Best Prompt Security Vendors to Secure Claude (2026)

Enterprises increasingly use Claude for complex, high-level work. Teams use it to review contracts, analyse financial models, prepare board papers and work through client files in Cowork. To do that work well, Claude needs access to documents and data to ground its answers. The more real context Claude gets, the better the work it can produce for employees.

Given this, prompt security for Claude can't rely on blocking prompts that contain sensitive data, because that stops the work Claude is used for. It has to protect sensitive data while still giving Claude the context it needs to work well. Many prompt security tools either let the prompt through with the real data or block it, and Claude's own inference hooks, added in August 2026, only give vendors those two options. The more mature tools find sensitive data by meaning and give employees a way forward other than a hard block. The strongest way forward is to sanitise prompts at runtime by swapping each sensitive value for a realistic synthetic one that Claude can still work with.

This guide compares eight prompt security tools for Claude on that test: whether your data stays protected and Claude can still do the work you chose it for. It also looks at how mature each vendor is for Claude specifically.

How your enterprise data flows into Claude

Employees use Claude in several ways, and each one reaches company data differently:

• Claude chat receives what employees type, paste or attach.
• Claude Cowork reads and edits files across folders on the employee's computer, so one task can take in every file in a client or deal folder.
• Claude Code reads source code, configuration files and anything else the developer's terminal can reach.
• Claude extensions for Excel, PowerPoint and Outlook work on the open spreadsheet, deck or email, including the client data inside it.
• Connectors and Model Context Protocol (MCP) servers pull records from email, drives and business systems into a task, and can act on them.

In each case, Claude does its best work when it has the real documents and data. That is why prompt security for Claude has to sanitise what reaches the model at runtime, without stripping out the context Claude needs.

The limits of Claude's built-in governance

In 2026, Anthropic added two controls that give security teams more say over what goes into Claude: the Compliance API and inference hooks. Each has limits that matter when employees use Claude on sensitive data.

The Compliance API

The Compliance API gives your security tools a record of Claude activity. Since August 2026, it also includes Cowork and Claude Code sessions from the last 30 days.

Limitations of the Compliance API: It works after the fact, so the data has already reached the model by the time you see it. It also doesn't record which values were protected or which policy applied, which an auditor may ask for.

Inference hooks

Inference hooks launched on 5 August 2026 for Claude Enterprise, first as a test release and now open to all Claude Enterprise customers. Before Claude runs a prompt, Anthropic sends it to a security server that you or your vendor runs, and waits for a verdict. One hook covers claude.ai, Cowork, Claude Code, Claude for Microsoft 365 and Claude in Chrome, so a security team can stop a prompt without installing anything on employees' devices.

Most established security vendors, including Netskope, Zscaler, Palo Alto Networks and Nightfall, now use inference hooks for their Claude-specific controls. The hooks have limits, though, and every vendor that relies on them inherits those limits.

Limitations of inference hooks:

• Allow or block only: Anthropic's documentation says "Rewriting or redacting a prompt is not supported." An allowed prompt reaches Claude with the sensitive data, and a blocked one stops the work, which pushes people towards personal accounts.
• Detection depends on the vendor: Most vendors use their existing data loss prevention (DLP) rules, which find card and ID numbers but often miss business details such as a deal codename.
• Images aren't checked: The hook doesn't pass images to the security tool, so if an employee attaches a screenshot, any sensitive data in it goes to Claude unchecked.
• Claude Enterprise only: Claude Team, the Claude Platform API, Amazon Bedrock and Google Cloud aren't covered.

What to look for in runtime prompt security for Claude

A prompt security tool for Claude should protect sensitive data without stopping the work. Four benchmarks show whether it can, and the vendor comparison below uses the same ones. In this guide, maturity for Claude means how well a tool protects sensitive data without getting in the way of the work: whether it recognises sensitive data by meaning, gives employees a way forward other than a hard block, and covers the Claude apps teams use.

1. Where it intercepts prompts going to Claude

A prompt travels from the employee's device, through the Claude app, to Anthropic's servers, where the model runs. Claude can also reach company systems, such as email and drives, through connectors. Most security vendors intercept prompts through Anthropic's inference hooks, and some also check traffic on the company network or on employees' devices. A few govern the connectors Claude's agents use. Each position has its own limits:

• Inference hooks: The security tool can only allow or block a prompt.
• Network and device tools: Most can warn, block or redact. Redacting removes the data from the prompt, so Claude loses the details it needs.
• A gateway in front of the model: It can replace sensitive data and put the real values back in Claude's answer, but only for the Claude apps that send their traffic through it.

