AI Red Team · Whitepaper

Chapter 16 · Protect

Data and Platform Security with and for AI

Key insights from Chapter 16 of "AI Red Team"

Author Conceived and directed by Gunnar Nordqvist; text written by AI agents
Published 2 November 2026
Build number 2026.11
ai-red-teaming ai-enabled-defence purple-teaming security-operations nist-csf-2
Figure 16.1: Security data passing classification, a gateway and guardrails before reaching security AI, with attacker-controlled input treated as untrusted.
Figure 16.1: Security data passing classification, a gateway and guardrails before reaching security AI, with attacker-controlled input treated as untrusted.

Security AI is only as trustworthy as the data it reads and the platform it runs on. A triage assistant handles user names, command lines and, in a public authority with health and social-care duties, fragments of special-category data; a detection-engineering assistant touches the repository that holds the entire detection logic. Each capability concentrates sensitive data in a new place and reads content that an adversary can write, so protecting security data and its platforms is the condition for using AI in defence at all.

This chapter covers two Categories of the Protect Function of NIST CSF 2.0 (19, NIST, 2024). PR.DS Data Security protects the confidentiality, integrity and availability of data at rest (PR.DS-01), in transit (PR.DS-02) and in use (PR.DS-10), and requires backups that are created, protected, maintained and tested (PR.DS-11). PR.PS Platform Security manages platform hardware, software and services, with outcomes for configuration management (PR.PS-01), maintenance and removal of software and hardware (PR.PS-02 and PR.PS-03), log records made available for continuous monitoring (PR.PS-04), prevention of unauthorised software (PR.PS-05) and secure software development (PR.PS-06). The chapter treats both Categories through the three focus areas of the NIST Cyber AI Profile (20, NIST, 2025).

Security teams are used to protecting the organisation's data; they are less used to protecting their own.

Primary topics explored

  1. Data security for security data
  2. Guardrails and policy points
  3. Secure configuration with AI
  4. Secure development with AI assistance
  5. Data and platform security across modes, levels and focus areas
  6. Summary

About AI Red Team

AI Red Team is Book 4 of The Transformed Architecture. It shows how large European enterprises and public authorities put artificial intelligence to work as an active part of cyber defence: AI-assisted red teaming and adversary emulation, red teaming of AI systems themselves, the AI-assisted security operations centre, detection engineering, threat intelligence, incident response and purple teaming, all under a lawful mandate and with evidence a supervisor can inspect.

It builds on the conclusions of Architecture as Code, AI Governance and AI Platform and Security.

Who should read this

CISOs, SOC leads, red and blue team practitioners, security architects, AI architects and technical decision-makers.

Portrait of Gunnar Nordqvist

Gunnar Nordqvist

Conceived, directed and published the books of The Transformed Architecture.

Continue with the full chapter

Read the full chapter online

Chapter 16: Data and Platform Security with and for AI in AI Red Team gives the detailed explanations, practical examples and implementation patterns behind this summary.

This whitepaper belongs to “Protect” and is one of 32 drawn from the manuscript.