Plan for and secure your company’s AI technology.
Prepare, Configure, and Monitor Deployments.
We assess your readiness for a Copilot deployment or help to secure your existing deployment through a Copilot configuration health check to identify gaps in controls that could lead to unintended or over-permissive access to sensitive systems and data. We help determine if security monitoring is in place and functional.
Measure and Benchmark AI Security Defense Capabilities
The Artificial Intelligence Threat Simulation Index (the “AI Index”) is a Purple Team test plan for measuring threat resilience against attacks related to generative AI systems, using VECTR™ to log attack techniques, track results, and report on overall performance and improvement.
The AI Index focuses on the emerging threats in the AI space including targeted use cases for Microsoft Copilot, internally developed LLMs and protecting against unauthorized sensitive data exposure to external LLMs.
Pen Test your AI Environment
We test your AI environment to determine if the appropriate access controls exist to isolate and protect access to AI training data (data poisoning) and AI models (model manipulation). We use our extensive prompt library to test if an attacker can leverage deployed LLMs to gain access to sensitive data (PII, ePHI, IP). We focus on the broader AI environment to determine insecure applications, cloud services, network and remote access services, and other configurations could allow unauthorized access to AI systems and data
Why SRA?
- SRA is a thought leader in AI-related cybersecurity and we advise our clients on their AI security strategy and roadmaps.
- SRA is an official Microsoft Solutions Partner with proven experience securing emerging technologies.
- We are known for our deep technical acumen and research, and we use a structured but flexible approach to help you address your unique AI risks.
Related Blogs
The AI Attribution Problem Nobody in Security Is Talking About, and How to Solve It
AI agents like Claude Cowork and Copilot are acting on behalf of users directly from corporate endpoints, creating a critical attribution gap for SOC teams. This post explores how to use existing EDR telemetry in Microsoft Defender to build a probabilistic model that distinguishes human activity from AI-driven actions, using KQL queries you can deploy in your tenant today.
The AI Attribution Problem, Now With Queries: KQL for Defender Advanced Hunting
Six KQL queries for Microsoft Defender Advanced Hunting that implement a weighted, multi-tier attribution model for AI-driven activity. Covers seed detection, process lineage, file and network scoring, and a unified SOC timeline view, with production tuning guidance and known limitations.
Prepping for AI Velocity: Do the Common Things Uncommonly Well
AI-accelerated exploitation is changing attack speed, not attack fundamentals. This post breaks down how tools like Mythos shift attacker workflows across reconnaissance, exploit development, and supply chain targeting, and why egress filtering, segmentation, credential management, and patch velocity are now load-bearing security controls.