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Talk to TheosYour AI systems are part of your attack surface. Theos tests them before adversaries do.
THE CHALLENGE
The security gap in enterprise AI deployment.
Organisations are deploying AI across development pipelines, SaaS platforms, customer-facing systems, and operational workflows. Most are applying traditional security thinking to a fundamentally different attack surface.
Adversaries are already targeting AI infrastructure. In 2025, exploitation of AI platform vulnerabilities increased sharply, including direct attacks on AI development tools, malicious MCP servers impersonating legitimate integrations, and prompt injection attacks designed to manipulate AI-connected workflows. AI systems that connect to sensitive data or business processes are high-value targets.
The attack surface includes the model itself, training data, the API layer, connected integrations, and the access controls governing who can interact with AI systems and what they can instruct them to do. Most penetration testing programmes were built before these components existed.
HOW THEOS ADDRESSES IT
What Theos delivers.
AI Penetration Testing
Structured testing of AI systems and infrastructure against the attack patterns adversaries are already using, including prompt injection, model abuse, API exploitation, and unauthorised data access through AI-connected workflows. Findings are documented with clear remediation guidance and prioritised by risk.
Red Teaming Against AI Systems
Adversary simulation that treats your AI infrastructure as a target, testing whether an attacker who gains access to your AI tools can use them to move laterally, exfiltrate data, or manipulate business processes. Results feed directly into how your AI security programme is hardened.
EXPLORE
Related Challenges
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