Is PasteGuard worth it for teams that paste customer data into ChatGPT?

It depends on whether you can run Docker. PasteGuard detects over 30 types of private data — names, emails, phone numbers, credit cards, IBANs, API keys, JWTs — and replaces them with placeholders like [[PERSON_1]] before the text reaches the provider, with a live dashboard showing masked percentage and detected PII types. If a support team is already pasting real tickets into ChatGPT, that is a genuine reduction in exposure for a self-hosted, telemetry-free tool. If nobody on the team can run a container, it is not worth forcing.

Does PasteGuard integrate with ChatGPT, Claude, and Cursor?

Yes, across three surfaces. The experimental browser extension covers ChatGPT, Claude, and Gemini with a ⌘⇧K masking shortcut. For apps, PasteGuard exposes an OpenAI-compatible endpoint at http://localhost:3000/openai/v1 and an Anthropic-compatible one at http://localhost:3000/anthropic. For coding agents, it masks .env files and config context for Codex, Claude Code, Cursor, and Windsurf. The browser extension is the least mature of the three, so treat the proxy and coding-agent paths as the sturdier ones.

How does PasteGuard compare to hosted redaction APIs and provider-side guardrails?

The dividing line is where the boundary sits. Hosted redaction APIs and provider-side guardrails put it on someone else's infrastructure; PasteGuard runs locally or self-hosted under Apache 2.0 with no telemetry, so the masking happens before a request leaves your environment. You trade vendor convenience for that control: no support contract, and you own the container, the detector config, and any local LLM needed for Route mode.

What are PasteGuard's biggest limitations?

Three honest ones. The browser extension for ChatGPT, Claude, and Gemini is labelled experimental and beta. Route mode keeps sensitive requests on a local LLM you have to run, but other requests still go to the configured cloud provider, so it is not a zero-egress mode. Placeholders such as [[PERSON_1]] and [[EMAIL_1]] are restored in responses only where supported. PasteGuard also states in its own docs that it reduces what reaches AI providers — your legal and security controls still decide compliance.

Can PasteGuard replace a managed privacy or DLP service?

Only for the masking job itself, not the rest. PasteGuard covers over 30 PII and secret types, the OpenAI- and Anthropic-compatible proxy endpoints, Mask and Route modes, and an auditable Apache 2.0 codebase with no telemetry. What it does not provide is the managed layer: SSO, granular roles, enterprise access controls, or a vendor who certifies your compliance. Teams wanting those out of the box should look elsewhere; teams wanting an owned boundary will find the masking side covered.

How long does PasteGuard take to set up?

The proxy path is under a minute. You run docker run --rm -p 3000:3000 ghcr.io/sgasser/pasteguard:latest, open localhost:3000, and set OPENAI_BASE_URL or ANTHROPIC_BASE_URL in your app or SDK. Adding the beta browser extension is also quick but experimental. Budget more time for detector tuning, persistent logging, and standing up the local LLM that Route mode requires.

How do I move from manually redacting text to PasteGuard?

You do not change the chat workflow at all for the browser path — install the extension and highlight text with ⌘⇧K before it reaches ChatGPT, Claude, or Gemini, and PasteGuard swaps names, emails, and secrets for placeholders automatically. For applications, the migration is a base-URL change to http://localhost:3000/openai/v1 or http://localhost:3000/anthropic. Teams replacing custom per-app masking code get the biggest reduction in maintenance.

Is PasteGuard good for developers worried about secrets in coding agents?

Yes, this is one of its clearest fits. It masks .env files and config context for Codex, Claude Code, Cursor, and Windsurf, so values like DATABASE_URL, OPENAI_API_KEY, and AWS credentials arrive at the agent as placeholders such as [[API_KEY_SK_1]]. Its detector set specifically includes API keys, SSH keys, JWT tokens, passwords, connection strings, private keys, and bearer tokens — the exact categories that leak when a config file lands in a prompt.

Is PasteGuard free to use?

Yes — it is published as open source under the Apache 2.0 license with the code auditable and no telemetry, run via a single docker run command that publishes port 3000. The cost that remains is operational: you supply the machine, the container maintenance, and the local LLM if you use Route mode. Your legal and security controls still determine whether it satisfies your compliance obligations.

Is Pasteguard still active in 2026?

