AI Security

Your existing security stack wasn't built for AI.

Prompt injection, data exfiltration through AI tools, model governance failures, and shadow AI usage are net-new threat vectors. Your EDR doesn't see them. Your firewall can't block them. We close the gap.

Review Your AI Exposure See the Threat Landscape

What Is AI Security?

AI security is the discipline of protecting business data, identities, and decisions from AI-specific threat vectors: shadow AI usage, prompt injection, data exfiltration through AI prompts, model governance failures, and AI-specific compliance violations. It extends an existing cybersecurity stack rather than replacing it, using controls like DNS-layer monitoring, browser-layer DLP, and AI vendor risk monitoring.

Five threat patterns your stack doesn't see.

All five are active in mid-market environments today. Most teams aren't measuring any of them.

1. Shadow AI / unsanctioned tool use

Employees pasting customer data, contracts, financials, or code into ChatGPT, Claude, Gemini, or whatever AI tool they personally prefer. Public models train on prompts. Your data leaves the perimeter. No EDR alert fires.

2. Prompt injection in customer-facing tools

If you ship an AI feature, malicious actors can hide instructions in documents, emails, or web content that hijack your AI to leak data or take actions. Indirect prompt injection attacks the AI through content it processes, not through the user.

3. Sensitive data leaving via AI prompts

Even with sanctioned tools, employees paste sensitive data (patient information, financials, contract terms, credentials) into prompts. Without DLP at the AI tier, your sensitive data flows to vendor subprocessors with their own data-handling postures and breach disclosure cycles.

4. Model governance failures

AI vendors update their models, security postures, and DPAs without notifying you. A vendor breach affects your data flow. A subprocessor changes terms. Without ongoing monitoring, you only find out when the news breaks.

5. AI-specific compliance violations

HIPAA, MSHA, PCI-DSS, GDPR, and the patchwork of state AI laws (Colorado, California, New York, others) are all developing AI-specific requirements. AI use that was acceptable in January may be violation by July. Most compliance programs are not yet mapped to AI scope.

Six controls we deploy under AI Security.

All six work with what's already in your stack.

Shadow AI monitoring

DNS-layer surveillance via Cisco Umbrella for unsanctioned AI tool access. Monthly AI Usage Report by user, by tool, by trend.

Browser-layer DLP

Island Browser policy enforcement when deployed. Block paste of clipboard contents over a defined size or pattern. Block file uploads to AI sites entirely. Per-site policies.

M365 governance audit

Inforcer-driven Microsoft 365 audit log monitoring for AI tool usage inside the tenant. Sensitivity-label drift detection. Conditional access policy enforcement.

Vendor risk monitoring

Subprocessor breach disclosure tracking, DPA renewal management, AI vendor security posture review. We track what they ship so you don't have to.

AI incident response

On-call coverage for AI-specific incidents: data leak via AI tool, prompt injection event, sanctioned-tool failure, vendor breach. Existing Unió on-call infrastructure extended to AI.

Audit-ready evidence packaging

Quarterly packaged evidence of AI controls: monitoring logs, policy enforcement records, incident timelines, vendor-risk attestations. Ready to hand to your auditor or insurance carrier without a fire drill.

AI Security extends your stack. It doesn't replace it.

Huntress EDR and ITDR. ConnectSecure for vulnerability management. dmarcian for email authentication. Avanan for inbox protection. These are doing real work, but they were built before AI tools became a primary data exfiltration channel.

AI Security adds the missing layer: visibility into AI tool usage, policy enforcement at the browser and DNS layers, vendor risk for AI subprocessors, and AI-specific incident response. It runs on top of what you have, not instead of it.

If you're a Unió Digital managed IT or cybersecurity client, the integration is essentially zero-cost effort because the stack is already deployed. If you're new to us, the assessment maps your stack, identifies the AI gap, and recommends the smallest set of controls that close it.

Why Unió Digital owns AI Security credibly.

Stack we already run

Cisco Umbrella, Inforcer, Huntress, ConnectSecure, dmarcian. AI Security plugs into the security stack we deploy and operate every day. No platform learning curve. No procurement cycle for net-new tooling.

Operational discipline at MSP scale

AI Security findings get logged, tracked, and reviewed inside the same operating cadence as our managed IT and managed cybersecurity work. Not a side workflow that gets dropped when something else breaks.

