AI product team
A product and platform team building generative-AI applications or agents with access to internal data and tools, supported by security, cloud, data, and governance partners.
A reference overlay for an AI product: strong workload identity, AI discovery and governance, adversarial testing, runtime guardrails, data-loss controls, centralized telemetry, and recoverable supporting systems. It complements rather than replaces the organization's baseline security stack.
By Cyber Tool Stack Editorial TeamUpdated
The stack, layer by layer
All 10 defense layers, in order — what this team chose, why, and what they left for later.
- 01
Identity & Access
Microsoft Entra IDMicrosoftFreemiumAI applications and agents need accountable workload identities and conditional access before they receive model, data, or tool permissions; Entra provides that identity boundary in a Microsoft-centered environment.
- 02
Endpoint Protection
Not covered
No endpoint protection selected — malicious activity on laptops and servers may go undetected.
- 03
Network Security
Not covered
No network security selected — visibility and control over network traffic will be limited.
- 04
Email Security
Not covered
No email security selected — phishing and malicious email remain common initial-access paths.
- 05
Cloud Security
Not covered
No cloud security selected — exposed services, weak permissions, and configuration mistakes can go unnoticed.
- 06
Application Security
garakCommunity projectFreeA free, repeatable command-line probe suite gives engineers a practical first regression layer for prompt injection, data leakage, jailbreaks, and other generative-AI failure modes.
NeMo GuardrailsCommunity projectFreeProgrammable input, retrieval, execution, and output rails let the application enforce its own policy around model interactions and agent tool use instead of trusting model behavior alone.
- 07
Data Protection
Microsoft Purview Data Loss PreventionMicrosoft$$AI-specific controls still need an enterprise data policy behind them; Purview gives the team shared sensitive-data definitions and loss-prevention controls across the Microsoft information estate.
- 08
Detection & Response
Microsoft SentinelMicrosoft$$AI runtime and application events need to join identity, cloud, endpoint, and data telemetry in the existing incident workflow so the team can investigate abuse as part of the wider environment.
- 09
Resilience & Recovery
Veeam Data PlatformVeeam Software$$$Models are only one dependency: the application, retrieval stores, configuration, and supporting workloads still need immutable backups and tested recovery from destructive incidents.
- 10
Compliance & Awareness
HiddenLayer AI Security PlatformHiddenLayer$$$Discovery, ownership, posture, and model lineage create the inventory an AI product team needs before it can apply policy or prove that security reviews cover the systems actually in production.