AI SECURITY PRACTICE

Secure every layer of your AI stack — prompt to agent to server.

Every new AI capability your team adopts opens a new attack surface: prompts that can be hijacked, agents that can be tricked into overstepping their remit, MCP servers with more access than anyone reviewed, and tools quietly adopted without IT ever knowing they exist. We find, harden, and monitor all five.

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WHAT WE SECURE

Five places AI risk actually lives.

Traditional application security tooling doesn't see any of these by default. Each one needs its own review, its own controls, and its own owner.

01 AI Prompt Security

Defends against prompt injection and jailbreak attempts that try to override a system's intended instructions.

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04 Shadow AI

Discovers AI tools already in use across your business that were never formally reviewed or approved.

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02 AI Agent Security

Bounds what autonomous agents are allowed to do, so a compromised agent can't take an unauthorized action.

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05 GenAI Data Leak

Defends against prompt injection and jailbreak attempts that try to override a system's intended instructions.

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03 MCP Security

Vets and scopes Model Context Protocol servers and tools before they get standing access to your systems and data.

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Pairs with AI Governance

Security findings feed directly into your AI Readiness Audit and Policy Guard documentation and Governance Report

WHY THIS IS A DISTINCT DISCIPLINE

AI risk doesn't look like traditional application risk.

A firewall doesn't see a prompt injection hidden inside a PDF. A code review doesn't catch an agent that was given more standing access than the task required. An endpoint DLP tool doesn't flag an employee pasting a customer list into a free AI chatbot. Each of these needs a control built specifically for how generative AI and agentic systems actually work.

Our practice is grounded in the OWASP LLM Top 10, extended with the operational patterns we see across BFSI, manufacturing, and services clients running AI in production.