Bench depth via the Claude Partner Program

Internal AI capability cohort. Ten employees trained by mid-2026. AI Security is a team capability, not a single-person dependency.

AI Security in your industry.

Healthcare

PHI containment as a first-class concern in every AI Security control. PHI scope explicit in the AUP and DLP rules. Documented AI Policy that respects the regulatory perimeter healthcare practices operate inside.

Mining

MSHA documentation integrity for AI-touched records. Training-record handling that survives audit. IT/OT segmentation maintained when AI tools enter the environment.

Construction

Contract data leakage prevention. Subcontractor and submittal data protection. Multi-site AI policy enforcement that respects field-team workflows.

AI Security: FAQs.

Why is this not just covered by Huntress or our existing EDR?

Huntress is excellent at endpoint detection and response, but it doesn't see browser-layer paste events to ChatGPT, doesn't track DNS-layer access to AI tools, and doesn't manage vendor DPAs. AI Security is the missing layer between your endpoint stack and the AI tools your employees are using. The two stacks are complementary, not redundant.

How does Island Browser fit into this?

Island Browser is a managed enterprise browser that lets us enforce policy at the browser layer: block paste of clipboard contents over a defined size, block file uploads to AI sites, block specific AI tools entirely, watermark and audit copy operations from sensitive applications. It's our preferred deployment mechanism for clients in regulated industries (HIPAA, MSHA, contract-heavy construction). Pricing typically lands at $10 to $30 per user per month.

What happens to data we already pasted into ChatGPT?

Honest answer: it's already in OpenAI's training data unless you used the Enterprise tier with explicit opt-out. AI Security can't retrieve or unleak data that's already gone. What it can do is stop the next round, document what likely went out for compliance discussion, and harden the policy and tooling so it doesn't continue. The first conversation in the assessment usually produces a sober inventory of past exposure.

Can we do this without Island Browser?

Yes. The DNS-layer monitoring (Cisco Umbrella), M365 audit (Inforcer), vendor risk monitoring, and incident response coverage all work without Island. Island adds browser-layer DLP, which is the strongest control for stopping paste-based data leakage in real time. For non-regulated environments, the rest of the stack often closes 80% of the gap.

What's an AI-specific incident look like?

Examples we've planned for: an employee pastes a contract into ChatGPT and the AI vendor has a breach two weeks later; a customer-facing AI tool gets prompt-injected via a document upload; a sanctioned AI vendor changes their DPA and quietly removes a data-handling protection; a SaaS app you use turns on an embedded AI feature without notification, sending your data to a new subprocessor. AI incident response covers all of these.

Will this produce evidence we can hand to an auditor or insurance carrier?

Yes. Quarterly evidence packaging is one of the six controls. You get a packaged record of monitoring logs, policy enforcement events, incident timelines, and vendor-risk attestations on a cadence that fits audit and insurance review cycles. Format adapts to whatever framework or carrier is asking.

Will this slow down our team?

Not if it's deployed properly. The point of AI Security isn't to block AI; it's to make sanctioned AI work better while stopping the unsanctioned tools that create the exposure. Most teams report that after rollout, the experience improves because Microsoft Copilot and the other sanctioned tools work properly (oversharing remediated, sensitivity labels working) while the shadow AI churn stops.

How do we get started?

Book the free AI Readiness Assessment. The AI Usage Report alone tells you what's currently leaving your environment. From there, we recommend the smallest set of AI Security controls that close the gap, mapped to your existing stack.

Related AI Services

AI Security pairs naturally with the broader Managed AI program.

Managed AI Agreement

AI Security is one module under the recurring program.
Microsoft Copilot

DLP, sensitivity labels, prompt safety on the Microsoft side.
AI Strategy (vCAIO)

Board-level reporting on AI risk and posture.

Schedule an AI Security review.

Start with the free assessment. The AI Usage Report alone tells you what your existing stack is missing.

Book the Assessment

Further Reading

Authoritative references

Ryan Gyure, Managing Partner & Co-Founder of Unió Digital

Written by Ryan Gyure, Managing Partner & Co-Founder of Unió Digital.

Ryan has led Arizona managed IT, cabling, and security delivery since 2016. He authors and operates the Managed AI program at Unió Digital. More about Ryan · LinkedIn