AI security and governance
Know where AI touches your data, then put controls around it
AI security and governance is the work of deciding which AI tools your organization may use, what data they may see, and how you detect misuse. Storcom inventories AI use across your endpoints and cloud accounts, helps you write policy against the NIST AI Risk Management Framework, and extends the security controls you already run to cover it.
Last updated
Practice: AI security and governance
- Built for
- For IT and security leads whose staff adopted AI tools before a policy existed.
- What you get
- Inventory of AI tools already in use
- Policy mapped to the NIST AI RMF
- Built on controls you already own
- Starts with a discovery call
- Delivered from
- Geneva, Illinois, for Chicagoland and customers across the U.S.
Watch policy catch a risky prompt
An unapproved AI tool appears, sensitive data shows up in a prompt, and policy blocks, redacts and logs it.
Approved AI tools in use. Policy enforced.
- 1Unapproved AI tool found in use
- 2Sensitive data spotted in a prompt
- 3Policy blocks the tool and redacts the data
- 4The event is logged against your AI policy
Illustration only. The controls shown are CrowdStrike Falcon Guardian capabilities, deployed by Storcom.
What is AI security and governance?
Governance is the set of decisions: which AI tools are approved, who may use them, what data is allowed in a prompt, who reviews a new use case, and who is accountable when something goes wrong. Security is the set of controls that make those decisions stick, such as identity, endpoint, network and cloud posture controls, logging and response.
Most organizations already have people pasting documents into public chatbots, AI features switched on inside software they license, and a few teams experimenting with models in a cloud account. None of that waited for a policy. The first job is to see it.
What Storcom does
AI use inventory
We use your endpoint, firewall and cloud telemetry to list the AI tools and services in use, who uses them, and which ones were never approved.
Acceptable-use policy
A written policy your staff can follow: approved tools, data that must never enter a prompt, and how a new tool gets reviewed.
Framework mapping
Your policy and controls mapped to the four functions of the NIST AI Risk Management Framework: Govern, Map, Measure and Manage.
Controls on what you own
Identity, endpoint, firewall and cloud posture controls tuned to block unapproved tools and log use of approved ones.
Protection for AI workloads
If you run models in Azure, AWS or your own data center, we review the accounts, keys, storage and network paths around them.
Incident response for AI
Your incident response plan extended with AI scenarios, such as sensitive data pasted into a public tool, then tested in a tabletop exercise.
Which AI risks matter most?
These are the ones that come up most often, and the control that addresses each.
| Risk | What it looks like | Control |
|---|---|---|
| Shadow AI | Staff use tools nobody reviewed, on personal accounts | Inventory from endpoint and network telemetry, then an approved-tools list |
| Data leaving in prompts | Customer, patient or financial data pasted into a public chatbot | Acceptable-use policy, data classification, and blocking or monitoring at the endpoint and firewall |
| Over-permissioned assistants | An AI assistant surfaces files a user should never have been able to open | Access review of file shares and Microsoft 365 before the assistant is switched on |
| Prompt injection | Content an AI system reads carries instructions that change what it does | Limit what the system can reach and act on, and log its actions |
| Exposed AI infrastructure | Model endpoints, keys or training data left open in a cloud account | Cloud posture review and CrowdStrike Falcon exposure management for internet-facing systems |
| No owner | Nobody is accountable for approving or reviewing AI use | A named owner and a short review process in the policy |
Prompt injection is listed first in the OWASP Top 10 for Large Language Model Applications.
How does an engagement run?
Discover
After a discovery call, we inventory AI use and review the controls you have.
Decide
We work with your leadership on the approved-tools list, data rules and who owns review.
Enforce
We tune identity, endpoint, firewall and cloud controls to match the policy and turn on logging.
Review
A scheduled review of new tools, new use cases and anything the logs turned up.
What this service is not
Storcom does not build AI models, audit model accuracy or bias, or certify you against a standard. If you need a formal certification such as ISO/IEC 42001, we help you prepare the security and infrastructure evidence and work alongside your auditor.
Technology we deploy for this
CrowdStrike Falcon for endpoint detection and response and vulnerability management, resold, deployed and tuned by Storcom, including Falcon Flex bundles.
Cisco switching, routing, wireless and firewalls for data center and campus networks, designed, implemented and managed by Storcom.
Tenable vulnerability management for scanning servers, networks and internet-facing assets as part of a continuous risk program.
Microsoft Azure infrastructure and Microsoft 365, with Storcom managing Azure resources and backing up Exchange Online, SharePoint, OneDrive and Teams.
Sources
- AI Risk Management Framework (AI RMF 1.0) National Institute of Standards and Technology. Accessed .
- OWASP Top 10 for Large Language Model Applications OWASP Foundation. Accessed .
- ISO/IEC 42001:2023, Artificial intelligence management system International Organization for Standardization. Accessed .
Frequently asked questions
What is the NIST AI Risk Management Framework?
The NIST AI Risk Management Framework (AI RMF 1.0) is voluntary guidance published by the U.S. National Institute of Standards and Technology in January 2023. It organizes AI risk work into four functions: Govern, Map, Measure and Manage. Storcom uses it as the structure for AI policy and controls.
What is shadow AI?
Shadow AI is the use of AI tools that IT has not reviewed or approved, often on personal accounts. It matters because company data can leave in prompts and uploads with no record. Storcom finds it using the endpoint, firewall and cloud telemetry you already collect.
Do we need new security tools to govern AI?
Often not at first. Identity, endpoint protection, firewalls and cloud posture tools can enforce most of an acceptable-use policy once they are tuned for it. Where a gap remains, we recommend a specific tool and explain what it adds.
Should we block AI tools entirely?
Blanket blocking usually pushes use onto personal devices where you can see nothing. Most organizations do better with a short list of approved tools, clear rules on what data may be entered, and monitoring. Storcom helps you set that list and enforce it.
Does Storcom certify us against an AI standard?
No. Storcom is not a certification body. We help you write policy, put controls in place and gather the security and infrastructure evidence an auditor will ask for, including for ISO/IEC 42001 preparation.
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Start with a discovery call.
Tell us what you run today, what is changing and what worries you. We listen, ask questions and tell you plainly whether and how we can help. No cost, no commitment.