Pasteguard is active in 2026 but worth monitoring — liveness 67/100. Its weakest signal is how little the vendor publishes (no docs, changelog or pricing detail).

Security & Privacy

Pasteguard

PasteGuard masks PII and secrets in your browser and API traffic before text reaches ChatGPT, Claude, Gemini, or any model API.

67/100MonitorFreeFree

When your security review demands the privacy boundary sit on your own metal, PasteGuard earns a look: Apache 2.0, no telemetry, and one Docker container covering browser chat, app APIs, and coding agents. The catches are concrete — the chat extension is beta, restoration only happens where supported, and the vendor itself says it reduces exposure rather than certifying compliance. Treat it as a control you operate, not a checkbox you buy.

Verified 9h ago · liveness 67/100 · cite: rightaichoice.com/tools/pasteguard

Best for

Teams pasting customer or client data into ChatGPT, Claude, or Gemini for support and drafting
Developers using Codex, Claude Code, Cursor, or Windsurf who don't want production secrets in prompts
Compliance-minded orgs mapping AI usage to GDPR, DORA, or internal data-handling policy
Consulting, legal, and finance teams that need cloud AI without raw client data leaving the network

Not ideal for

Teams that need a fully managed, hosted privacy service with a support contract
Organizations requiring SSO, granular roles, or enterprise access controls out of the box
Users who can't run Docker or install a browser extension

Visit Website

IntermediateUnder a minute to a running proxy: one docker run command publishing port 3000, then open localhost:3000 and set OPENAI_BASE_URL or ANTHROPIC_BASE_URL in your app. Adding the browser extension is quick but experimental. Expect longer for detector tuning, persistent logging, and standing up the local LLM that Route mode requires.Web · API · PluginAPI availableVerified 9h ago

Pricing

Free

FreeFree tier4 hidden costs

Learning curve

Intermediate

Under a minute to a running proxy: one docker run command publishing port 3000, then open localhost:3000 and set OPENAI_BASE_URL or ANTHROPIC_BASE_URL in your app. Adding the browser extension is quick but experimental. Expect longer for detector tuning, persistent logging, and standing up the local LLM that Route mode requires.

Runs on

WebAPIPlugin

API available · 9 integrations

Who it's for

Support team lead at a company handling customer dataDeveloper using Claude Code or Cursor on a production repoPlatform engineer at a regulated firm

Live sentiment

Is Pasteguard actually worth it?

We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.

Honest verdict, not marketing
Real pros & cons from real users
Attributed quotes with receipts

Run a free scan

3 free scans · no card needed

Skip it if

Skip PasteGuard if you want a hosted privacy service with a support contract and SSO out of the box, or if any outbound AI traffic at all is unacceptable — Route mode still sends non-sensitive requests to your cloud provider.

The 30-second take

Biggest gripe

Running Route mode means standing up and paying for a local LLM of your own, on top of any cloud AI subscriptions you already have.

Price reality

PasteGuard is published as free open-source software under Apache 2.0, so the comparison is not tier-versus-tier but build-versus-buy: hosted redaction and guardrail services bill per seat or per volume, while PasteGuard costs you a container and the engineering time to run it.

In short

Pasteguard — PasteGuard masks PII and secrets in your browser and API traffic before text reaches ChatGPT, Claude, Gemini, or any model API. Best for Teams pasting customer or client data into ChatGPT, Claude, or Gemini for support and drafting, Developers using Codex, Claude Code, Cursor, or Windsurf who don't want production secrets in prompts, Compliance-minded orgs mapping AI usage to GDPR, DORA, or internal data-handling policy. Free to use.

Compared withvs Sublime Security vs Audioeye vs Push Security

What people actually say about Pasteguard — is it worth it?

We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.

38 mentions across 3 sources (Hacker News, YouTube, GitHub) · researched Aug 1, 2026.

55% positive45% critical

Average across the 3 sources that answered — each source counts once, not each post.

Recurring strengths

+Free and open-source (Apache 2.0) with a local-first architecture.
+Automatically detects over 30 types of PII and secrets.
+Preserves AI context by replacing data with placeholders like [[EMAIL_1]].
+Supports multiple AI providers: ChatGPT, Claude, Gemini, and coding agents.
+Self-hostable via Docker with a single command.