2. How it finds sensitive data

Pattern matching and keyword rules catch card and ID numbers, but they miss client names and deal codenames written in ordinary sentences, and someone has to keep updating them. A tool that reads prompts for meaning finds business-sensitive data without a rule for every client.

3. What it does with sensitive data

Blocking stops the work. Redacting turns "Acme Bank" into "[REDACTED]", which leaves Claude guessing. Replacing it with a realistic synthetic value, such as "Kite Bank", keeps the real data out and lets Claude do the work. This needs a gateway in front of the model that can change the prompt.

4. Which Claude plans it needs

Inference hooks and the Compliance API only work on Claude Enterprise, so tools that depend on them don't cover teams on other Claude plans.

Runtime prompt security vendors for Claude in 2026

This guide compares eight of the prompt security tools that work with Claude today. Each entry explains how the tool works with Claude, where it falls short and who it suits.

1. Mavs AI

Mavs AI is a runtime prompt security platform that lets teams use AI on sensitive work without exposing the data. For Claude, it runs as a secure gateway in front of Anthropic's model and protects Claude Desktop, Cowork and the Claude extensions for Excel, PowerPoint and Outlook. Instead of blocking a prompt, Mavs finds business-sensitive values, such as client names and deal codenames, and swaps each one for a realistic synthetic value. Claude keeps the context it needs, so teams can give it real contracts and client files and get the work done, without stopping to strip out data first and without the real values reaching the model.

Strengths

• Finds business-sensitive data in context: Mavs catches deal codenames, key accounts and merger terms by reading the context they appear in, so there's no keyword list to build or maintain.
• More than allow or block: Tools that work through inference hooks can only let a prompt through or stop it. The Mavs Reins pick an action based on the data in each prompt. Mavs swaps sensitive values for synthetic ones, and when swapping wouldn't make the prompt safe enough, it automatically reroutes the prompt to an internal model. For employees the company trusts to make the call, admins can turn on an override: Mavs shows what it flagged, and the employee can edit the prompt or send it as it is. Mavs blocks only harmful prompts, such as prompt injection.
• No Claude Enterprise needed: Mavs secured Claude through a secure gateway, not through inference hooks. Thus, teams do not need to be on the enterprise plan in order to get visibility and runtime security.

Limitations

• Built for business users: Mavs covers the Claude apps business teams use, and doesn’t work Claude Code used by developers for now.
• Focused on data going in: Mavs protects PII, PHI and business sensitive data from flowing into LLMs, it’s not built for moderating the content the LLMs generate.

Maturity for Claude: High. Mavs finds business-sensitive data by meaning, replaces it with realistic synthetic values instead of blocking, and covers Claude Desktop, Cowork and the Claude extensions for Excel, PowerPoint and Outlook.

Best for: Teams that want to use Claude on client files, financial models and other regulated data for complex work.

2. Netskope

Netskope covers Claude mainly through its web proxy, which checks what employees type and upload on claude.ai. On Claude Enterprise, it also connects through inference hooks and the Compliance API. If an employee pastes a client's account details into claude.ai, Netskope can block the prompt and show a message explaining why.

Strengths

• Reuses existing policies: Companies already on Netskope can apply the data protection rules they use for the web and other apps to Claude, without setting up new ones.
• Blocks personal accounts: Netskope can see whether an employee signed in to Claude with a company or personal account, and block the personal one.
• Lets teams roll out Claude in stages: Security teams can approve one Claude app at a time. For example, a company can let developers use Claude Code while it's still reviewing the Claude Desktop app.

Limitations

• Blocks or masks, but doesn't replace: Through its web proxy and inference hooks, Netskope blocks a prompt or warns the employee. Its AI gateway can also mask sensitive data in Claude Desktop, but masking removes the details Claude needs to do the work.
• Business details need custom rules: Its built-in profiles cover personal, payment and health data, so client names and deal codenames need custom profiles.
• Needs software on every computer: The web proxy only checks Claude traffic on computers where Netskope's software is installed and set up to inspect it.

Maturity for Claude: Medium. Netskope can warn instead of only blocking, but it relies on DLP rules that miss business details unless the team adds custom profiles.

