AI Security
Hardening models, prompts, and toolchains.
AI Security is the discipline of protecting models and the systems that wrap them — from training-data poisoning and adversarial examples to prompt injection and tool abuse. It is a core technology layer shared by Cyber Intelligence and every production AI product we ship.
Adversarial Training
Robustness methods for perception and language.
Prompt Defenses
Injection detection and grounded response policies.
Supply Chain
Model and dataset provenance controls.
Red Teaming
Continuous evaluation against evolving attacks.
Threat models for the autonomy era
We catalog threats across training, serving, and agent tools. Each product maps features to mitigations: content filters, capability scoping, output validation, and human gates for irreversible actions.
Research into product
Findings from our adversarial robustness publications become evaluation suites and training recipes. Security is not a PDF checklist — it is runnable tests in CI.
Shared with Security Lab
The Security Lab owns deep research; AI Security technology productizes the patterns that survive contact with real enterprise deployments.