Shadow AI Detection: Every Unauthorized AI Tool, Visible
Employees are using AI tools you haven't approved. ShadowLock detects every AI tool running on every managed endpoint, browser-based, desktop, signed-in, anonymous, and shows you exactly what data has been pasted into them.
What is shadow AI detection?
Shadow AI detection is the practice of identifying unauthorized AI tool usage on company devices - browser tools like ChatGPT and Gemini, desktop AI apps, and the sensitive data submitted to them. ShadowLock surfaces every AI tool and every risky paste across your endpoints, so nothing leaves your environment unseen. Starting from zero? Begin with shadow AI discovery to inventory what is already in use, then detection keeps it in check.
of organizations suspect employees are using prohibited AI tools, but only a fraction can prove it. (Gartner)
You can't govern what you can't see
Network-layer tools miss anonymous and personal-account AI use, which is most of it. Endpoint agents that watch processes alone miss browser-based ChatGPT. Solving shadow AI requires detection at every layer where it actually happens: the browser, the desktop, and the clipboard.
ShadowLock is purpose-built for shadow AI detection across all three layers, with a single multi-tenant dashboard for IT teams and MSPs. Other tools cover one layer well; the comparison hub sets out who does what, with links to each vendor's own documentation.
Four layers of detection.
One dashboard, one agent, one extension.
Browser-based AI tools
The managed browser extension watches paste flows into ChatGPT, Claude, Gemini, Copilot, Perplexity, and the long tail of niche AI tools, including ones your IT team has never heard of.
Desktop AI applications
The Windows agent fingerprints installed and running desktop AI apps via signed binary hashes. NTFS ACL blocking can disable them without uninstalling, so users can't simply reinstall.
Sensitive data on paste
Every paste into an AI tool is classified on-device: PII, source code, credentials, customer records, financial data, PHI. You decide what gets blocked, what gets logged, what passes silently.
One multi-tenant view
A single dashboard rolls up every AI event across every endpoint and every client. Search by user, tool, or data type. Export for compliance reporting.
How do shadow AI detection methods compare?
Four approaches are commonly sold as shadow AI detection. They differ enormously in what they can actually see. The gap that matters is whether a method can tell you what data left, or only that a domain was contacted.
| Method | What it sees | What it misses |
|---|---|---|
| DNS and proxy logging | That an AI domain was resolved | What data was sent; personal hotspots; embedded AI that never resolves a blockable domain |
| Network / SSL inspection | AI API calls in decrypted traffic | Anything off the corporate network; privacy-sensitive and operationally heavy to run |
| Endpoint process detection | Desktop AI apps installed and running | Every browser-based tool, which is where most shadow AI happens |
| Browser and clipboard classification | The tool, the account, and the class of data pasted into it | Nothing on a managed endpoint. This is the layer that answers "what data left?" |
ShadowLock runs the bottom two rows together on every managed endpoint. Once you can see the usage, the next question is what to do about it, which is covered on blocking ChatGPT and unsanctioned AI tools. For the background on the problem itself, start with what shadow AI is and why it spread.
Shadow AI detection FAQ
What is shadow AI detection?
Shadow AI detection is the practice of identifying unauthorized AI tool usage on company devices, including browser-based tools like ChatGPT and Gemini, desktop AI apps like Claude for Mac, and the sensitive data being submitted to them. Without detection, organizations have no record of what data has left their environment through AI tools.
What features should I compare when evaluating shadow AI detection tools?
Compare five things: endpoint coverage (browser and desktop, not just network), whether the tool classifies the data being submitted or only logs the destination, whether it sees personal and anonymous accounts, whether logs are audit-grade and exportable, and whether policy cascades across tenants if you are an MSP. A tool that only reports domains answers "was AI used?" but never "what data left?".
How is shadow AI detection different from shadow AI discovery?
Discovery is the one-time inventory: which AI tools, browser extensions, and Microsoft 365 OAuth grants already exist in your environment. Detection is the ongoing monitoring that catches new tools and risky data as they appear. Most teams run discovery first to size the problem, then leave detection running.
How does ShadowLock detect AI usage that bypasses corporate SSO?
ShadowLock operates at the endpoint and browser layer, not at the network perimeter. That means it sees AI tool usage regardless of which account is signed in: corporate SSO, a personal Google account, an anonymous session, or no account at all. Network-only tools miss roughly half of shadow AI activity because employees routinely use personal accounts to bypass them.
Does ShadowLock detect AI tools we have not seen before?
Yes. ShadowLock's detection catalogue is updated continuously as new AI tools are released. Customers automatically receive new detection signatures via the agent's auto-update channel. The platform also flags suspicious paste patterns to unknown destinations so emerging tools can be reviewed and classified.
Is shadow AI detection different from DLP?
Traditional DLP was built for file transfers and email. It does not understand clipboard paste flows into web-based AI tools, and it does not know which destinations are AI services. ShadowLock is purpose-built for the AI threat surface: it knows the AI tool catalogue, classifies on paste, and reports in AI-specific terminology your auditors and compliance officers can act on.
How fast can we deploy shadow AI detection?
Most teams have shadow AI detection running across their fleet in under an hour. The Windows agent installs silently via RMM or Group Policy. The browser extension force-installs via Chrome and Edge enterprise policies. From the moment the agent reports in, you see live AI activity in the dashboard.
How ShadowLock compares
Researching alternatives? Honest side-by-side comparisons against every MSP-channel shadow AI tool.
AI-native XDR with no M365 scanning. We scan the tenant and publish a price.
Browser-only. We add endpoint and M365 tenant.
Blocks AI apps. We inspect the prompt content.
Resolver-layer only. Blind to embedded AI and M365 OAuth.
Browser isolation. We are purpose-built for shadow AI.
Governs shadow AI inside the E5 stack. We need no E5 license.
See every AI tool running in your environment
Free 14-day trial. Detection live within an hour of agent install.
Related reading
- How to detect shadow AIThe vendor-neutral method: five detection layers, what each one sees, and where the gaps are.
- What is shadow AI?The definition, how it differs from sanctioned AI and shadow IT, and the risks it creates.
- Shadow AI detection tools comparedTen named platforms compared by detection layer, with links to each vendor’s documentation.
- Shadow AI incident recordDocumented cases, with confirmed incidents kept separate from allegations.
- Glossary: endpoint agentWhat an endpoint agent sees that network-layer tools cannot.