Time To First Finding

Get your first real finding against your own AWS environment in under 10 minutes.

No agents, no credentials stored by Stave, no network calls during evaluation. You extract the data yourself with the AWS CLI, then Stave evaluates it offline.

Prerequisites

• stave installed and on PATH
• AWS CLI configured with read access to the target account
• Optional: jq installed (for extracting observation data)
• If jq is not installed, you can use JMES path that is part of AWS CLI

Step 1: Extract a snapshot from your AWS account

Use the AWS CLI to pull S3 bucket configuration into a local directory. This is your extractor — a few shell commands you control.

mkdir -p snapshot-raw
aws s3api list-buckets > snapshot-raw/list-buckets.json
for bucket in $(jq -r '.Buckets[].Name' snapshot-raw/list-buckets.json); do
  aws s3api get-public-access-block --bucket "$bucket" > "snapshot-raw/${bucket}-pab.json" 2>/dev/null || true
  aws s3api get-bucket-acl --bucket "$bucket" > "snapshot-raw/${bucket}-acl.json" 2>/dev/null || true
  aws s3api get-bucket-policy --bucket "$bucket" > "snapshot-raw/${bucket}-policy.json" 2>/dev/null || true
  aws s3api get-bucket-encryption --bucket "$bucket" > "snapshot-raw/${bucket}-encryption.json" 2>/dev/null || true
  aws s3api get-bucket-logging --bucket "$bucket" > "snapshot-raw/${bucket}-logging.json" 2>/dev/null || true
  aws s3api get-bucket-versioning --bucket "$bucket" > "snapshot-raw/${bucket}-versioning.json" 2>/dev/null || true
done

This runs in your terminal. Stave never sees your credentials.

Step 2: Convert the snapshot into observations

Use an extractor to convert the raw AWS CLI output into Stave's normalized observation format (obs.v0.1 JSON). You can write your own extractor in any language, or use an existing one such as stave-extractor. See Building an Extractor for a jumpstart template.

Your extractor should read the files in snapshot-raw/ and produce one or more obs.v0.1 JSON files in an output directory:

# Example: run your extractor
./my-s3-extractor.sh ./snapshot-raw ./observations

Step 3: Validate the observations

Check that the extracted data is well-formed before evaluation.

stave validate --controls controls/s3 --observations ./observations

If validation fails, the error message tells you exactly which field is missing or malformed. Fix your extractor script (Step 2) and re-run it.

Step 4: Apply built-in controls

Run all 43 built-in S3 controls against your observations. This is where findings appear.

stave apply --controls controls/s3 --observations ./observations \
  --max-unsafe 168h --now "$(date -u +%Y-%m-%dT%H:%M:%SZ)" --format text

Example output:

Evaluation Results
==================

Summary
-------
  Controls evaluated:  43
  Assets evaluated:    12
  Attack surface:      2
  Violations:          3

Violations
----------
  1. CTL.S3.CONTROLS.001
     Public Access Block Must Be Enabled
     Asset: res:aws:s3:bucket:staging-uploads
     Remediation: Enable BlockPublicAccess on this bucket.

  2. CTL.S3.ENCRYPT.002
     Transport Encryption Required
     Asset: res:aws:s3:bucket:staging-uploads
     Remediation: Add a bucket policy requiring ssl-only access.

  3. CTL.S3.LOG.001
     Access Logging Required
     Asset: res:aws:s3:bucket:staging-uploads
     Remediation: Enable server access logging.

You now have your first findings with specific remediation guidance.

Step 5: Fix and verify

Fix the issues in your AWS account, then take a second snapshot and re-evaluate.

# Fix the cloud config (e.g., enable BlockPublicAccess in AWS console or Terraform)

# Take a second snapshot
aws s3api get-public-access-block --bucket staging-uploads > snapshot-raw/staging-uploads-pab.json

# Re-run your extractor and re-evaluate
./my-s3-extractor.sh ./snapshot-raw ./observations
stave apply --controls controls/s3 --observations ./observations \
  --max-unsafe 168h --now "$(date -u +%Y-%m-%dT%H:%M:%SZ)" --format text

If the fix worked, the finding disappears from the output. To formally verify:

# Save both evaluations
stave apply ... -f json > before.json   # (from Step 4)
stave apply ... -f json > after.json    # (after fix)
stave verify --before before.json --after after.json

Step 6: Check status

See where you are in the workflow and what to do next:

stave status

What if apply returns no findings?

Your infrastructure might be clean, or the threshold might be too high. Run:

stave diagnose --controls controls/s3 --observations ./observations

This explains why findings did not trigger — threshold too high, time span too short, no predicate matches, or data shape issues.

What if validate fails?

The error tells you which field is missing or malformed. Common fixes:

• Missing captured_at: add a timestamp to your observation: "captured_at": "2026-03-15T00:00:00Z"
• Schema mismatch: ensure observations use obs.v0.1 format — flat JSON, no "snapshots" wrapper

Fix your extractor script, re-run it, and validate again.

Summary

Step	Command	What happens
1	AWS CLI + jq	Extract bucket config from your account
2	Your extractor	Normalize raw exports to observations
3	stave validate	Check observations are well-formed
4	stave apply	Evaluate 43 S3 controls, get findings
5	Fix + re-snapshot	Remediate, retake snapshot, re-evaluate
6	stave verify	Confirm the fix resolved the finding