AI Security Consulting
& LLM Red Teaming
Enterprise AI adoption has outpaced security governance. Prompt injection, model jailbreaks, and RAG manipulation now represent a Tier-1 attack surface invisible to most security programs.
Why Boards Can't
Ignore This
AI attack surfaces are expanding rapidly: blind spots are increasing across every enterprise.
Regulations like the EU AI Act and NIST AI RMF introduce direct board-level liability for unvalidated AI deployments.
LLM-driven data exfiltration bypasses traditional DLP controls, remaining invisible to existing systems.
Our Security
Methodology
LLM Red Team Assessment
Using proprietary tools to run adversarial testing mapped to the OWASP Top 10 for LLM Applications (2025).
RAG Security Review
Delimiter injection, embedding poisoning, and retrieval manipulation testing.
Guardrail Design & Deployment
Implementation of Lakera Guard, HiddenLayer, and CalypsoAI across your AI stack.
AI Security Governance
Model inventory, risk classification, and full NIST AI RMF alignment.
AI-Native Threat Detection Playbooks
Integrated directly into your existing SIEM and SOC workflows.
Expected
Outcomes
AI systems move from experimental → governed → continuously monitored.
Hidden vulnerabilities are exposed before exploitation.
Security becomes predictive, not reactive.
If your AI systems aren't tested, they're already exposed.
Start with a controlled assessment.