AI security
Four ways AI changes your risk
Attackers use AI against you, and the AI you deploy can itself be attacked. Both need attention.
AI-powered attacks
Deepfakes, AI-generated phishing and automated exploitation make attacks harder to spot.
Weaknesses in AI systems
Prompt injection, data poisoning, model theft and adversarial inputs target the AI systems you build and deploy.
Governance and compliance gaps
The EU AI Act, NIST AI RMF and newer regulations add compliance requirements to AI adoption.
Shadow AI
Staff using unapproved AI tools can paste sensitive data into systems nobody is managing.
Attacks, systems and adoption
We look at AI from three sides: the AI-powered attacks aimed at your organization, the AI systems you build, and the AI tools your staff already use.
Our team combines security testing experience with hands-on AI/ML work, so we can cover both the offensive and defensive sides of AI security.
Offensive and defensive
We red-team AI systems and we help defend against AI-driven attacks.
Technical testing and governance
Prompt injection tests and AI policy work sit in the same practice.
Vendor-agnostic
Our advice doesn't depend on which AI platform you use or plan to buy.
Practical recommendations
Recommendations sized to your business and the tools it actually uses.
Six AI security services
Pick the one closest to what you're working on.
AI security assessments
A review of your AI and ML systems: model security, data pipelines and inference endpoints.
AI governance and risk
AI policies, frameworks and compliance programs aligned with the EU AI Act, NIST AI RMF and responsible AI principles.
LLM and GenAI security
Prompt injection testing, jailbreak resistance checks and AI red teaming for large language models.
AI-powered threat defense
AI applied to threat detection, behavioral analytics, automated threat hunting and deepfake detection.
Secure AI implementation
Security architecture for rolling out Copilot, ChatGPT Enterprise and custom LLMs.
AI incident response
Response to AI-specific incidents such as model compromise, data poisoning and deepfake attacks.
Rolling out AI? Talk to us first.
Tell us which AI tools you use or are building. We'll show you where the risks are and what to look at first.