CIS Benchmark Automation with AI Agents
Continuous CIS benchmark compliance across AWS, Azure, and GCP, with auto-remediation for low-risk controls and audit-ready evidence.
AWS
Azure
GCP
OPAThe problem today
Your annual CIS benchmark assessment takes a security engineer three weeks, produces a 400-row spreadsheet, and is out of date the day it's delivered. Drift between audits is invisible. A single `aws s3api put-bucket-acl` undoes a passing control without anyone noticing. The 'compliant' cloud environment you certified in January is already out of compliance by February.
How AI agents solve it
The Security Agent continuously evaluates every cloud account against the CIS benchmark controls for AWS, Azure, and GCP. Each control is checked in real time, not annually. For low-risk failures (encryption flags, logging enablement, default tags), the agent drafts a Terraform PR to bring the resource back into compliance. For higher-risk failures, it generates an audit-ready evidence report. Everything is timestamped and signed for auditor review.
Who this is for: Security and GRC teams running CIS benchmarks across multi-cloud environments
Manual workflow vs. Security Agent
Manual workflow
- Annual CIS assessment by a dedicated security engineer
- 400-row spreadsheet compiled from console screenshots
- Evidence out of date the day it's delivered
- Drift between audits is completely invisible
- Remediation is manual and tracked in Jira
With the Security Agent
- Every CIS control evaluated continuously, not annually
- Audit evidence generated on demand with full history
- Low-risk drift auto-remediated via Terraform PRs
- Regressions caught the moment they happen
- Auditors see a live dashboard, not a stale spreadsheet
How the Security Agent runs this
- 01
Security Agent subscribes to cloud provider change events across all accounts
- 02
On every change, evaluate affected resources against CIS benchmark controls
- 03
For low-risk failures, generate a Terraform fix PR via the Terraform Agent
- 04
For high-risk failures, create an evidence report with timestamps and context
- 05
Track control status over time (pass, fail, remediated, exception)
- 06
Generate auditor-ready reports on demand with full historical data
- 07
Alert on any regression in previously-passing controls
Measurable impact
Turns a 3-week annual audit into a continuous, always-current process
Catches compliance regressions within minutes of the change
Reduces auditor back-and-forth by producing evidence on demand
Low-risk auto-remediation handles ~60% of findings without engineer time
Agents involved
Governed by the AI Gateway
Every agent action in this use case is audited, policy-checked, and cost-tracked
Structura's AI Gateway sits between every agent and the underlying LLM providers. Every decision made during this use case. Every plan review, every policy check, every fix PR, is routed through guardrails, logged to an immutable audit trail, and evaluated against NIST AI RMF and AIUC-1 controls.
Learn about the AI GatewayRelated use cases
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See this use case in a live demo
We'll walk you through exactly how the Security Agent handles this in a real environment with your stack, your policies, and your constraints.