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AI for Cloud Posture Management

5 min read
Cloud ArchCloud Eng

Cloud Arch

AI surfaces risks. You own the risk register and remediation priorities.

Cloud Eng

Use AI to triage findings. You fix — and document why some stay as exceptions.

AI for Cloud Posture Management

TL;DR

  • AI can scan for misconfigs, public buckets, overprivileged IAM, compliance drift.
  • AI generates a lot of findings. Many are noise or false positives. You triage.
  • Use AI for continuous scanning. You own the response and the exception process.

Cloud security tools have been scanning for years. AI adds: natural language queries ("show me all resources with public access"), pattern-based anomaly detection, and prioritized remediation suggestions. The volume of findings goes up. The question is what to do with them.

What AI Security Tools Surface

Configuration drift:

  • S3 bucket was private; someone made it public. AI flags it.
  • IAM role gained new permissions. AI compares to baseline.

Compliance mapping:

  • "We need to be PCI compliant. What's missing?" — AI maps controls to resources. You verify.

Threat modeling:

  • "If this VM is compromised, what can the attacker reach?" — AI can graph blast radius. You decide if that's acceptable.

Prioritization:

  • 200 findings. AI ranks by severity and exploitability. You still decide what to fix this sprint.

The Noise Problem

AI and scanning tools over-report. Examples:

  • "Security group allows 0.0.0.0/0" — Maybe it's a legacy dev box. Maybe it's prod. AI can't tell.
  • "Resource has no tags" — Policy violation or intentional? Context matters.
  • Duplicate findings — Same issue, 10 resources. AI might list 10 times. You fix once.

Triage is human work. AI can help sort; it can't decide "we're accepting this risk for now."

The Exception Workflow

Every org has exceptions. "This bucket is public because X." Document it. AI will keep flagging it. You need:

  • Exception register (what, why, owner, review date)
  • Regular exception review (still valid? still needed?)
  • Escalation path (exception expired, no owner — auto-ticket?)

AI doesn't maintain that. You do.

Manual process. Repetitive tasks. Limited scale.

Click "With AI" to see the difference →

Quick Check

What remains human when AI automates more of this role?

Do This Next

  1. Run a posture scan (native or AI-assisted). Get the top 20 findings. Manually triage: true positive, false positive, accepted risk. Document the categories.
  2. Define your exception process — Who can approve? How long do exceptions last? Where are they logged?
  3. Set a cadence — Weekly scan? Monthly review? AI runs the scan. You run the review. Don't let findings pile up unaddressed.