// moorai vs sentinelone

MoorAI vs SentinelOne

SentinelOne’s AI security is the former Prompt Security — the GenAI-security startup SentinelOne acquired in 2025 and folded into its Singularity platform. It is a broad offering: prompt-injection defense, DLP for generative-AI apps, and a real-time AI firewall, delivered as a browser extension, a gateway / reverse-proxy, and an API that fronts your own AI applications — now marketed as Prompt Security for Employees, for AI Code Assistants, and for AI Agents, alongside the Purple AI agentic SOC analyst. Its reach is the whole organization: it will “Redact sensitive data and enforce policies across 15,000+ AI services in real time” and “scrub sensitive outputs with a real-time AI firewall”, and its browser extension “prevents sensitive information disclosure to GenAI tools”. (sentinelone.com / Chrome Web Store)

That breadth is the point, and it is genuine. One enforcement point over every employee’s ChatGPT, Claude and Gemini use and thousands of SaaS AI tools; inline redaction of PII, secrets and source code from prompts and responses; automated red-teaming of your own AI apps before they ship — all inside a full XDR / EDR platform with SOC automation. MoorAI attempts none of that and has no roadmap to. If the requirement is org-wide GenAI DLP across the whole company — every employee, every chatbot, every homegrown app — that is their product, not ours.

MoorAI is narrower and deeper. It is on-device security for AI coding agents — Claude Code, Cursor, Copilot CLI, Claude Desktop — a governance layer, not a sandbox: a PreToolUse hook inside the agent, an MCP stdio proxy in front of the tool servers, and a companion browser extension. It scores each prompt and each action on the device against a 67-threat matrix mapped to the OWASP LLM Top 10, MITRE ATLAS and STRIDE, and decides before the call runs.

And the real line between them is not cloud versus local. SentinelOne can be self-hosted, and the extension does some detection client-side, so “it’s a cloud service” would be too glib. The line is content. Its mechanism is to read the text and redact it — an AI firewall that scrubs a prompt has to see the prompt. MoorAI’s mechanism is content-free by architecture: detection runs on the device and only category · risk · a keyed one-way hash (HMAC-SHA-256) ever leaves it. The agent is AGPL-3.0, so that claim is auditable rather than asserted. Two honest exceptions, stated not buried: an administrator can turn on a capture tier that does store the matched text it was enabled to collect, and where the OS cannot OCR an image locally a pasted screenshot goes to your own AI provider for text extraction, never to us.

yes partial unconfirmed no

Where MoorAI goes deeper

Agent-native depth, and the content-free evidence trail that comes with it. A firewall blocks and redacts what an agent is about to transmit; an action-centric governor blocks the call before it runs — including local tool activity that never crosses the network for a proxy to inspect.

MoorAI SentinelOne
No content-bearing telemetry, by architecture — verifiable
Only category · risk · keyed one-way hash leave the device
Open source (AGPL-3.0) — the content-free claim is auditable
Action interception — blocks the tool call before it executes, not just the egress
On-device MCP tool-call gateway over stdio (local servers that never touch the network)
Per-tool MCP argument rules at call time
Transit-override detection — HTTPS_PROXY + CA-override env injection
On-device OCR of pasted screenshots (macOS Vision / Windows OCR) — no image egress
On-device semantic second opinion without content leaving the device (opt-in, default off)
Sees local tool activity that never crosses the network
Content-free data lineage / Event Flow
Cryptographically signed, tamper-evident decisions
JIT elevation + entitlement envelope
Per-agent assurance score
Lethal-trifecta / cross-server toxic-flow detection
Break-glass / offline fail-closed
Free for the whole org up to 200 users — in-app signup, auto-enroll, free download

Where the two genuinely overlap

SentinelOne’s AI work — the Prompt Security engine — is real and specific, and it is worth stating plainly rather than marking it absent. It names the same coding agents MoorAI wraps, inspects prompts and outputs, discovers shadow AI, maps MCP servers, and verifies the integrity of agent skill and configuration files — a direct analog of MoorAI’s rules-file poisoning detection. Anyone evaluating both should expect a real overlap here.

MoorAI SentinelOne
Reviews prompts before they reach any model / API
Reviews AI output, not just prompts
Prompt-injection / jailbreak detection
Shadow-AI discovery
Names the coding agents explicitly (Claude Code, Cursor, Copilot)
Model / AI-service allow-list + policy enforcement
MCP server discovery / inventory
Skill / agent-config integrity analysis
Browser GenAI prompt interception across major AI chat apps (ChatGPT, Claude, Gemini)
MDM fleet rollout (Intune / Jamf) with a signed installer

Where SentinelOne covers more ground

This is the honest half of the page. Because the Prompt Security engine inspects content in the path — and because it is aimed at the whole organization rather than one class of developer tool, now inside a full XDR platform — SentinelOne covers a large surface MoorAI does not attempt and has no plan to. If the requirement is “one guardrail over every employee’s AI use, with inline redaction, wired into the SOC,” that is their product and not ours.

