AI is creating an attack surface of its own.
Employees adopt assistants, copilots and coding tools directly. Development teams build AI into internal and customer-facing applications. Agents can access data, invoke tools and take actions across enterprise systems.
These environments introduce security questions traditional controls were not designed to answer alone: what data can an AI system access? What can an agent do? Can retrieved content manipulate its behaviour? Can sensitive information leave through model outputs? Can security teams detect when an AI system starts behaving differently?
Securing AI means extending existing governance and security capabilities to this new attack surface – without creating another isolated security stack.
Security for every way AI enters the organization.
Govern & assure AI
Inventory AI use cases and ownership, classify risk and applicable obligations, define approval criteria and build the evidence needed for governance and assurance.
Use AI securely
Gain visibility into workforce AI use, protect sensitive information, apply policies according to user, team and data context, and maintain visibility over AI interactions.
Build & run AI securely
Threat-model AI applications and agents before production, test them adversarially and control retrieval, permissions, agent actions and tool calls as they operate.
Detect & validate continuously
Monitor AI-specific threats and behaviour, investigate relevant telemetry and continuously validate whether controls remain effective as models, prompts, data and connected tools change.
Security across the AI lifecycle.
Govern
Use
Build
Run
Detect
Validate
AI security cannot stop at policy or pre-production testing. Models change. Prompts change. Retrieval sources change. New tools and permissions are connected to agents.
HWG Sababa links governance and protection with continuous detection and adversarial validation – from understanding how AI is used to securing applications and agents in production.
Through HyperSOC®, relevant AI telemetry can become part of continuous monitoring, investigation and response. Our offensive security specialists complement these operations by testing AI applications and agents against scenarios including prompt injection, malicious retrieved content, model extraction, guardrail bypass and agent abuse chains.
Testing extends beyond the model itself to examine data, identities, retrieval, permissions and connected tools – helping turn exploitable findings into stronger controls and detections as AI systems evolve.
Make AI innovation safer to scale.
Gain visibility and control
Understand how AI is being used, who owns it, what data it can access and which policies apply.
Protect sensitive data
Reduce the risk of sensitive information, secrets and credentials being exposed through AI interactions.
Secure applications and agents
Address AI-specific attack paths before production and control permissions, retrieval and actions as systems operate.
Strengthen AI assurance
Align governance and controls with relevant frameworks and build evidence for regulatory and customer requirements.
Detect and adapt
Monitor AI-specific threats and continuously validate controls as models, prompts, data and connected tools evolve.
Aligned with established AI security and governance frameworks
EU AI Act · ISO/IEC 42001 · NIST AI RMF · OWASP LLM Top 10 · MITRE ATLAS
Explore AI Security in practice.
AI SOC Agents
Explore how AI agents are changing security operations and the role of human expertise, AI and automation in investigation and response.
HyperSOC™: SOC Hyperautomation at Machine Speed
Why manual response can no longer keep pace, and how hyperautomation brings the SOC up to the speed of today’s threats.