Arcjet vs Rein Security

Arcjet vs Rein Security

Rein Security and Arcjet both reject the network proxy and secure agents from inside the runtime. Rein deploys as a sidecar next to your production application, observes every prompt, tool call, and resource an agent touches, maps each action to business impact, and adds application security testing. Arcjet enforces policy in the path of each action: an SDK check in your code before a tool or request runs, and the hooks of Claude Code, GitHub Copilot, Cursor, OpenAI Codex, and Muse Code, with HTTP bot detection, rate limiting, and WAF in the same SDK.

The key difference is how each product blocks. Rein's Protect Mode learns a baseline and blocks deviations from it, and Arcjet evaluates explicit policies that you write and dry run. Choose Rein when you want one deployment that watches the whole agent runtime and your application security posture. Choose Arcjet when you want explicit policy on each action, coverage for coding agents, and web application security alongside it.

Arcjet publishes this comparison. Competitor details come from Rein Security's public documentation, reviewed on September 25, 2026.

What is Rein Security?

Rein Security is an application and agent runtime security platform that describes its approach as "inside-out." Rein's platform page says Rein deploys as a sidecar at the "AI-Native Runtime" and captures every prompt, service call, tool invocation, and resource an agent touches, and who triggered it. Rein's Business Impact Analysis connects agent activity to business outcomes for audits under SOX, HIPAA, and the EU AI Act.

Rein's Protect Mode baselines agent behavior and blocks deviations in real time. Rein also emphasizes data sovereignty: you run Rein on your own servers instead of routing data through an outside gateway.

Rein isn't only an agent product. Rein's homepage lists software composition analysis (SCA), static analysis (SAST), and real-time API security alongside agentic workflows in one deployment. Rein's launch announcement describes an agentless architecture with under one millisecond of performance impact and no reliance on proxies, sampling, or eBPF.

Rein was founded in 2024, is based in Tel Aviv and New York City, and emerged from stealth on January 28, 2026, with an $8 million seed round led by Glilot Capital. Rein names Lemonade and HiBob as production customers. Rein's public pages don't list supported languages, pricing, or coding-agent integrations.

What is Arcjet?

Arcjet is an AI agent runtime security platform that discovers the agents running in your organization, enforces policy across every action, prompt, and tool call, and keeps the evidence to prove what happened. Arcjet enforces in the path of the action, in code or in the agent's hook, not on the network.

For agents and applications you build, the Arcjet JavaScript, TypeScript, Python, and Go SDKs provide guard() for tool calls, queue workers, and MCP handlers, and protect() for HTTP routes. Arcjet integrates with 15 agent frameworks, including the Claude Agent SDK, LangChain, LangGraph, Mastra, OpenAI Agents, the Vercel AI SDK, CrewAI, and Google ADK. You write Guard policies in Rego or a builder, run them in dry run, and publish them from the Arcjet Console or MCP server, with changes taking effect in real time.

For coding agents, Claude Code, GitHub Copilot, Cursor, OpenAI Codex, and Muse Code call Arcjet from the hooks they already fire, with no SDK and no code change. One Arcjet policy applies across all five agents, installed through managed settings so developers can't remove it without admin access.

Arcjet detectors cover prompt injection, sensitive information, destination threat analysis with Arcjet threat intelligence, and token budgets. On HTTP routes the same SDK adds bot detection, Shield WAF, rate limiting, and email validation. The Arcjet Console records every decision, and on the Enterprise plan decisions export to Datadog, Splunk, SentinelOne, Panther, and Amazon S3.

How do Rein Security and Arcjet differ?

Rein Security and Arcjet differ in 10 areas, from where each runs to how mature each product is. The following table lists them, and the sections after it cover the two that shape most decisions: a learned baseline versus an explicit policy, and coverage of coding agents.

A baseline versus an explicit policy

Rein's Protect Mode learns what normal agent behavior looks like and blocks deviations. A baseline catches behavior you didn't anticipate, and it needs a baseline period and tuning.

Arcjet decides on explicit rules that you can read, test, and review: deny a git push --force to main, deny a read of a credential file, or deny a refund above the limit for this plan. An Arcjet policy runs in dry run first, so you can see what it would block before it blocks anything.

Coding agents

Coding agents run on developer laptops and in CI, not in your production runtime, so a sidecar next to your application doesn't see them. Arcjet enforces on coding-agent tool calls through the hooks that Claude Code, GitHub Copilot, Cursor, OpenAI Codex, and Muse Code fire, so one policy covers the agents your developers use and the agents you ship. For more information, see how to secure AI coding agents.

Which questions separate Rein Security and Arcjet?

Five questions separate runtime agent security products in a bake-off: when enforcement happens, where coverage ends, whether prior actions count, what leaves your environment, and what happens when a check fails. Ask them of Arcjet too. The following list gives Arcjet's answers:

• Is enforcement pre-action or post-hoc? For Arcjet, the decision returns before the action runs.
• What is the coverage boundary? For Arcjet, coverage is wherever you put a check or install the hook: HTTP handlers, tool calls, jobs, and coding-agent events.
• Can the control use prior actions in a run when deciding the next one? A correlation ID ties Arcjet decisions to a run so the sequence is reconstructable for investigation.
• What leaves your environment? For Arcjet, SDK-local sensitive information inspection keeps the raw body in process. A server-side detector runs for coding-agent hooks. Rate-limit counters, bot reputation, and prompt injection detection use the Cloud API.
• What happens when a check can't finish? The direct guard() call fails open and returns ALLOW with an error result, which you can detect with hasFailedOpen(). Agent framework wrappers fail closed by default unless you opt in to continuing. For more information, see the Guards reference.

Who is Arcjet for?

Arcjet is for teams that want explicit policy on each agent action, in the agents they build and in their developers' coding agents. Choose Arcjet in the following situations:

• You want explicit, reviewable policy on each action, published centrally and tested in dry run.
• You need the same policy on Claude Code, GitHub Copilot, Cursor, OpenAI Codex, and Muse Code as on the agents you build.
• You want bot detection, rate limiting, and WAF rules in the same SDK as your tool-call checks.
• You want published pricing and a self-serve start.

Who is Rein Security for?

Rein Security is for teams that want one runtime deployment to observe agents and inform application security, with audit evidence tied to business impact. Choose Rein in the following situations:

• You want one sidecar deployment that discovers and observes the whole agent runtime without adding checks to each code path.
• Business impact analysis and audit evidence for SOX, HIPAA, or the EU AI Act are the main requirement.
• You also want SCA, SAST, and API security informed by production context from the same vendor.

Rein and Arcjet can run together, with Rein observing the production runtime and Arcjet enforcing explicit policy on specific actions and on coding agents.

What are the alternatives to Rein Security?

The alternatives to Rein Security include in-path enforcement, application-side evaluators, and agent security platforms with posture management. If you're evaluating Rein, the following products cover overlapping ground:

• Arcjet: policy on each action in code and in coding-agent hooks, with prompt injection, sensitive information, and destination threat detectors, plus web application security.
• Datadog AI Guard: an evaluator that your application calls, with policy in Datadog.
• Zenity: agent inventory, posture, and enforcement across SaaS, custom, and coding agents.
• Noma Security: discovery, posture management, red teaming, and runtime protection.

For the wider category, see AI agent security platforms.