NXT

Independent AI Security

We break your AI agent before someone else does.

NXT tests the agent you built or switched on the way an outsider would, in a sandbox, and writes down everything that gave way. Findings you can hand to a customer, an auditor, or a regulator. Fixed scope. Re-tested after you fix it.

  1. 01What We Test

    Your agent, as deployed.

    Custom builds, and the agents you switched on inside Microsoft 365 Copilot or Salesforce Agentforce. Chat, voice, email, documents, and the tools and records behind them. Tested where it runs, in a sandbox, with no production customer data.

  2. 02How We Test

    The full input surface, not just the prompt.

    Prompts, documents, images, hidden content, and the multi-step workflows where one bad interaction cascades. Every verdict is deterministic and repeatable: the same input produces the same result, with no AI grading AI.

  3. 03What You Get

    Findings you can hand to a regulator.

    A findings register with the exact input, the response, and the severity. Remediation mapped to the controls your team already has. Compliance mapping to the EU AI Act, NIST AI RMF, and OWASP LLM Top 10. A re-test attestation once it is fixed.

  4. 04The Evidence

    Independent, published, credited.

    We don't build your AI or sell you the model. Three published studies on named frontier models, including the finding that seven of eight disclosed customer data to an unverified caller. Confirmed vulnerabilities reported to Apple and Google through their official programs.

Adversarial test executions published
5,000+
Published studies
3
Credited vulnerability reports
Apple, Google
Frontier models
Tested as they release

In Practice

What an unprotected agent does when asked nicely.

Pick a scenario, then toggle between an unprotected system and the same system after assessment and remediation.

Support assistant

Web chat

Simulated exchanges based on attack patterns from real assessments.

See how the checkpoints and audit trail work →

What We Test

If an agent can touch real data or real systems, it can be attacked. Which one is yours?

Support and sales assistants that can see account data and act on it.

See what we test for it →

Why NXT

Offensive security roots

Most AI security firms come from ML research or enterprise sales. We come from breaking systems at the largest companies in the world, with credited findings to show for it. And when we research, we publish the way we break: named models, measured results, methodology in full.

Independent by design

We don't build your AI or sell you the model. The people who build a system shouldn't be the only ones grading it.

Deterministic evidence

No AI evaluating AI. The same input produces the same verdict every time, so every finding is reproducible and defensible.

Research

October 2026

Absent Deliberation

How LLMs Resolve Competing Objectives Without Reasoning About Them

LLM customer service agents confirm stored PII when asked to verify it, while refusing direct requests for the same data. We trace the mechanism through more than 1,500 API calls across six Claude models with full thinking-trace capture. The model almost never asks itself whether confirmation is disclosure, and when it does, it reasons past the question. Made to take a position on the scenario beforehand, it refused in every trial. More reasoning effort did not reliably help, and in one model made disclosure more explicit.

Read the report →

View all publications →

Trusted By

  • Comex Logistics LLC
    Freight forwarding, Los Angeles
  • Immaculate Shipping Line Inc.
    Shipping, Panama

Get Started

Deploying AI? Find out where it breaks before someone else does.

A short call to understand what you're running and what an assessment would cover. No sales pitch.

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