Best for: Teams that want the same DLP rules on claude.ai and Claude Enterprise, and accept that flagged work stops.

3. Zscaler

Zscaler sends Claude traffic through its web proxy to AI Guard, its AI security product. With Zscaler's software on each company computer, this covers claude.ai, Claude Desktop, Cowork, Claude Code and the Excel and PowerPoint add-ins, on any Claude plan. On Claude Enterprise, AI Guard also connects through inference hooks. If an employee pastes a client's account details into Cowork, AI Guard can block the prompt or flag it for the security team.

Strengths

• Covers most Claude apps on any plan: Because the web proxy route doesn't need Claude Enterprise, companies on any Claude plan can protect claude.ai, Claude Desktop, Cowork and Claude Code.
• Different rules for personal accounts and teams: Zscaler can tell company and personal Claude accounts apart, and apply different rules to different teams, such as stricter rules for finance.
• Sensitive topics described in plain words: Teams can describe what counts as sensitive in plain words, not only with patterns.

Limitations

• Can only block prompts: In Claude's apps, AI Guard can allow, flag or block a prompt, but it can't clean the data out. Zscaler can mask data only in apps built on the Claude API.
• Business details need a rule each: AI Guard finds personal and payment data on its own, but client names and deal codenames are only caught if the security team describes them.
• Needs software on every computer: The web proxy route only works where Zscaler's software is installed and set up to inspect Claude traffic.

Maturity for Claude: Low. Zscaler covers most Claude apps, but when it finds sensitive data it either flags the prompt and lets the real data through, or blocks it.

Best for: Teams that want one set of AI policies across most Claude apps and plans, and accept that flagged work stops.

4. Palo Alto Networks

Palo Alto Networks covers Claude through several products. Its firewall, its Prisma Access web proxy and its Prisma Browser can check what employees send to AI apps. On Claude Enterprise, Prisma AIRS checks prompts through inference hooks, and it also connects to Claude Code. If an employee pastes the text of a merger agreement into Cowork, Prisma AIRS can recognise it and block the prompt.

Strengths

• Recognises business documents: Prisma AIRS can identify merger, legal and HR documents in a prompt.
• Works without Claude Enterprise: Its web proxy and Prisma Browser check what employees send to claude.ai on any Claude plan.
• Blocks personal accounts: Prisma Browser can stop employees signing in to personal Claude accounts.

Limitations

• Can only block prompts: In Claude's apps, Palo Alto Networks can allow or block a prompt, but it can't clean the data out. It can mask data only in apps built on the Claude API.
• Business details need custom rules: Prisma AIRS recognises whole document types, but client names and deal codenames in a short prompt need custom rules.
• Hooks check available in the US only: Palo Alto Networks offers its inference hooks check only in the US region.
• Several products to combine: Covering every Claude app means buying and running several separate products, each set up on its own.

Maturity for Claude: Low. Palo Alto Networks recognises business documents, but it can only let the real data through or stop the work.

Best for: Teams that already use Palo Alto Networks and want to spot sensitive business documents in Claude prompts, and accept that flagged work stops.

5. Nightfall

Nightfall covers Claude through several routes: software on company computers, a browser extension, inference hooks on Claude Enterprise, and checks on developers' machines for Claude Code.

Strengths

• Covers claude.ai, Claude Desktop and Claude Code: Nightfall checks all three, and security teams manage the rules for them in one place.
• Lets employees continue with a reason: Instead of a hard block, Nightfall can let an employee send a flagged prompt after explaining why, so legitimate work doesn't stop.
• Finds business data by meaning: Nightfall's AI detectors can find company-specific data, such as deal terms or internal documents, from a plain-language description instead of a keyword list.

Limitations

• Blocks or redacts, but doesn't replace: Nightfall's Claude checks block a prompt or let the employee override it. Its browser extension says it can also redact data in AI prompts, but redacting removes the details Claude needs to do the work.
• Business data must be described first: Nightfall only looks for the kinds of business data the security team has described, such as deal terms or client lists.
• Several pieces to deploy: Covering every Claude app means installing and running the computer software, the browser extension, the hooks and the developer checks separately.

Maturity for Claude: High. Nightfall doesn't replace data with synthetic values, but it finds business data by meaning, lets employees continue with a reason instead of a hard block, and covers claude.ai, Claude Desktop and Claude Code.

