Security Plan - Project Name

Important to note: ISE cannot certify/attest to the security of an architecture nor code. This document is intended to help produce backlog items specific to the customer engagement and to document the relevant security design decisions made by the team during build. Please direct your customer to work with their account team or preferred security vendor to seek an audit or pen-test from a security vendor if required/desired.

Overview

Please find the Security Plan for the Project Name below. This document shows the architecture and data flow diagram of the application.These artifacts were constructed based on documentation and source code from the project itself and are subject to change as the architecture and codebase evolves. Each of the labeled entities in the figures below are accompanied by meta-information which describes the threats, describes the data in scope, and recommendations for security controls.

Diagrams

Architecture Diagram

<insert image here>

Data Flow Diagram

<insert image here>

For help getting started, please see our Security Plan Guidelines and Microsoft Threat Modeling Security Fundamentals.

Data Flow Attributes

#	Transport Protocol	Data Classification	Authentication	Authorization	Notes
1	[Name of the protocol for the service]	[Data classification guidance can be found in the Appendix]	[Method of authenticating the caller]	[Method of authorizing the caller]	[Additional Notes]
...	...	...	...	...	...

Threats and Mitigations

<insert notable threats and mitigations here however you like>

For inspiration, see our Example Threats and Mitigations.

Secrets Inventory

An ideal architecture would contain zero secrets. Credential-less options like managed identities should be used wherever possible. Where secrets are required, it's important to track them for operational purposes. Please see our Example Secrets Inventory to help you get started.

Name	What is its purpose?	Where does it live?	How was it generated?	What's the rotation strategy? Does it cause downtime?	How does the secret get distributed to consumers?	What's the secret's lifespan?
...	...	...	...	...	...	...

AI and automation capabilities described in this scenario should be implemented following responsible AI principles, including fairness, reliability, safety, privacy, inclusiveness, transparency, and accountability. Organizations should ensure appropriate governance, monitoring, and human oversight are in place for all AI-powered solutions.