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Open models for security research, in the EU

A guarded model refuses the analysis of malware, phishing and exploit text. Name the open model your security team needs, and we run it on capacity of your own.

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When the model refuses, the analysis stops

A malware sample. A phishing corpus. An exploit write-up from a disclosure you are triaging. A guarded model reads the words and declines, and your analyst goes back to doing it by hand.

That refusal is correct for a consumer chat product and wrong for a security team. Munito AI runs open models on capacity you reserve, so you can name the model the work needs.

Name the model, and we run it

The public catalog carries no model with its refusal behaviour removed, and this page does not pretend otherwise. What we offer is the route to one.

A dedicated endpoint is reserved GPU capacity running one open model, for your organization only, in the region you pick, set up on request and under contract. The model can be one the public catalog does not list, including a variant tuned or modified for security work.

What you bringWhat we do
The open model you needPlace it, provision it, and serve it on reserved GPUs
Your request rate and latency targetSize the capacity for it
Your regionRun it in the EU, the US, your own cloud, or on-premises
Your use caseAgree it in the contract before anything is provisioned

You call it with the same API and the same key as the shared models, through the OpenAI or the Anthropic interface.

The workloads this unblocks

  • Malware and script triage. Summarize what a sample does, in plain language, for an analyst who then decides.
  • Phishing corpora. Classify, cluster and describe campaigns from real messages, not sanitised ones.
  • Disclosure triage. Read an advisory or a proof of concept and extract the affected versions, the conditions and the mitigation.
  • Detection engineering. Draft and explain rules against real artefacts.
  • Red-team support. Reason over your own engagement scope, for engagements you are authorised to run.

The analyst stays in the loop on every one of them. The model reads and drafts; a person decides and signs.

Detonate it on a machine that is not yours

Reading a sample is one risk. Running it is another. A sandbox is an isolated cloud computer started in about a second and thrown away afterwards, and its network policy is yours to set, which for a sample means no egress at all.

One sandbox per artefact, no shared state, billed per second from $0.0073 an hour.

Samples are the data you least want kept

Customer artefacts, victim data, and sometimes the contents of a breach. Zero data retention is the default here: we keep no prompts and no outputs, we train on nothing you send, and we run no human review and no content moderation over what you send.

Pin the region with the api.eu host and read munito-region off the response. The DPA applies with no signature, at legal.munito.ai/dpa, and the sub-processor list names every company by region.

For work that may not leave your perimeter, the platform runs inside your own cloud account or on-premises. See Enterprise.

How we decide

A dedicated endpoint for this work is agreed in a contract, not clicked. Tell us the organization, the work and the model, and we scope it with you. We serve authorised defensive and research work: threat analysis, detection, triage and red-teaming you are engaged to perform. We do not serve a request to build or operate an attack.

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