MoorAI SentinelOne
Org-wide GenAI DLP across every employee — not just developers
Thousands of SaaS AI tools covered with no integration (15,000+ AI services)
Governs AI chat in the browser (ChatGPT, Claude, Gemini) fleet-wide
Inline redaction / scrubbing of PII, secrets and source code from prompts and outputs
Real-time AI firewall in front of your own homegrown / production AI apps
Pre-deployment red-teaming — automated prompt-injection / jailbreak testing of your AI apps
Full XDR / EDR endpoint platform (SentinelOne Singularity)
Agentic SOC analyst (Purple AI) — natural-language investigation & response
Centralized enterprise policy console over the whole organization
SIEM / SOC integration + enterprise support at platform scale

The rows worth explaining. On content leaving the device we do not mark SentinelOne absent out of spite — we mark it ✗ because the Prompt Security mechanism requires reading the content to redact it, and it publishes no content-free egress guarantee. MoorAI emits category · risk · keyed one-way hash and nothing else, the agent is AGPL-3.0, and anyone can read the code and confirm there is no content path off the device — that is what the marks reflect, not an accusation. And on browser AI chat MoorAI is honestly partial: a companion extension covers the major chat surfaces, where SentinelOne’s extension is built for exactly that job across the whole fleet and 15,000+ services.

Where MoorAI is stronger. The tool call, and the record of it. SentinelOne’s AI enforcement is content- and egress-centric: it inspects what an agent is about to transmit and redacts or blocks it. That is genuinely useful and it catches data leakage. It does not see the action — an agent about to run a destructive shell command, read a credential file, or drive a local MCP server over stdio whose filesystem, git and database calls never touch the network, so a content-inspecting firewall sees nothing at all. MoorAI sits at that exact point: allow-list the server, constrain the arguments, block before execution, and land a signed, content-free record mapped to ISO 42001, NIST AI RMF, the EU AI Act and the OWASP LLM Top 10.

Where SentinelOne is stronger. Breadth, inline redaction, and the platform. One guardrail over every employee’s GenAI use — thousands of SaaS tools, browser chat, and your own homegrown AI apps — with PII, secrets and source code scrubbed in real time, plus pre-deployment red-teaming and a full XDR / SOC platform behind it, is a real procurement argument MoorAI has no answer to. MoorAI is macOS, Windows and Linux and governs coding agents, not the whole company’s chatbot use. Those are different purchases for different problems.

Use both, honestly. They are more complementary than competitive. Run SentinelOne if you want one enforcement point over org-wide GenAI use with inline DLP across every employee and application, wired into an XDR/SOC platform. Run MoorAI where developers run coding agents with terminal and filesystem access, where you need the MCP layer governed at call time, and where the evidence an auditor reads must contain no one’s prompt content at all.

SentinelOne’s AI-security capabilities are the former Prompt Security, which SentinelOne announced its acquisition of in 2025 and is folding into the SentinelOne platform; they are mapped from SentinelOne’s and Prompt Security’s own published product and extension listings as of 2026, and quoted phrases are theirs (sentinelone.com, Chrome Web Store). ◐ = partial — present but narrower than the other column. — = unconfirmed, not necessarily absent: it marks a capability their published material does not clearly document. MoorAI marks reflect shipped capability. SentinelOne and Prompt Security are trademarks of their respective owners; this is an independent capability comparison, not an endorsement, and every product here evolves — verify specifics against their current documentation.

Recently shipped in MoorAI — all on-device and content-free: a content-free browser extension guarding prompts across eight AI chat apps (ChatGPT, Claude, Microsoft Copilot, Gemini, Perplexity, Mistral, DeepSeek, Grok), a Linux endpoint tier alongside macOS and Windows (on-device OCR first-class on macOS and Windows, opportunistic on Linux), an opt-in, default-off on-device model second opinion that stays on the device (loopback Ollama or your own provider key), MDM fleet rollout via Intune and Jamf, transit-override detection (flags HTTPS_PROXY + CA-override env injection that reroutes an agent’s traffic while the destination looks unchanged), Skill Analysis (a content-free inventory and intent-labelling of the entire skill surface an agent auto-loads — SKILL.md, subagents, slash commands, MCP configs, hook-bearing settings), a per-agent destination map of the hosts and MCP servers each agent actually reached, on-device OCR of pasted screenshots (macOS Vision / Windows OCR), a lethal-trifecta detector, rules-file poisoning detection (CLAUDE.md / .cursorrules), a per-agent assurance score, cryptographically signed agency decisions, and in-app signup with auto-enroll — scored against a 67-threat matrix mapped across the OWASP LLM Top 10, MITRE ATLAS, STRIDE, NIST AI RMF, ISO 42001 and the EU AI Act.

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glick.run — AGPL-3.0