Compare/Agent Armor vs Mozilla 0DIN AI Scanner

AI tool comparison

Agent Armor vs Mozilla 0DIN AI Scanner

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

A

Security

Agent Armor

Zero-trust Rust runtime that governs every AI agent action before it runs

Ship

75%

Panel ship

Community

Paid

Entry

Agent Armor is a lightweight governance layer for AI agents, written in Rust and designed to intercept every agent action before execution. It sits in front of LangChain, CrewAI, AutoGen, or Claude Code and runs each proposed action through an 8-stage decision pipeline: intent classification, credential leak scanning, rate limiting, resource scoping, behavioral fingerprinting, semantic deduplication, human-review escalation, and final allow/block. The project is MCP-aware and can intercept tool calls at the protocol level, which means it works regardless of which agent framework you're using. Actions that pass all 8 layers execute normally; those that fail can be automatically blocked, held for human review, or rewritten to a safer equivalent. A live dashboard shows agent activity, pending reviews, and anomaly alerts. Version 0.3.0 arrived as a Show HN today and hit the front page. The author, Edoardo Bambini, built it after a production incident where a coding agent attempted to overwrite git history on the main branch. The timing is good — as more teams ship agents to production, "what guardrails do I put between the agent and the real world?" is an increasingly urgent question.

M

Security

Mozilla 0DIN AI Scanner

Battle-tested LLM security scanner from the team that broke every frontier model

Ship

75%

Panel ship

Community

Free

Entry

Mozilla's AI security team — 0DIN (Zero Day Investigation Network) — open-sourced their internal LLM vulnerability scanner on April 10, 2026. Unlike synthetic red-teaming tools, this is built on real attack knowledge: 0DIN researchers have spent two years getting paid to break every major frontier model, discovering and reporting thousands of verified vulnerabilities. Those discoveries are now encoded as reproducible probes. Built on NVIDIA's GARAK open-source framework, the 0DIN Scanner adds a graphical interface, automated scan scheduling, cross-model comparative analysis, and enterprise reporting. It ships with 179 community probes covering 35 vulnerability families — prompt injection, jailbreaks, data leakage, harmful content generation, and more — all aligned to the OWASP LLM Top 10. Six specialty probes target advanced threat categories. For any team deploying LLMs in production — RAG systems, agents with tool access, customer-facing chatbots — this is now the baseline for security auditing. The Apache 2.0 license means enterprise deployment without legal headaches. With LLM security audits running $50K-$200K from specialist firms, this democratizes access to professional-grade testing.

Decision
Agent Armor
Mozilla 0DIN AI Scanner
Panel verdict
Ship · 3 ship / 1 skip
Ship · 3 ship / 1 skip
Community
No community votes yet
No community votes yet
Pricing
Open Source (MIT)
Free, Open Source (Apache 2.0)
Best for
Zero-trust Rust runtime that governs every AI agent action before it runs
Battle-tested LLM security scanner from the team that broke every frontier model
Category
Security
Security

Reviewer scorecard

Builder
80/100 · ship

I've been looking for exactly this: a framework-agnostic safety layer I can drop in front of my agents without rewriting them. The credential leak scanning alone is worth the integration cost — agents have a bad habit of echoing secrets into tool calls.

80/100 · ship

Every team shipping LLM features in production should be running this in CI. The OWASP LLM Top 10 alignment means it maps directly to compliance frameworks. The fact that it's built from actual vulnerabilities found in frontier models — not synthetic prompts — gives it way more credibility than competitors.

Skeptic
45/100 · skip

An 8-stage pipeline on every agent action is a lot of latency overhead, especially for interactive agents. And sophisticated attackers will study the classifier patterns — once Agent Armor is widely deployed, the 8 stages become an adversarial target. This is good for basic hygiene, not a security guarantee.

45/100 · skip

GARAK-based scanners catch known vulnerability patterns, but novel attacks will always slip through static probe libraries. The graphical interface is serviceable but not polished enough for non-technical security teams. And 179 probes sounds like a lot until you realize a dedicated red teamer generates thousands of custom vectors in a day.

Futurist
80/100 · ship

The agent governance market will be worth more than the agent framework market within 3 years. As AI agents take real-world actions with real consequences, something has to sit between the model and the world. Agent Armor is an early but serious attempt at the right architecture.

80/100 · ship

As LLM agents gain tool access and real-world power, security becomes existential not optional. Mozilla's decision to open-source two years of hard-won attack knowledge is a rare act of public benefit in a space dominated by consulting firms charging enterprise rates. This becomes the industry standard within 12 months.

Creator
80/100 · ship

The dashboard is beautifully designed for a security tool — clear threat visualization, pending review queue, agent behavior timeline. I actually want to run this just to see what my agents are attempting even when nothing looks wrong.

80/100 · ship

Even content teams using AI for copywriting or customer service need to know their models won't be jailbroken into producing harmful outputs. This gives non-technical managers a report they can actually present to legal. That's underrated value.

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