The challenge behind the engagement.
This service is for security teams adding an AI assistant or agents to alert triage and response without opening a new attack surface, whether a vendor product or a model you host yourself. We tier each use case: summarizing and drafting queries as read-only, enrichment and triage verdicts as read-only with analyst review, and response actions as write. We design identity so an assistant never exceeds the analyst who invokes it, so least-privilege roles come first, and agents get their own scoped identities. We write the approval matrix for containment and configuration changes, allowlist the actions a playbook may take, and treat a poisoned alert field as a real attack path. You receive hardened playbooks, detections for agent misuse, and a staging validation report.
For security operations managers, detection engineers, and CISOs who have licensed an AI assistant, or who are wiring a model into their automation platform. Engage before the first playbook takes a write action on your tenant, or when a government or sovereign cloud tenant asks whether the product is even in scope.
What we do.
What you can use.
Register use cases and the role model
We start with your monitoring and automation platforms and licenses, the analyst role model, the playbook inventory, the data source list, a staging workspace or tenant, and owner-level access to data-sharing settings. Each proposed use case goes into a register with its tier, the data it can read, and the actions it may take, before any agent is enabled.
Design identity, gates, and logging
We set least-privilege analyst roles so an assistant acting for a user cannot widen access. Agents get their own scoped identities and a tool allowlist. The safe-automation standard requires human approval on containment and configuration changes, bars unreviewed agent edits to detection rules or access policies, adds a kill switch and rollback, and logs every prompt, tool call, and action to your monitoring.
Harden playbooks and prove them in staging
We harden two or three playbooks with human gates, write detections for agent misuse and for injection through alert fields, and validate any model-drafted detection query in staging before production. You receive the use-case register, the identity and permission design, a per-product data-handling record with evidence, the safe-automation standard, and an agent-goes-wrong tabletop built into your incident-response plan.
Who it’s for.
When you need it.
- Security operations teams adding an AI assistant to alert triage and response
- Detection engineers wiring a model or agent into their monitoring and automation platform
- CISOs who must show AI in the SOC did not widen access
- MSSPs or multi-tenant SOCs weighing AI assistants across customer environments
- A playbook is about to take its first automated write or containment action
- An AI assistant was licensed and analysts are already using it daily
- A government or sovereign cloud tenant needs its product eligibility confirmed
- An agent produced a wrong verdict or action that went unreviewed
What the scope can include.
- 01
Use-case register tiered as read-only, read-only with analyst review, or write, with controls per tier
- 02
Analyst role and agent identity design: least-privilege roles in your identity system, scoped agent identities, and a tool allowlist
- 03
Data-handling settings per product: data sharing, prompt evaluation location, training terms, and government cloud fit, confirmed against current documentation
- 04
Safe-automation standard: approval matrix for containment and configuration changes, allowlisted playbook actions, kill switch, rollback
- 05
Prompt injection through attacker-controlled alert fields such as log lines and email bodies, with detections for anomalous agent behavior
- 06
Logging of every agent prompt, tool call, verdict, and action into your monitoring, with false-verdict metrics and staging validation of drafted queries
What it typically costs.
One rate: $150/hour.
Every engagement is priced by the hours it takes at one flat rate, with scoping, the work, and the final deliverables included. Find the size closest to yours.
One AI assistant used by analysts for read-only help, with one or two automated responses
About 32–56 hoursAn AI assistant plus agents that can take response actions, with two or three hardened playbooks
About 72–110 hoursSeveral AI tools and agents across your security platforms, or across multiple customer environments
About 140–200 hours- Number of AI tools, agents, and automated playbooks
- Whether any automation can take containment or configuration actions
- How much analyst role cleanup is needed before AI is enabled
- Multiple customer environments or government cloud tenants
Ranges are planning estimates at $150/hour, not a quote. Your price is confirmed in writing after a scoping call, before any work begins.
What you take forward.
- Use-case register with tier, permitted data, permitted actions, and controls for each AI workflow
- Identity and permission design covering analyst roles, agent identities, and the tool allowlist, plus a data-handling record per product with evidence
- Safe-automation standard and two or three hardened playbooks with human gates, plus detections for agent misuse
- Staging validation report and tabletop findings for an agent-goes-wrong scenario
Final coverage, deliverables, timing, and any retesting or implementation work are confirmed before the engagement begins.
Before we get started.
Can an analyst use the assistant to see data they are not otherwise allowed to see?
Not by design, but the design depends on your roles. An assistant that authenticates on behalf of the user returns only what that user's permissions allow; its own product roles, such as owner or contributor, are not directory roles, so they do not widen data access. The exposure comes from analysts who already hold broad roles: an assistant makes over-permissioned access fast and conversational. We fix the role model first, then test in staging by asking the assistant, as each role, for data outside that role's scope and recording the result in the validation report.
Will this work in a government or sovereign cloud tenant?
Check before you license. Availability varies by product and by region, and government or sovereign cloud tenants are often out of scope. Some widely used assistants state plainly that they are not designed for government or defense cloud environments, so a contractor with such a tenant cannot assume the product is in scope. For commercial tenants, where prompts are evaluated and whether data is shared are usually configurable, and both are recorded in the data-handling record with evidence. For any assistant or custom integration we confirm these points against the provider's current documentation during scoping, and we never describe a product as available where its own documentation says it is not.
- Secure Software Development Practices for Generative AI and Dual-Use Foundation Models: An SSDF Community Profile (NIST SP 800-218A)
- AI Risk Management Framework
- Joint Guidance on Deploying AI Systems Securely
- AI Data Security: Best Practices for Securing Data Used to Train & Operate AI Systems
- OWASP Top 10 for Agentic Applications for 2026
- Model Context Protocol Specification: Authorization
- Protecting Controlled Unclassified Information in Nonfederal Systems and Organizations (NIST SP 800-171 Rev. 3)