Recurring frustrations

−Reliability issues: 400 errors with Claude Code and long-context DOMException.
−Docker startup crashes reported by some users.
−Limited community support and sparse documentation for integrations.
−Configuring with LibreChat and other tools requires manual setup.
−Experimental browser extension may be flaky.

Patterns worth knowing

Strong need for privacy with cloud LLMs, but reliability gaps hold back adoption.

Seen on Hacker News, GitHub

Open-source and free nature is a big plus, but users want more documentation and examples.

Seen on Hacker News, GitHub

Specific integration problems with Claude Code and LibreChat frustrate users.

Seen on GitHub

Learning curve

intermediateProductive in ~A few hours

Hidden costs people mention

• Cost of running your own server or Docker host.
• Time spent configuring and debugging integrations.

Viability Score

67/100

Monitor

How well maintained and how widely used is Pasteguard? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this

Recent activity

not measured

Traction

100

Site health

User sentiment

What the vendor publishes

Last calculated: October 2026

How we score →

Key Features

Detects over 30 private data types including names, emails, phone numbers, credit cards, IBANs, EU VAT numbers, IP
Detects secrets including API keys, SSH keys, JWT tokens, passwords, connection strings, private keys, and bearer tokens
Replaces sensitive values with placeholders such as [[PERSON_1]] and [[EMAIL_1]]
Restores original values in responses where supported
Browser extension (beta) for ChatGPT, Claude, and Gemini
⌘⇧K keyboard shortcut to mask selected text before it reaches the provider
OpenAI-compatible HTTP proxy at http://localhost:3000/openai/v1 (set as OPENAI_BASE_URL)
Anthropic-compatible HTTP proxy at http://localhost:3000/anthropic (set as ANTHROPIC_BASE_URL)
Masks .env files and config context for Codex, Claude Code, Cursor, and Windsurf
Mask mode: placeholder replacement with optional response restoration
Live dashboard showing scan time, masked %, PII types, model, and language
Detects private data in any language; dashboard shows EN, IT, ES, and FR traffic
One-command Docker install; runs locally or self-hosted under Apache 2.0 with no telemetry

About Pasteguard

FreeIntermediateAPI availableWeb · API · Plugin

PasteGuard is an open-source, self-hosted privacy proxy that strips private data out of your text before it reaches ChatGPT, Claude, Gemini, or a model API. It detects over 30 categories of sensitive values — names, emails, phone numbers, credit cards, IBANs, EU VAT numbers, IP addresses, locations, API keys, SSH keys, JWTs, passwords, connection strings, private keys, and bearer tokens — then swaps each for a placeholder like [[PERSON_1]] or [[EMAIL_1]]. The model keeps enough context to answer, and the originals stay on your infrastructure. GitHub shows 767 stars on the project. There are three entry points. A browser extension (beta; the vendor labels earlier builds experimental) covers ChatGPT, Claude, and Gemini, and a ⌘⇧K shortcut masks selected text before the provider sees it. For your own apps, PasteGuard exposes OpenAI-compatible (http://localhost:3000/openai/v1) and Anthropic-compatible (http://localhost:3000/anthropic) endpoints, so you change a base URL and route traffic through the proxy. For coding agents like Codex, Claude Code, Cursor, and Windsurf, it masks values in .env files and config context so production credentials stay out of prompts. Setup is one Docker command — docker run --rm -p 3000:3000 ghcr.io/sgasser/pasteguard:latest — then open localhost:3000. A live dashboard reports per-request scan time, masked percentage, detected PII types, model, and language (the sample view shows EN, IT, ES, and FR traffic). Mask mode swaps values for placeholders and restores them in responses where supported. It suits teams that cannot paste raw customer data, client files, or secrets into cloud AI — those under GDPR, DORA, or client-confidentiality pressure. The vendor is explicit that PasteGuard reduces what reaches AI providers and that your own legal and security controls still decide compliance. Compare it to hosted redaction APIs and provider-side guardrails, which move the boundary off your infrastructure.

