GULFPORT, Miss. | August 31, 2026
The Mississippi Artificial Intelligence Network (MAIN) has released the no-cost Cybersecurity AI Playbook, a practical resource for organizations that need to secure AI systems, use AI in defensive work with clear boundaries, and prepare for incidents involving AI.
A practical operating resource
The playbook helps organizations govern and inventory AI systems, secure their components and dependencies, and place limits around AI-assisted defensive workflows. It also addresses preparation for AI-enabled threats, independent validation of AI output, and incident response that preserves evidence and accountable human oversight.
It is voluntary guidance. It is not a compliance standard, threat-intelligence directive, incident-specific runbook, penetration-testing authorization, or substitute for qualified professional advice. The resource does not recommend delegating consequential containment, account, network, endpoint, production, notification, attribution, or evidence decisions to AI by default.
Three connected cybersecurity missions
MAIN organizes the material around three missions that security and organizational leaders can address together:
- Secure AI system components. Protect models, data, prompts, applications, agents, identities, tools, infrastructure, interfaces, monitoring, and software and service dependencies.
- Conduct AI-enabled cyber defense. Use AI to support bounded analysis while preserving source evidence, controlling access, measuring performance, and requiring qualified review.
- Thwart AI-enabled cyberattacks. Prepare for more scalable or persuasive forms of familiar abuse, as well as risks involving AI applications, models, agents, data, and software supply chains.
This organizing model is informed by NIST IR 8596, the Cybersecurity Framework Profile for Artificial Intelligence. NIST continues to identify that publication as an initial preliminary draft, not a final standard.
What readers will find
The playbook is designed for use during planning, procurement, testing, operations, and incident preparation. It includes:
- A cybersecurity AI risk map and minimum AI-system inventory
- AI lifecycle and attack-surface guidance
- Secure development and acquisition checkpoints
- Seven bounded defensive workflows, each paired with validation questions
- An AI-related incident-response sequence that emphasizes evidence preservation
- A 30-day cybersecurity AI pilot
- A pilot scorecard and explicit stop conditions
- Links to authoritative standards, preliminary drafts, and threat-knowledge resources with their status identified
Start with one bounded workflow
The recommended starting point is one lower-risk, read-only workflow using approved and minimized data. Teams should limit privileges, establish a measurable baseline, require analyst verification, and retain logs outside the AI workflow so results can be reconstructed without relying on model memory.
Before a pilot begins, the organization should define revocation, recovery, and stop conditions. At the end, an authorized owner records whether the evidence supports continuing, revising, pausing, or stopping the work. A useful summary or recommendation is not evidence that autonomous containment or production change is safe.
Who can use the playbook
The resource is written for security leaders; security operations and incident-response teams; threat-intelligence and detection-engineering professionals; application, cloud, identity, and data security teams; AI and machine-learning teams; and professionals working in risk, privacy, legal, procurement, and audit. Its shared structure can help those groups define ownership before an AI system reaches production or a defensive pilot expands.
Part of MAIN’s practical resource system
The Cybersecurity AI Playbook joins MAIN’s broader collection of practical AI playbooks, AI policy guides, no-cost AI courses, workforce-development resources, and implementation support. Together, these resources help Mississippi organizations connect governance, skills, and day-to-day operating decisions.
Use the Cybersecurity AI Playbook
Begin with the web playbook, share the PDF with the reviewers who own the workflow, and use MAIN’s full playbook collection to connect cybersecurity work with broader AI implementation planning.
About MAIN: The Mississippi Artificial Intelligence Network is Mississippi’s statewide AI initiative, anchored at Mississippi Gulf Coast Community College. MAIN helps residents, educators, employers, and public institutions build practical AI knowledge and workforce capacity. Learn more about MAIN or contact the network.