Challenge Everything. Assume Nothing.
AI systems are rapidly becoming embedded across modern organisations — from copilots and AI agents to automated workflows, retrieval systems, and business-critical decision making.
But while AI adoption is accelerating, security maturity is not keeping pace.
Traditional security controls were designed for deterministic systems. AI introduces a fundamentally different risk model: systems that interpret context, interact dynamically with data, trigger automated actions, and can be manipulated in ways conventional testing was never designed to detect.
At Liora Security, our AI Red Teaming service simulates how real attackers target AI-enabled environments — exposing weaknesses across models, integrations, workflows, and connected systems before they can be exploited.
We do not test AI in isolation.
We test the entire ecosystem.
Our assessments evaluate how AI systems behave under realistic adversarial conditions, including attempts to manipulate outputs, bypass safeguards, abuse integrations, and influence automated processes.
Testing whether attackers can override instructions, manipulate behaviour, or influence AI outputs through adversarial prompts and contextual abuse.
Assessing retrieval systems for sensitive data leakage, excessive context exposure, and knowledge poisoning risks.
Evaluating whether filtering, policy enforcement, and safety controls remain effective under adversarial persistence.
Testing whether AI-driven workflows and automated actions can be manipulated to bypass business controls or trigger unintended outcomes.
Reviewing overprivileged integrations, insecure connectors, token misuse, and AI-enabled access escalation paths.
Assessing connected applications, cloud platforms, and third-party integrations for exploitable weaknesses across the wider AI ecosystem.
AI-related attacks are no longer theoretical.
Modern AI environments can introduce:
As frameworks such as the EU AI Act, ISO 42001, and DORA continue to evolve, organisations are under increasing pressure to demonstrate secure and controlled AI adoption.
Our approach is designed to reflect how attackers operate in real-world environments — not controlled laboratory scenarios or checklist-driven testing.
We assess:
Every engagement delivers evidence-based findings with prioritised remediation guidance designed to improve resilience, governance, and operational control.
AI adoption should accelerate innovation — not introduce unmanaged risk. Liora Security helps organisations identify, validate, and reduce AI-related risk through practical, adversary-led security testing built for modern enterprise AI environments.
Challenge everything. Assume nothing.