Behind the Verdict

The question PasteGuard answers is narrow and useful: how do we let people use ChatGPT, Claude, or a model API without handing over client names, emails, and production keys? You run one Docker container, point your BASE_URL at it, and the model receives [[PERSON_1]] instead of a real name. The honest reason we'd pick it is auditability. Apache 2.0, no telemetry, and the whole detection pipeline on your own hardware means a security reviewer can actually read the code and prove where data goes. Hosted redaction APIs can't offer that, because the boundary lives in someone else's cloud. Where it bites: the ChatGPT/Claude/Gemini extension is beta, so test it against your real prompts before rolling it out broadly. Response restoration only happens where supported, which means a workflow relying on getting exact original values back can surprise you. And the vendor's own framing matters — it reduces what reaches providers, it does not make you compliant on its own. On the API side, swapping the base URL is a small change with a big payoff for developers who already centralize their SDK calls. For coding agents the .env masking is arguably the most immediate win: the demo masks DATABASE_URL, OPENAI_API_KEY, and AWS credentials before they enter a Cursor or Claude Code prompt. Pick PasteGuard if you can run Docker, want the boundary self-hosted, and need a single layer across chat, APIs, and coding agents. Pass if you need a managed service with a support contract, or if outbound traffic to any cloud model is off the table — non-sensitive requests still go to the provider you configured. Closest alternative logic: hosted PII-redaction APIs and provider-side guardrails are easier to adopt but put the boundary in a vendor's hands. For teams whose policy says otherwise,

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Real-world workflow fit

Concrete scenarios for the personas Pasteguard actually fits — and what changes day-one when you adopt it.

Support team lead at a company handling customer data

You install the PasteGuard container, point the browser extension at ChatGPT, and your agents highlight a ticket with ⌘⇧K before pasting it, so the model sees [[PERSON_1]] and [[EMAIL_1]] instead of the real customer.

Outcome: Agents keep using ChatGPT for drafting without raw customer names and emails crossing the provider boundary, and the dashboard shows the masked percentage per request.

Developer using Claude Code or Cursor on a production repo

You set your coding agent's base URL to http://localhost:3000/anthropic (or /openai/v1) and let PasteGuard mask .env.local, so DATABASE_URL, OPENAI_API_KEY, and AWS credentials arrive as placeholders.

Outcome: The agent still reasons about your config, but API keys, passwords, and connection strings from the project never land in the prompt.

Platform engineer at a regulated firm

You run PasteGuard in front of an internal AI app via the OpenAI-compatible endpoint, enable logging and detector settings, and keep sensitive requests on a local LLM with Route mode.

Outcome: The privacy boundary stays on your own infrastructure and is auditable under Apache 2.0, with your legal team owning the compliance call rather than outsourcing it.

Use Cases

Mask customer names and emails before pasting support tickets into ChatGPT.
Redact API keys from .env files when using Claude Code or Cursor for code review.
Protect patient health information before submitting clinical data to a medical AI API.
Filter credit card numbers from chat conversations when using Gemini for customer service.
Avoid leaking JWT tokens while debugging authentication issues with a coding agent.
Put a self-hosted masking proxy in front of an internal AI product via the OpenAI-compatible endpoint.

Models Under the Hood

gpt-5.2

as of 2026-10-17

Limitations

PasteGuard masks names, emails, API keys, and other private data before they reach AI providers like ChatGPT, Claude, and Gemini, but the browser extension for those providers is labelled experimental and beta.
Route mode keeps sensitive requests on a local LLM while other requests go to the configured cloud provider, so it is not a zero-egress mode.
Placeholders like [[PERSON_1]] and [[EMAIL_1]] replace sensitive values, with originals restored in responses only where supported.
GLiNER is one documented semantic detection backend.

as of 2026-10-11

Verification history

We have re-verified Pasteguard 10 times since Jul 3, 2026. Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.

Oct 18, 2026 — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Oct 9, 2026 — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Sep 22, 2026 — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Aug 31, 2026 — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Aug 25, 2026 — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Aug 16, 2026 — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it

Showing the 6 most recent of 10 verification passes.

Free to cite with attribution — this page re-verifies continuously.

12-month cost

Project the real annual outlay, including the implied monthly cost when only an annual tier is published.

Plan

Annual total

Free

Over 12 months

Effective monthly

—

Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.

Plans compared

For each published Pasteguard tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.

Open Source (Apache 2.0)

Ideal for

Teams that can run Docker and want the privacy boundary on their own infrastructure — support teams pasting tickets into ChatGPT, developers guarding .env secrets from coding agents, and regulated orgs under GDPR or DORA pressure.

