and pass the safe prompts through.

CONTENT-BORNE-INJECTIONS

Context Guard

For indirect instructions hidden inside the data sources that the AI is instructed to read.

Workflow

Your AI pulls in outside content: an email, a web page, a ticket.

Our Context Guard scans this third-party data before it blends into the AI's context window.

The clean data is safely delivered to the AI without compromising its operational logic.

FILE-BORNE-INJECTIONS

File Guard

Expose and stop adversarial instructions hidden inside files, images and document metadata.

Workflow

A file comes in: a document, an image, an archive.

Our File Guard applies OCR and gradient analysis to scan the file's text and visual layers.

Malicious instructions hidden in metadata or document layers are uncovered and removed.

RESOURCES

What we're learning and sharing.

Research reports, threat intelligence, deployment playbooks, and the occasional blunt opinion on where the AI security category is going.

See All

Research

Adversarial Multi-Turn Prompt Injections

Guide

AI Security Glossary

Research

Decoding the Latest AI Exploits