Generative AI data loss prevention

If your problem is that employees can paste proprietary source code into ChatGPT, Claude, Gemini, or Copilot without your security tools detecting it, you're looking for browser-based generative AI DLP (Data Loss Prevention).

These products inspect prompts, pasted text, and sometimes file uploads in the browser, then apply policies to block, warn about, redact, or log sensitive data before it reaches the AI provider. Several vendors specifically market this capability.layerxsecurity.com+2

Vendors to evaluate

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LayerX Security

(Strong enterprise starting point)

Its enterprise browser extension is explicitly designed to prevent sensitive information from being pasted into ChatGPT and other GenAI tools. Features include text-string blocking, granular browser activity visibility, and policy enforcement based on user, device, and data context.layerxsecurity.com+1

Best for: enterprise browser controls and broader web/SaaS security.

Product details

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Strac

Its Browser (Gen AI) DLP extension monitors AI web applications for sensitive data in prompts, pasted text, and file uploads. Published capabilities include detecting source code, secrets, PII, and other confidential information, with configurable warning and blocking policies.layerxsecurity.com+2

Best for: evaluating a focused GenAI DLP control for source code and other sensitive content.

Extension details

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Containment

Its AI Chat Firewall uses a browser extension to check employee submissions to supported AI chat services against organizational policies before submission. Its published coverage includes ChatGPT, Claude, Gemini, Copilot, and Grok.www.containment.ai

Best for: pre-submission policy enforcement across multiple AI chatbots.

Product details

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heLLM — STYX

A browser-native DLP product that scans prompts and can block, warn, redact, or silently log activity, with rules configured per user or group.layerxsecurity.com+2

Best for: prompt-level controls and configurable policies for shadow AI usage.

Product details

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VAHTOR

Offers a Chrome and Edge extension with real-time AI prompt guardrails, client-side prompt redaction, and the ability to stop file submissions before they leave the browser. The vendor says chat text is not uploaded.vahtor.com

Best for: browser-based controls with a privacy-conscious, client-side design.

Product details

Other options worth knowing about

What I would prioritize for your use case

For proprietary code, don't select a vendor based on generic PII detection alone. Evaluate these five controls:

• Source-code detection: Can it identify proprietary code, internal repositories, API keys, and secrets—not just credit card numbers and email addresses?
• Pre-send enforcement: Can it actually block a prompt or paste before data leaves the browser, rather than merely alerting afterward?
• Enterprise policy management: Can IT centrally deploy the extension, prevent employees from disabling it, and configure policies by user or group?
• Coverage: Does it cover Chrome and Edge, multiple AI providers, file uploads, and relevant desktop applications?
• Privacy and auditability: Where is inspected prompt content processed, what gets retained, and can security teams investigate incidents without unnecessarily collecting employees' full conversations?

My recommendation: Start with LayerX and Strac for an enterprise-oriented evaluation, then compare Containment and STYX for prompt-level enforcement. Treat these as an initial shortlist, not a verified performance ranking.

One important distinction: conventional network DLP may see encrypted traffic going to an approved AI domain without seeing the actual code in the prompt. A browser-level control can inspect the content at the point of entry, where prevention is still possible.

One question that would narrow this down: Are you looking to deploy this across a managed corporate workforce, or do you need a lightweight solution that also works on employees' unmanaged devices? That distinction materially changes which vendors are the best fit.

If your team is pasting proprietary source code into public AI tools, you want browser-level data loss prevention (DLP) that inspects prompts and blocks sensitive content before it is submitted—not just a tool that detects which AI websites employees visit.

There are several enterprise products designed for this problem. The main distinction is whether you need a secure browser, protection added to Chrome or Edge, or a broader cloud security platform that also enforces AI policies.www.paloaltonetworks.com+5

Browser-based GenAI DLP solutions to evaluate

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1. Palo Alto Networks Prisma Browser

(Strong fit for prompt blocking)

A secure enterprise browser with controls for GenAI prompts, file uploads, clipboard actions, and access to unapproved AI services. It supports content-aware prompt inspection and can block prompts matching configured DLP profiles, including proprietary information. It also offers an extension for existing browsers, although some capabilities differ by deployment mode.www.paloaltonetworks.com+6

Best for: Organizations wanting granular, browser-level enforcement, including restrictions on unmanaged devices.

Official product overview ·Prompt control documentation

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2. Netskope One DLP and Skylight AI Guardrails

Inspects AI prompts and responses in real time, with controls intended to prevent source code, personally identifiable information, and intellectual property from leaking into public AI models. Netskope also offers user coaching and controls for unauthorized AI applications. Its approach combines cloud-delivered security enforcement with AI-specific guardrails rather than relying solely on a browser extension.www.netskope.com+1

Best for: Organizations already using a secure web gateway, CASB, or enterprise DLP platform, and those needing centralized AI governance.

