Inside the Novee Gym: Training, Benchmarking, and Controlling Offensive AI That Thinks Like an Attacker

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Inside the Novee Gym: Training, Benchmarking, and Controlling Offensive AI That Thinks Like an Attacker

Register Now

Novee vs. Mindgard

The risk that causes breaches lives in your applications, not just your AI models.

Mindgard secures your AI model well, but attackers rarely stop at the model – they move through every part of the application attack surface, where Mindgard doesn’t test and where real breaches actually happen.

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Chosen by teams that take attackers seriously

Novee vs. Mindgard at a glance

Challenges with Mindgard

Mindgard is strong at model-layer security, but testing the model in isolation means it never reaches the application around it – and doesn’t close the loop.

Challenges with Mindgard:

  • AI model layer only

    Mindgard tests AI models and agents. It doesn't test the full application attack surface, including the APIs on the back end.
  • Model-risk findings

    Deliverables center on model-risk findings, not the working exploits and replication steps your team needs to act on with confidence.
  • Open loop

    Remediation and verification fall back to your team – no tailored fix, no automatic retest to confirm the risk is gone.
  • Undisclosed pricing

    Mindgard's pricing isn't public, making it hard to plan coverage or compare cost against what you're protecting.

Why Novee Over Mindgard?

AI penetration testing is only as valuable as the risk it can actually reach. Model coverage matters, but so do the applications around it – and proof you can act on.

Where Novee goes further:

  • Covers what Mindgard can't

    One platform for web, API, mobile, and AI apps – the whole attack surface, not just the isolated model layer.
  • Validated findings

    Three independent agents respectively exploit, re-exploit blind, and validate independently every finding. Every issue comes with a working exploit, replication steps, and a PoC script.
  • Tailored remediation

    Tailored remediation guidance for your architecture, WAF, and tech stack. Automatic retesting confirms the fix held and flags anything new introduced by the change.
  • Context that compounds

    Every cycle deepens understanding of your application's roles, workflows, and logic. Testing gets more targeted over time and never resets.
  • Business-logic depth

    Novee reasons about how your app works, finding authorization gaps and chained paths model testing can't reach.
  • Predictable pricing.

    Per-asset pricing means depth and frequency never cost extra. Test as often as needed without the bill scaling against you.

Novee vs. Mindgard Across Key Areas

Capability Novee AI Pentesting Mindgard
Approach

Tests the AI model in isolation. No persistent model of how the application works, what roles exist, or how components relate. The whole application stays untested.

Depth

Tests model behavior – prompt injection, jailbreaks, model extraction, adversarial attacks. It doesn’t reason about application business logic, so authorization gaps and workflow abuse never get tested.

Scope

AI model and agent testing; no broad application coverage.

Context & Memory

No compounding context across model test runs. Each run starts fresh, and nothing is carried forward.

Continuous Testing

Offers continuous AI-model monitoring.

Regression Testing

No closed-loop remediation, so no automatic verification that fixes hold.

False Positive Triage

Delivers model-risk findings, not working application exploits.

What security leaders say

“As the leading agentic orchestration platform for the enterprise, data isolation between our customers is non-negotiable. We need to prove that continuously, not once a year. Novee adapted to our multi-tenant SaaS product within days.”

Scott Roberts
CISO
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“Our pen tests took weeks and consistently missed critical issues. Novee found them immediately and gave us instant remediation guidance. It showed us what we'd been missing.”

John Barrow
CISO

"Traditional DAST produced either zero or irrelevant results. We needed something that could identify complex vulnerabilities like server-side request forgery. Novee consistently surfaces findings we simply weren't seeing before."

Robert Kugler
Head of Security, IT & Compliance

“Novee rethinks penetration testing for how attacks actually happen today. Continuous, attacker-level validation that proves what’s exploitable and shows teams exactly how to fix it is a meaningful shift for modern security programs.”

Troy Wilkinson
Former Fortune 500 CISO
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"The hardest vulnerabilities for us to catch aren’t misconfigurations or known patterns. They’re business logic issues that only show up when someone understands how the application is supposed to work. That’s exactly the gap Novee closes."

Tamir Ronen
CISO, HiBob

"We had EASM tools and manual pentests that produced mostly noise. Novee came in black-box with zero credentials and within days found dozens of real vulnerabilities we could actually fix."

