AI Tool

zn Review

zn is an open-source security proxy for AI agents, designed to provide sacrificial protection against prompt injections and secure Multi-Cloud Platform (MCP) infrastructure.

shipped Aug 25, 2026researchfreemium

research

Why it matters

1Offers a freemium pricing model with a Free Trial and paid tiers starting at $19/month.

2Provides sacrificial protection for every agent tool call against prompt injections.

3Features a multi-layer defense system including WASM policies, PII scrubbing, and cryptographic audit trails.

4Includes a real-time prompt analysis system and supports user-conducted attack corpus tests.

About zn

Business Model

Subscription SaaS

Usage Pricing

$0.002/call per api-call

Platforms

Web, API

Target Audience

Developers and organizations utilizing AI agents

Pricing Plans

Free Trial

Free

• 48-hour free run
• No card required

Hobby

$19/mo

• 10,000 calls/mo
• $0.002/call overage

Starter

$49/mo

• 75,000 calls/mo

Growth

$149/mo

• 350,000 calls/mo

Enterprise

Custom / monthly

• Unlimited calls/mo

Starter pack

$9 / one-time

• 5,000 calls

Pro pack

$40 / one-time

• 25,000 calls

Scale pack

$140 / one-time

• 100,000 calls

Cost Examples

• 5,000 calls for $9
• 25,000 calls for $40

API Docs GitHubOpen Source

overview

What is zn?

zn is an open-source security proxy tool developed by NetSim Labs that enables AI Developers, Security Engineers, and DevOps Engineers to secure Multi-Cloud Platform (MCP) infrastructure for AI agents. It provides sacrificial protection for every agent tool call against prompt injections, leveraging a multi-layer defense system with WASM policies, PII scrubbing, and cryptographic audit trails. Users can conduct their own attack corpus tests and access a real-time prompt analysis system to enhance the security and trustworthiness of AI agent operations.

features

Key Features of zn

zn incorporates a comprehensive suite of security primitives and features designed to protect AI agent deployments. Its architecture emphasizes zero-trust principles and real-time threat detection.

Sacrificial protection for every agent tool call against prompt injections.
Multi-layer defense system with WebAssembly (WASM) policies.
Personally Identifiable Information (PII) scrubbing for sensitive data handling.
Cryptographic audit trails with an evidence vault utilizing SHA-256 hashing.
Real-time prompt injection detection and blocking capabilities.
Agent identity verification and role-based access control (RBAC).
Post-Quantum cryptography (Ed25519 + ML-DSA (Dilithium3) hybrid signatures).
SIEM Exporter for real-time streaming of logs to platforms like Splunk, ElasticSearch, and Datadog.
Deterministic rules engine for policy enforcement.
Open-source core available on GitHub (github.com/tljohnsilver/zn).

use cases

Who Should Use zn?

zn is primarily designed for technical professionals and organizations deploying and managing AI agents in environments requiring robust security and compliance.

AI Developers: For integrating a zero-trust security layer into their AI agent applications and ensuring secure API calls.
Security Engineers: For implementing real-time prompt injection detection, PII scrubbing, and cryptographic audit trails for AI agent deployments.
DevOps Engineers: For securing Multi-Cloud Platform (MCP) infrastructure for AI agents and managing agent identity with RBAC.
Organizations deploying AI agents: For achieving compliance and monitoring through SIEM exportable audit trails and protecting against advanced cybersecurity threats.

how to use

How to Use zn

To utilize zn, users typically integrate its security proxy into their AI agent deployment workflow, configuring policies for prompt injection defense and data handling. The platform offers both web-based access and an API for programmatic control.

1Access the zn platform via the web interface at usezn.com or integrate through its API.
2Configure WASM policies to define security rules for AI agent tool calls.
3Implement PII scrubbing to automatically redact sensitive data processed by agents.
4Utilize the real-time prompt analysis system to monitor and detect potential injection attempts.
5Conduct attack corpus tests to evaluate the effectiveness of the multi-layer defense system.
6Export cryptographic audit trails to SIEM systems (e.g., Splunk, ElasticSearch, Datadog) for compliance and monitoring.

pricing

zn Pricing & Plans

zn operates on a freemium model, offering a free trial and various subscription tiers, alongside usage-based pricing for API calls. One-time packs are also available for specific call volumes.

Free Trial: Free for 48 hours.
Hobby: $19/month (monthly billing).
Starter: $49/month (monthly billing).
Growth: $149/month (monthly billing).
Enterprise: Custom pricing (monthly billing).
Starter pack: $9 (one-time) for 5,000 API calls.
Pro pack: $40 (one-time) for 25,000 API calls.
Scale pack: $140 (one-time) for a higher volume of API calls.
Usage Pricing: $0.002 per API call.

Pros

+Provides sacrificial protection specifically for agent tool calls, a targeted defense mechanism.
+Incorporates a multi-layer defense system including WASM policies and PII scrubbing for comprehensive security.
+Offers cryptographic audit trails with SHA-256 hashing and SIEM export for compliance and monitoring.
+Features real-time prompt analysis and allows users to conduct their own attack corpus tests.
+Open-source core available on GitHub, fostering transparency and community contributions.
+Supports Post-Quantum cryptography (Ed25519 + ML-DSA (Dilithium3) hybrid signatures).

Cons

−The 'sacrificial protection' mechanism may introduce overhead or complexity in agent architectures.
−Specific user reviews and reception for the open-source ZN security layer are not widely available.
−The provided URL (usezn.com) is a forwarding email domain, which could initially cause confusion for users seeking product information.
−Requires integration into existing AI agent deployments, which may involve development effort.
−While open-source, commercial offerings or support from NetSim Labs may incur additional costs.

Similar Tools

zn vs Competitors

zn differentiates itself in the AI security landscape by focusing on a zero-trust, open-source security proxy specifically for AI agent deployments, emphasizing sacrificial protection at the tool call level.

LLM Guard↗

LLM Guard is an open-source toolkit for sanitizing and redacting LLM prompts and responses, offering a variety of scanners for different types of threats.

While LLM Guard provides a comprehensive set of scanners for prompt and response sanitization, it requires more manual integration and configuration compared to Zn30's potentially more integrated 'sacrificial protection' for agent tool calls. It's a toolkit you build with, rather than a plug-and-play service.

Guardrails AIOn Stork

Guardrails AI is an open-source library that allows developers to define and enforce constraints on LLM outputs, including validation, correction, and re-prompting.

Guardrails AI focuses on ensuring the quality and safety of LLM outputs through validation and re-prompting, which can indirectly help with injection defense by controlling responses. Zn30 specifically targets proactive protection against prompt injections at the agent tool call level, whereas Guardrails AI is more about post-processing and enforcing output structure and safety.

Rebuff↗

Rebuff offers an API and SDK to detect and prevent prompt injection attacks using a combination of heuristics, LLM-based detection, and a honeypot defense.

Rebuff provides a dedicated API for prompt injection detection, similar in purpose to Zn30's defense system. However, Zn30 emphasizes 'sacrificial protection for every agent tool call' and real-time analysis, which might imply a more deeply integrated or agent-specific defense mechanism than Rebuff's API-centric approach.

See every zn alternative, compared→

Related AI Tools

Other tools in this category, matched by shared tags

Unitovo PetNid Magdox LingCode MaruCheck EMSYO

Visit zn↗

Connect

𝕏

X / Twitterx.com/use_zn

⌘

GitHubgithub.com/tljohnsilver/zn