Official GenAI security overview ·AI Guardrails

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3. LayerX Security

A browser security platform worth evaluating for organizations that want controls closer to employee browsing activity, including the use of generative AI websites. Assess its current plan and deployment-specific ability to inspect prompt content, identify proprietary code, and block submissions in your team's actual browsers.

Best for: A browser-focused deployment evaluation, particularly if you want to preserve employees' existing browsing workflows.

Official website

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4. Island Enterprise Browser

An enterprise browser approach that brings data protection and policy enforcement into the browsing environment. Evaluate its current GenAI-specific controls for prompt entry, copy/paste, file uploads, and access to personal versus corporate AI accounts rather than assuming generic browser DLP covers every scenario.

Best for: Companies considering a managed enterprise browser as a broader workplace security standard.

Official website

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5. Microsoft Purview DLP with a browser enforcement layer

If your organization already uses Microsoft 365 security and compliance tooling, consider extending existing Purview DLP policies into the browser. For example, Island announced an integration that applies Purview classifications and policies to browser activity, including AI prompts and file uploads.support.island.io+4

Best for: Microsoft-centric organizations that want to reuse existing classifications and policies instead of maintaining a separate set of DLP rules.

Island–Purview integration details

Comparison: which should make your shortlist?

These are vendor-documented capabilities, not independent comparative test results. Verify current licensing, supported browsers, and enforcement coverage during a proof of concept.docs.paloaltonetworks.com+4

What I would require for your specific use case

Don't buy a product based solely on its ability to discover or block AI websites. Your developers may have legitimate reasons to use approved AI coding tools, while still needing to keep proprietary code out of public accounts.

Ask each vendor to demonstrate these five controls:

One important technical detail: source-code detection is not the same as secret detection. A DLP policy that catches API keys or passwords may still allow an entire proprietary function to be pasted into ChatGPT. Test the exact type of intellectual property you need to protect.

My recommendation

Start with a proof of concept comparing Prisma Browser and LayerX GenAI DLP if your priority is preventing developers from pasting code into public AI tools. Add Island if you're interested in an enterprise-browser strategy, and Netskope if you already have a broader Netskope security deployment. These are shortlist recommendations based on their documented approaches, not a claim that one has the best detection accuracy.

To narrow this down to the most practical fit: does your team need to keep using Chrome or Edge, or can you require employees to use a managed enterprise browser? That distinction will significantly change which solution is easiest to deploy.

Yes. There is now a distinct “GenAI DLP” / “AI data security” category aimed specifically at detecting and preventing proprietary information from being pasted, uploaded, or otherwise sent to public LLMs.

Vendors I would shortlist

The important distinction

Your problem sounds more specific than conventional DLP:

“An employee takes proprietary information from our systems and pastes it into ChatGPT/Claude/Gemini/etc. We need to know that it happened—and ideally stop it.”

Traditional DLP often misses this because there's no file transfer. The sensitive information can simply be copied from a document and pasted into an LLM text box. Cyberhaven describes this exact gap, while Nightfall, Netskope and Forcepoint now explicitly inspect AI prompts at the point of interaction.www.cyberhaven.com

There are actually three different products hiding under “GenAI DLP”:

1. Employee → public LLM protection
   “Did Alice paste source code/customer data into ChatGPT?”
   → Nightfall, Forcepoint, Netskope, Cyberhaven, Check Point/Lakera

2. Data lineage / forensic detection
   “Where did this information originate, and how did it get into the LLM?”
   → Cyberhaven is particularly differentiated here.www.cyberhaven.com

3. Your own LLM application → model protection
   “Our application sends customer data to an LLM; prevent sensitive data from reaching the model or leaking in responses.”
   → Lakera/Check Point, Netskope, etc.docs.lakera.ai

My initial recommendation

If your primary requirement is “tell me when our proprietary data is being leaked into public LLMs”, I'd put these three at the top of an evaluation:

1. Nightfall — strongest purpose-built/AI-native DLP angle. It specifically advertises prompt inspection and data lineage across AI applications.www.nightfall.ai

2. Cyberhaven — strongest if you need to establish exactly what corporate data was copied into the AI interaction and where it came from, rather than merely matching sensitive strings.www.cyberhaven.com

3. Netskope — strongest if you want this as part of a broader SSE/CASB/DLP architecture, particularly if you already have Netskope. It says it can inspect every prompt and response and enforce DLP in real time.www.netskope.com+2

Forcepoint is also very compelling if you already have its DLP footprint; its current AI Data Security product now explicitly covers prompts, responses and uploads across multiple major LLMs.www.forcepoint.com+1

If you tell me your existing stack (e.g. Microsoft, CrowdStrike, Netskope, Zscaler, Palo Alto, Forcepoint, etc.) and whether you're trying to detect past leakage or prevent future leakage, I can build you a vendor-by-vendor comparison of ~10 GenAI DLP products, including deployment method, ChatGPT/Claude/Gemini coverage, endpoint/browser visibility, detection of proprietary data, blocking, and pricing model.