AI Security & Red Teaming for Government

Government AI carries obligations most private systems do not: data sovereignty, public-records and transparency rules, procurement scrutiny, and the duty to protect citizen data and classified material. A citizen-services assistant ingests untrusted public input by design, which makes prompt injection and abuse an everyday threat, while any system near cleared or sovereign data raises exfiltration stakes to a national level. Public trust is the asset, and one leak or manipulated answer erodes it. We adversarially test your AI for injection, leakage, and abuse, harden it within your sovereignty and clearance boundaries, and produce the documented evidence that procurement and oversight demand.

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How we deliver it

AI Security & Red Teaming, built for government

We threat-model around sovereignty and sensitivity: where data must stay, which systems touch classified or citizen data, and how untrusted public input reaches the model.

We run injection and abuse tests against citizen-facing assistants, proving whether public input can manipulate responses, exfiltrate data, or drive denial-of-service-style abuse.

We test data-boundary controls so information cannot cross sovereignty lines or clearance levels through the AI or its retrieval layer.

We harden with guardrails, strict access controls, and audit logging that supports transparency, public-records, and procurement requirements.

Where it pays off in government

Citizen-input injection

We test whether a member of the public can manipulate a citizen-services assistant through crafted input to leak data or produce off-policy answers.

Sovereignty boundary testing

We probe whether data can cross jurisdictional or sovereignty boundaries through the model, its logs, or its integrations.

Clearance and access abuse

We attempt to pull information above a user's clearance or authorization and harden the system so the boundary holds.

Transparency-safe logging

We add audit logging that satisfies public-records and oversight needs without itself becoming a leakage vector.

Government clients close public-input injection and data-boundary paths before launch and produce procurement-ready evidence, protecting both citizen data and public trust.

Government AI, answered

We map where your data is required to reside and design the engagement to honor those boundaries, including where testing infrastructure runs. We then specifically probe whether the AI or its integrations can move data across a sovereignty line, and harden against it.

We treat the public input channel as hostile by default. We run adversarial and abuse tests as if real users were attacking the assistant, covering injection, data extraction, and manipulation, then add guardrails and monitoring tuned to public-facing risk.

Yes. Every threat, test, and fix is documented, and the audit logging we add supports public-records and transparency obligations. The result is an evidence package that holds up under procurement review and oversight.