Best for: Security teams that want to manage Claude rules for the browser, desktop and developer tools in one place.

6. Harmonic Security

Harmonic Security runs as a browser extension and on company laptops through an endpoint agent (software installed on each laptop), covering claude.ai, Claude Desktop, Cowork and Claude Code on any Claude plan. If an employee is about to paste a client list into a personal Claude account, Harmonic can warn them, send them to the company account, or block the paste.

Strengths

• Sees personal accounts: Harmonic shows Claude use on free and personal accounts and can apply different rules to them, so security teams can spot company data going to accounts the company doesn't control.
• Judges sensitivity from context: Harmonic says its models decide what's sensitive from context rather than from fixed patterns, so it doesn't rely on keyword lists.
• Coverage expands to connectors: Its MCP gateway can stop sensitive data being sent to the connectors Claude uses.

Limitations

• Warns or blocks, but doesn't replace: Harmonic doesn't mask or replace sensitive data, so the employee has to remove it or send the prompt as it is.

Maturity for Claude: High. Harmonic doesn't replace data with synthetic values, but it judges sensitivity from context, guides employees with warnings and redirects instead of only blocking, and covers Claude on both company and personal accounts.

Best for: Teams that want to see how Claude is used across company and personal accounts, and guide employees towards safer habits.

7. Zenity

Zenity connects to Claude Enterprise through inference hooks, and mainly uses them to control what Claude's agents do rather than what employees send in prompts. Before an agent sends an email, edits a file or calls a connector, Zenity checks the action against the company's rules and allows or blocks it.

Strengths

• Blocks risky actions: Zenity stops agent actions a company doesn't allow, such as deleting records or emailing data outside the company.
• Covers many Claude apps: Its checks reach claude.ai, Cowork, Claude Code, Claude in Chrome, Claude for Microsoft 365 and Claude in Slack.
• Limits connectors: Zenity can restrict which connectors Claude's agents may use, so agents only reach the systems the company has approved.

Limitations

• Blocks, but doesn't replace: Zenity can block prompts and actions, but it doesn't mask or replace sensitive data.
• Built for agent actions, not prompt data: Zenity says it also checks prompts, but hasn't published what sensitive data it looks for, so it doesn't stop data leaving in prompts on its own.
• Needs Claude Enterprise for most checks: Only its Claude Code checks work without Claude Enterprise.

Maturity for Claude: Low. Zenity can block risky actions and prompts, but can't keep sensitive data out while letting Claude continue.

Best for: Teams giving Claude's agents access to business systems who want control over what those agents can change or send.

8. Mintive (formerly MintMCP)

Mintive mainly controls the connectors Claude's agents use to reach company systems, such as email, drives and customer databases. It also connects to Claude Enterprise through inference hooks, which let it block prompts.

Strengths

• Sets connectors by team: Admins decide which connectors each team's agents can use. For example, the finance team's agents can reach the finance database, while marketing's can't.
• Masks data sent to connectors: Mintive can swap sensitive values for text such as "[REDACTED]" before an agent sends them to a connector.

Limitations

• Can only block prompts: When an employee's prompt to Claude contains sensitive data, Mintive can block it, but it can't mask or replace the data so the prompt can go through.
• Masking needs setup: Mintive's built-in checks don't mask anything. Masking only works once the security team writes its own code or connects an outside DLP service.

Maturity for Claude: Low. Mintive can block a prompt but can't protect the data in it and let Claude keep working.

Best for: Teams connecting Claude's agents to company systems who want control over which systems each team's agents can reach.

Choosing how to govern Claude

Most teams choose Claude for the work that needs real context: client files, financial models, contracts and deal documents. Every vendor in this guide can stop something before it reaches Claude or runs, but a tool that can only allow or block leaves two options for that work: the real data reaches Claude, or the work stops. For lighter tasks, blocking may be enough, but that isn't the work most teams choose Claude for.

For the work Claude is chosen for, look for a tool that recognises business-sensitive data by meaning and swaps it for realistic synthetic values at runtime, so Claude can reason over the details while the real data stays with your company.

Whichever vendors you shortlist, test them on your own work. Take a few real Cowork tasks, Excel models and client emails from your teams, run them through each tool, and compare what Claude gives back and how mature each tool's Claude integration is. The right choice keeps your data protected without making those answers any less useful.