Shadow vs Lasso Security — open-source Lasso alternative for GenAI data protection

Lasso Security is a GenAI security platform with a browser extension and gateway; its contextual data protection lets teams describe policies in plain English and then masks sensitive data or raises alerts. Shadow is an open-source privacy layer that translates sensitive values in AI API requests into realistic, reversible fakes and restores them in the response. Lasso offers policy-driven governance across people and apps; Shadow focuses on keeping values out of provider requests without breaking answers, streams or agents.

TL;DR

Lasso brings natural-language, contextual policies and central visibility to GenAI use, with masking or alerting. Whether it restores masked values in responses is not publicly documented. Shadow uses consistent, format-preserving fakes and restores them in streams, tool calls and files, locally and for free.

At a glance

	Shadow	Lasso Security
Open source / licence	Yes, Apache-2.0	No, commercial
Deployment	Endpoint HTTPS proxy, gateway (/gw/<provider>/), Rust library	Browser extension, gateway, SaaS console
Protection method	Reversible realistic fakes from a persona; typed tokens for reports; optional redaction	Mask or alert, driven by contextual policies
Restores responses	Yes, automatically	Not documented
Streaming	Yes, SSE and NDJSON with split-fake reassembly	Not documented
Tool calls	Yes, arguments restored locally; intent-aware for provider-hosted tools	Not documented
Files	DOCX, XLSX, PPTX masked in place; PDF to text; CSV, JSON, HTML	Not documented
Self-hosted	Yes, single binary, no account	Not documented
Price model	Free	Quote

What Lasso does well

• Plain-English policies. Security teams can describe what must not be shared (“pricing for unreleased products”, “customer health data”) instead of building regexes, which suits data that patterns cannot capture.
• Context over patterns. Contextual evaluation can catch sensitive business information that has no fixed format.
• People and applications. An extension for employee use and a gateway for applications give two enforcement points.
• Central visibility. Security teams get a view of GenAI use and policy events across the organisation.
• Masking as well as alerting. Masking lets work continue rather than stopping it outright.

Where Shadow is different

Masks that the model can still use

A mask such as **** or [NAME] removes meaning. Shadow replaces each value with a realistic fake from a persistent persona: jane@acme.com becomes hui.zhao@zhilan.cn, IBANs pass mod-97, codenames become other plausible codenames. The same real value always gets the same fake, so multi-turn conversations stay coherent.

Can Lasso restore values in responses, streams and tool calls?

Public documentation we checked does not describe restoration. Shadow restores fakes in JSON responses, SSE and NDJSON streams and tool-call arguments on your machine, so agents act on real targets.

Intent-aware policy

Shadow’s policy is less flexible in wording than Lasso’s natural-language rules, but it decides how to transform each value based on intent: typed tokens for reports, kept recipients and provider-hosted action targets, fakes elsewhere. See intent-aware policy.

Files

Shadow masks DOCX, XLSX and PPTX uploads in place and turns PDFs into masked text. See file masking.

Open source and local

No account, no telemetry, and no plaintext sent to a vendor cloud.

When should you choose Lasso?

• You want to express data policies in plain English for information without a fixed format.
• You need central visibility and governance over GenAI use by people and apps.
• Masking or alerting, without restoration, fits your workflows.
• You want a commercially supported platform.

When should you choose Shadow?

• You need masked values restored in answers, streams and tool calls.
• Developers, agents and services call model APIs directly.
• You want Office uploads masked before they leave.
• You want an open-source, self-hosted control with no licence cost.

Using Lasso and Shadow together

1. Use Lasso for employee browser use, contextual policies and central visibility.
2. Install Shadow on developer machines, CI runners and services that call model APIs (proxy mode, gateway mode).
3. Mirror the most important Lasso policies in Shadow as dictionary terms for names, customers and codenames.
4. If both sit in the API path, put Shadow nearest the application so downstream tools only see masked content.

How do they compare on accuracy?

Lasso does not publish detection results on public PII datasets that we could find. Shadow publishes its methodology on the benchmarks page.

Sources

• Lasso Security launches contextual data protection for GenAI applications
• Lasso Security
• Shadow: personas

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Last reviewed: 2026-10-31. Lasso Security is a trademark of its owner; this comparison is based on public documentation as of the review date.

Frequently asked questions

Is Shadow a free alternative to Lasso Security?

For masking data in AI API traffic, partly. Shadow is free and open source and replaces sensitive values with reversible fakes on the machines where it runs. Lasso Security is a commercial GenAI security platform with a browser extension, gateway and central policies that Shadow does not replicate.

What is Lasso's contextual data protection?

Lasso lets security teams write data-protection policies in plain English, which are applied contextually rather than as fixed patterns. Its extension can mask sensitive data or alert, according to the company's launch announcement.

Does Lasso restore masked values in AI responses?

Public documentation we checked does not say. Shadow restores its fakes in responses, SSE streams and tool-call arguments locally.

How much does Lasso Security cost?

Pricing is by quote. Shadow is free under Apache-2.0.

Can Lasso and Shadow be used together?

Yes. Lasso can govern employee and application AI use with contextual policies while Shadow masks the content of API, agent and developer traffic on the endpoint.