Itzik Menashe
CISO, Global VP IT InfoSec & productivity

“As an AI researcher, what stood out about Novee is that they built a proprietary offensive AI model designed to think like an attacker, rather than wrapping generic LLMs. That matters for enterprise-grade results.”

Tal Shapira
PhD, CTO

“This was by far the deepest and fastest security assessment we’ve had. Novee uncovered issues across our web and mobile applications that had gone undetected before, and the level of depth was unlike anything we’d seen from other vendors.”

Amir Tito
CISO

“We had urgent compliance need and we couldn’t wait weeks for DAST findings, an external exposure audit, and an in-depth pentest report. Instead Novee came in and delivered immediate value with their AI pentesting platform; with their findings, we closed our gaps and quickly met the criteria we needed for certification.”

Ron Reiter
CTO

"Before Novee, we were getting a snapshot once a year. Now we have continuous coverage across our application portfolio, we're already finding things that prior manual pentests missed completely, and I have real confidence that our security posture reflects what's actually in our environment."

Abhijeet Patkar
Cyber Security Manager

"Novee takes the complexity out of penetration testing while providing transparent, step-by-step details of everything they do. Novee delivers the attacker-level validation we need to confidently close real external-domain exposures that other testing misses."

Anthony Gacayan
Senior Information Security Engineer

"Novee has become our main security testing system because they focus on the product itself, where most of our real risk sits and where other tools keep coming up short. With regulatory pressure building across our global markets, continuous, change-triggered penetration testing has become essential."

Ronen Rabinovich
Sr. Manager Product Security Lead

The Novee Advantages

Full-Surface Coverage

The Problem with Mindgard:

Mindgard secures the AI model well – prompt injection, jailbreaks, model extraction, adversarial attacks. But attackers rarely stop at the model. They move through the web layer, the APIs, and the business logic that wrap it, and that entire surface sits outside Mindgard's scope entirely.

How Novee Covers More:

Novee covers your entire attack surface as one offensive system – web, API, mobile, and AI apps. Mappers continuously chart everything an attacker can reach, while the Asset Intelligence Model learns how each asset actually works. AI red teaming runs alongside application pentesting, not as a separate tool. The risk that causes breaches almost always lives in the application layer – the web, the APIs, the business logic – and Novee tests all of it, every cycle, the way a real attacker would approach it.

Persistent Context & Memory

The Problem with Mindgard:

Mindgard tests the model, but it doesn't build a persistent model of the application under test, and it carries nothing forward between runs. Each assessment covers the model layer in isolation, with no compounding understanding of your application's roles, workflows, and business logic – the context that makes testing sharper and more targeted with every engagement over time.

How Novee Compounds Over Time:

Novee's Asset Intelligence Model persists and deepens with every cycle. Every discovery – endpoints, tokens, roles, leaked data, partial exploits – feeds back into the model and sharpens the next run. The system knows more on day 90 than day 1, and never forgets. Dismissed findings and reviewer feedback are incorporated so the same noise never surfaces again.

Validation and Proof

The Problem with Mindgard:

Mindgard reports model-risk findings, but leaves your team to work out what's genuinely exploitable in the running application – and how much of it is real. Findings alone aren't the same as real proof.

How Novee Proves It:

Novee puts every suspected vulnerability through a multi-agent validation pipeline – a finder, an independent validator, and a blind re-validator – plus deterministic checks that confirm exploitability before anything surfaces. Every finding that reaches your team comes with a working exploit, replication steps, and a PoC script. No false positives, no manual triage. Your team acts on what is proven, not what is suspected.

Tailored Remediation

The Problem with Mindgard:

Mindgard stops at the finding. Model-risk results come back for your team to interpret, but there is no remediation tailored to your architecture or tech stack, and no automatic retesting to confirm the fix actually worked once deployed to production.

How Novee Closes the Loop:

Novee guides teams from finding to verified fix. Because the Asset Intelligence Model captures your architecture and tech stack, remediation guidance is specific to your WAF, backend, and codebase – not generic OWASP references. Once a fix is deployed, Novee automatically retests to confirm the risk is resolved and checks for anything new introduced by the change. Risk is found, validated, remediated, and verified – continuously, as your environment keeps evolving.