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.
A chatbot turned against its own brand.
A sales bot that gave away the store.
An AI assistant hijacked by one email
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.
