How the SecuritAI AI Firewall works
Every message a user sends to your AI passes through 7 security checkpoints before it reaches the model. Suspicious messages are blocked, clean messages pass through in milliseconds.
A plain-English overview of the layered defense that protects AI systems from prompt injection, jailbreaks, and data leaks, plus a dedicated module for keeping sensitive Canadian data out.
The problem: AI has no security layer
Every time a user sends a message to your AI, a chatbot, virtual assistant, or AI-powered app, that message goes straight to the model with no security checkpoint in between. Traditional firewalls were built for websites and networks. They do not understand AI attacks. Attackers have learned to manipulate AI systems in ways conventional security misses entirely, tricking them into revealing confidential data, ignoring their instructions, or doing things they were told not to do.
of organizations that suffered an AI-related breach lacked proper AI access controls, according to IBM’s 2025 Cost of a Data Breach Report.
added to the average breach cost when unmanaged “shadow AI” is involved, per the same IBM 2025 report.
The solution: the airport security model
Think of the AI Firewall like airport security. Before a passenger boards, they pass through several screening checkpoints: ticket check, ID check, baggage scan, body scanner, random secondary checks. Each one catches something different, and if one misses something, the next one catches it.
The SecuritAI Firewall works the same way. Every message passes through 7 checkpoints, called layers, before it reaches your AI. The fast early layers are designed to catch the most common attacks first, while the heavier checks run only when a message looks suspicious, so the firewall adds minimal latency to legitimate requests.
The 7 checkpoints, in plain English
Before even reading the message, it checks whether the request itself is weaponized, like spotting a letter bomb in the mailroom, and stops it before any processing begins.
Enforces your rules: who can send messages, how often, from which countries, at what times. Like a bouncer with a guest list, and it flags suspicious patterns like someone hammering the system.
Checks each message against a large library of known attack patterns, in multiple languages. Like a spam filter, but built for AI attacks such as prompt injection and jailbreaks.
Understands what a message actually means, not just the words it uses, so it catches attacks that are reworded or disguised as a polite question.
Looks at the whole conversation, not just the latest message. Some attackers build trust over several messages before striking, and this layer catches those slow-build attacks.
For messages that passed the earlier checks but still seem suspicious, a second AI is consulted, like calling in a specialist. It is the most powerful check, so it is used only when needed.
Checks what the AI sends back, not just what users send in, so the response never accidentally leaks confidential data, system instructions, or sensitive information.
What happens to a flagged message
When a message is flagged at any layer, your security team chooses what happens, and the choice is configurable:
- Block: the message is rejected and the user gets an appropriate error response.
- Flag and allow: the message is logged and flagged for review but allowed through, useful during testing.
- Redact and allow: sensitive data is removed automatically and the cleaned message is sent to the AI.
Every blocked or flagged event is recorded in the audit log with a timestamp, the layer triggered, and the attack type detected, giving your compliance and security teams full visibility.
Keeping sensitive data out: the DLP module
Alongside the attack layers, the firewall includes a dedicated Data Protection module, formally called DLP (Data Loss Prevention). Instead of stopping malicious intent, it stops sensitive data from flowing in or out of your AI, regardless of who sent it or why. Think of it like a customs inspection: before anything goes in or out, it is checked against a list of protected data types.
It is the only AI firewall module specifically designed for Canadian regulatory compliance, with built-in detection for Social Insurance Numbers, Health Card numbers, Business and GST numbers, and other Canadian data types required under PIPEDA and provincial privacy law. Each data type can be toggled on or off, set to block or redact, and every event is logged to a tamper-evident audit trail, the evidence required for PIPEDA breach notification.
SIN, Health Card, Business and GST number, driver’s licence, phone, postal code, address, and more, aligned to PIPEDA and provincial privacy law.
Credit card and CVV, US SSN, IBAN and SWIFT, date of birth, API keys, passwords, and email, to global standards.
Why it matters
Reduces the risk of an AI-related incident that could mean regulatory fines, customer loss, and reputational damage, and demonstrates AI governance to auditors and regulators.
Extends your existing security perimeter to cover AI, with the audit trail and incident evidence needed for reporting under PIPEDA and frameworks like SOC 2.
Integrates without infrastructure changes, and is designed to keep latency minimal on clean requests, so AI features stay fast.
Test AI features for vulnerabilities before launch with AI Red Teaming, then deploy the firewall to block them in production.
See the 7 layers protect your own AI
Book a walkthrough, or start free and put the firewall in front of your AI today.