What this tier adds

Starting tier and the only published tier: $0, self-hosted, covering the 30+ PII and secret detectors, the OpenAI- and Anthropic-compatible proxy endpoints, the experimental browser extension, Mask and Route modes, and a live dashboard with no telemetry.

Hidden costs & gotchas

What the public pricing page doesn't put in bold. Captured from pricing-page footnotes, contract terms, and recurring complaints.

Running Route mode means standing up and paying for a local LLM of your own, on top of any cloud AI subscriptions you already have.
Masking is only as good as the detectors you enable — tuning GLiNER or other semantic backends and maintaining detector config becomes ongoing work for whoever owns the deployment.
The proxy sits in the request path, so you carry the operational cost of running, logging, and upgrading the container yourself rather than paying a vendor to do it.
Response restoration only happens where supported, so some answers come back with placeholders your team has to map back by hand.

Where the pricing makes sense

The company stage and team size where Pasteguard's pricing actually pencils out — and where peers do it cheaper.

Setup time & first value

How long it actually takes to get something useful out of Pasteguard — broken out by persona, not the marketing-page minute.

Switching to or from Pasteguard

How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.

Migrating in

→From manual redaction before pasting into ChatGPT: change nothing about your chat workflow, install the extension, and highlight text with ⌘⇧K before the provider sees it.
→From provider-side guardrails or hosted redaction APIs: move the boundary onto your own infrastructure by running the container and pointing your SDK base URL at the local proxy.
→From custom masking code in each app: replace per-app redaction with one proxy endpoint at http://localhost:3000/openai/v1 or http://localhost:3000/anthropic.

Migrating out

↗To a managed hosted privacy service: swap the self-hosted proxy for a vendor-run endpoint, trading local control for a support contract and vendor-managed updates.
↗To provider-side guardrails: remove the proxy and accept that the boundary sits on the model provider's infrastructure rather than your own.
↗To local-only models with no cloud forwarding at all: drop Route mode's split behaviour and keep every request on your own LLM.

Integrations

ChatGPT Claude GeminiOpenAI APIAnthropic APICodexClaude Code Cursor Windsurf

Resources & Guides

Tutorials & Learning

YouTube returned 6 videos for “Pasteguard”, and we withheld 6: 6 could not be judged, because “Pasteguard” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Pasteguard.

Official links

Official Website

Tools that pair well with Pasteguard

Common stack mates teams adopt alongside Pasteguard, with the specific reason each pairing earns its keep.

MemoryLake

MemoryLake is portable AI memory for ChatGPT, Claude, Codex and Gemini — encrypted, exportable, and shared across every agent you run.

PrivacyScrubber

Browser-based PII redaction that strips names, PHI and secrets from AI prompts in local RAM before they reach ChatGPT, Claude or Gemini.

Omnifact

Omnifact is a GDPR-compliant enterprise AI platform with a Privacy Filter™ that masks sensitive data before prompts reach external LLMs.

Featured Head-to-Head Comparisons

Pasteguard vs Sublime Security

These tools serve completely different purposes: Sublime Security is an enterprise-grade email security platform for detecting advanced phishing and BEC attacks, while Pasteguard is a free privacy proxy that masks PII before sending data to AI services. Choose Sublime if you need AI-driven email defense with low false positives; choose Pasteguard if you want to safely use cloud AI tools with sensitive data. They complement each other but don't compete directly.

Pasteguard vs Audioeye

If you need enterprise ADA/WCAG compliance with legal backup and are willing to pay, AudioEye is the clear choice. If your goal is to safely use cloud AI without exposing private data, Pasteguard's free, open-source, local-first approach is far more practical and cost-effective. They solve completely different problems—choose based on your primary need.

Pasteguard vs Push Security

Choose Push Security if you're an enterprise security team facing browser-based attacks (AiTM, session hijacking, shadow AI) and need real-time visibility across all browsers. Choose PasteGuard if you're a developer or small team that simply wants to mask PII before it reaches AI services like ChatGPT or coding agents, with a free, local-first, open-source tool. They target different problems: Push is for defense-in-depth against sophisticated threats; PasteGuard is for privacy compliance in AI usage.

Alternatives to Pasteguard

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Frequently Asked Questions

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Topics

Automation API Data Analysis Open Source

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