A new class of AI for cloud security

General AI understands text. OFFENSAI understands cloud attacks.

Its model reasons over a Universal Offensive Ontology, a shared attack language linking identities, permissions, and services into real cross-cloud chains, each validated in live environments

Why can't frontier models and LLM wrappers deliver effective cloud security validation?

Context windows break on cloud-scale graphs

Frontier models reason within a session; real cloud attack paths span millions of relationships and require a persistent graph.

No persistent attack memory

Each prompt starts from zero. Without persistent knowledge, frontier models can't build or evolve multi-step attack chains.

No native understanding of cloud attack logic

General AI understands language, not attack primitives; without a unified ontology, it can't link IAM abuse and APIs into cross-cloud chains.

Your attack surface leaves the perimeter

Using frontier APIs requires sending cloud context externally, exposing IAM topology and trust relationships.

No deterministic proof of exploitability

Frontier models generate answers, not validated outcomes; they can't prove attack paths, leaving assumptions instead of evidence.

A specialized AI foundation for cloud attacks

Connect discovery, proof, execution, and learning into a loop that improves with every validated attack path.

Persistent cloud intelligence

OFFENSAI finds exploitable cloud changes across AWS, Azure, GCP, and Kubernetes, feeding a persistent graph instead of resetting with each prompt.

Persistent cloud intelligence

Formal proof engine

Mathematically proves which attack paths exist in your environment using z3 Datalog, delivering deterministic validation instead of probabilistic answers.

Formal proof engine

Execution layer: Operator-driven or autonomous

ATTACKSTUDIO™ lets operators build and control campaigns, while Agent O runs proven paths end to end, on demand with full reports and no hallucinations.

Execution layer: Operator-driven or autonomous

Compounding attack graph collection

Curates verified patterns into a compounding knowledge graph that sharpens every future discovery cycle, unlike frontier models with no persistent state.

Compounding attack graph collection

OFFENSAI's Universal Offensive Ontology

One attack language. Every cloud.
UOO powers cross-cloud attack chain discovery that no single-platform logic can achieve.

One attack ontology across all clouds

UOO maps thousands of cloud-specific actions into 11 universal attack primitives, allowing the model to reason across AWS, Azure, GCP, and Kubernetes as one system.

Cross-cloud attack chains by design

Techniques connect through shared primitives, not provider logic, enabling attack paths that span multiple clouds and services that traditional tools cannot see.

From noise to chain signal

UOO filters thousands of daily cloud changes into the few that matter, identifying combinations that collapse trust boundaries or enable lateral movement.

OFFENSAI cloud security validation you can trust

Human-initiated by design

Validations are only run on your approval.

Data sovereignty by design

Clouds connect via native APIs. Read-only access, no host agents to deploy.

Audit-ready output

Validated findings are structured for review and reporting.

Actionable remediation

Clear evidence and guidance, not just detection output.

Shift happens.
Be ready when it does.

Move from cloud exposure detection to controlled validation, technical evidence, and risk-based prioritization, powered by AI.

OFFENSAI autonomous attack agent