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AI agent security

Prove que seus agentes de IA resistem a ataques
com evidência validada por exploração.

Nossa infraestrutura autônoma de validação ofensiva, agora produtizada em fluxos de validação seguros para o cliente. Testamos prompt injection, uso indevido de ferramentas, exfiltração de dados e autonomia insegura em agentes LLM e suas ferramentas — somente leitura por padrão, escopo travado, autorizados por escrito, e cada achado sustentado por prova reproduzível em vez de heurísticas de scanner.

Non-disruptive
Scope-locked
Signed authorization
Read-only by default
What we test

The four ways agents go wrong in production.

Every finding ships with a working transcript: the prompt, the tool trace, the result, and a fix.

Diagram of an AI agent core surrounded by four attack-vector nodes
Prompt injection

Direct and indirect injection through user input, RAG documents, tool outputs and connected data sources.

Tool misuse & unsafe autonomy

Over-broad tool scopes, missing human-in-the-loop approvals, chained calls reaching beyond intended capability.

Data exfiltration

PII, secrets and internal docs leaked through tool calls, function args, error messages or model output channels.

Jailbreaks & policy bypass

System-prompt leakage, role confusion, refusal bypass, multi-turn coercion against the agent's safety policy.

Terminal log showing allowed and off-scope blocked probe entries
Non-disruptive by design

Built so you can run it against the real thing.

The testing pipeline enforces the same guardrails as the rest of the platform — at the database layer, not in a checklist.

Read-only probes

No destructive tool calls. No writes you didn't authorize. No spend. No production data mutated.

Allowlisted targets

Every run is scope-locked to an explicit list of agent endpoints. Off-scope calls hard-stop, no exceptions.

Signed authorization

assert_run_authorized blocks any run without a signed authorization document on file — same control that gates Web2/Web3 engagements.

How it works

Three steps. Working transcripts, not advisories.

Three-pane storyboard: authorization document, operator console, finding transcript
01
Authorize

You send the agent endpoint, tool list and scope. We countersign and lock it to your tenant.

02
Run the suite

Non-disruptive probes execute against staging or a sandboxed replica. Realtime logs in the operator console.

03
Get the transcript

Every finding lands with the exact prompt, the tool trace, the resulting leak or action, and a concrete fix.

Who it's for

Teams accountable for what an agent does next.

Agent product teams

Shipping a customer-facing copilot or autonomous agent and need evidence its tools are safe before launch.

AI platform owners

Operating an internal agent platform where many teams plug in tools — you need a continuous safety baseline.

Enterprise IT enabling copilots

Rolling out internal assistants with access to docs, tickets and code — and accountable for what they touch.

Compliance & risk owners

Producing evidence for EU AI Act, SOC2 or internal AI governance reviews. Findings come with reproducible artifacts.

Compiled proof-of-concept report with an emerald wax seal
Free pilot

Bring your agent. Leave with proof — for free.

Authorize a scope. We run the test on your agent's prompts, tools and integrations. You keep every finding with a compiled PoC. Then decide if you want continuous coverage.

Pare de perseguir falsos positivos.
Comece a entregar provas.

Traga um repo, um commit ou um alvo de staging. Voltaremos com exploits compilados e validados — ou nada.

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