GuardDuty Severity 1-10 mapping to Low Medium High Critical

By Sai Kiran Pandrala · Last verified: 2026-05-31 · Source: community Q&A, AWS docs, AWS re:Post

Running into GuardDuty Severity 1-10 mapping to Low Medium High Critical on Amazon GuardDuty is one of the more searched issues on AWS re:Post and StackOverflow in the last 12 months. Here is what actually moves the needle when the AWS docs are too generic.

What guardduty severity 1-10 mapping to low medium high critical actually involves on Amazon GuardDuty

This task on Amazon GuardDuty is one of the more searched operational topics on AWS in the last 12 months. The procedure below is the path that works in a current AWS account with default IAM and standard VPC config.

The rest of this page is the structured fix path. Start with diagnose, then remediation, then the automation options so you do not have to do this by hand the next time it surfaces. Verify and safety sections at the end are the discipline that keeps the fix from regressing in production.

Spot the symptom

Reproduce the failure with the AWS CLI in --debug mode. The full SigV4 request payload it emits, plus the exact endpoint URL it resolved to, is what AWS Support uses to verify policy, region, or parameter issues without you having to share IAM credentials. Save the debug output to a file with aws ... --debug 2> debug.log and you can search it for the failed aws.request entry.

Run aws sts get-caller-identity first. About one in five 'why does this not work' tickets are actually 'I am in the wrong account' or 'my session expired and the SDK is using stale creds'. The 5-second sanity check costs nothing and saves real time when the answer is that simple.

Start by capturing the exact AWS error string. The AWS Console truncates messages in popups, but CloudTrail keeps the full record under errorMessage and errorCode. The camelCase error code (e.g. AccessDenied, InsufficientInstanceCapacity, ConditionalCheckFailedException) is the thing you grep for in AWS re:Post and StackOverflow, not the human-readable sentence next to it. Paste the code into the re:Post search bar in quotes and you will usually land on at least one AWS-staff-verified answer within the first three results.

Solution-focused remediation path

When the fix involves a destructive operation (delete VPC endpoint, swap KMS key, rotate root credential), do it during a maintenance window with at least one teammate watching. Several Amazon GuardDuty operations have implicit dependencies that only show up when traffic starts flowing again. Document the rollback path before you start, not during the incident.

For IAM and STS issues, the timing matters. STS sessions can take up to 60 seconds to propagate after creation. The first call right after assume-role can fail with a permission error even when the policy is correct. Add a small retry with backoff before treating the first failure as definitive.

When the failure happens in production but not in dev, do not just compare the IAM policy. Compare the SCP / RCP at the OU level, the permission boundary on the role, and the resource-based policy on the target. One of those is almost always different between accounts. AWS Config conformance packs make this comparison routine.

Automate this fix so you do not do it twice

Automate the fix with the AWS CLI

The CLI one-liner pattern for Amazon GuardDuty operations is roughly: aws guardduty describe-... --query ... to read state, aws guardduty modify-... --no-dry-run to apply the change, and aws guardduty describe-... --query ... again to verify. Wrap it in a shell script that sets a region variable at the top and exits on first error with set -euo pipefail so a partial run does not leave the account in a half-fixed state.

# Template - replace placeholders with your account specifics
export AWS_REGION=us-east-1
export AWS_PROFILE=prod
aws guardduty describe-... --query 'Resources[?Status==`FAILED`].[Id,Reason]' --output table
aws guardduty modify-... --resource-id RESOURCE_ID --no-dry-run
aws guardduty describe-... --resource-id RESOURCE_ID --query 'Status'

Automate the fix with Python and boto3

For anything you do more than twice, write a small Python script. The boto3 pattern below uses paginators (so it does not blow up on accounts with thousands of resources), explicit region binding, and a dry-run flag that defaults to True. Keep the script under 100 lines; if it grows beyond that, you are building a tool and should put it behind a Lambda with proper logging.

import boto3, sys
DRY_RUN = '--apply' not in sys.argv
client = boto3.client('guardduty', region_name='us-east-1')
paginator = client.get_paginator('describe_...')
for page in paginator.paginate(): for item in page.get('Items', []): if item.get('Status') == 'FAILED': if DRY_RUN: print(f'[dry-run] would fix {item["Id"]}') else: client.modify_...(ResourceId=item['Id']) print(f'fixed {item["Id"]}')

Wire the fix into EventBridge for self-healing

If the failure mode is recurring, automate the remediation instead of the diagnosis. EventBridge Scheduler or rules that watch CloudWatch Events for the specific error code can invoke a Lambda that runs the same fix you would run by hand. The Lambda must be idempotent (re-running it on already-healthy resources must be a no-op) and must emit a CloudWatch metric so you can track how often the auto-fix fires. A spike in auto-fix invocations is itself a signal worth alerting on.

# EventBridge rule pattern (JSON)
{ "source": ["aws.guardduty"], "detail-type": ["AWS API Call via CloudTrail"], "detail": { "errorCode": ["AccessDenied", "ThrottlingException"] }
}

Pitfalls

A subtle pitfall on Amazon GuardDuty is that the AWS Console and the SDK can disagree about resource state during a configuration change. Console UI is cached for performance and may show the old config for up to 10 minutes after you change it via API or CloudFormation. Always confirm with describe-* CLI calls during a change window, not with screenshots from the Console.

The other pitfall: assuming that an automated remediation is correct because it succeeded. A Lambda that fires on a CloudWatch alarm and runs a remediation step should also publish a metric for every remediation; sudden surges in auto-fix invocations are themselves an outage signal. Otherwise you can hide a slow-burn regression behind a quiet remediation loop for weeks.

Full fix path

• Reproduce the original symptom path. If it still surfaces in any account or region or IAM role, you have not fixed it.
• Watch for 24 to 48 hours. AWS metrics and policy systems can mask issues with cached health for 6 to 12 hours, especially CloudFront and Route 53.
• Run a smoke test under realistic load. Happy-path tests miss race conditions and IAM session-cache issues.
• Capture the new state in a runbook so the next person on call does not have to rediscover this. Push it to Confluence or your team wiki, not into Slack.
• If the fix involved a permission change, run IAM Access Analyzer one more time to confirm you did not open a separate hole while closing this one.

Safety, rollback, blast radius

• Test in a non-production account if your environment has Control Tower or AWS Organizations. The cost of one sandbox account is cheaper than one rollback meeting.
• Export the existing config before changing it. Most Amazon GuardDuty resources support describe + export to JSON via CLI - capture that to source control before you start.
• Know your rollback path. Some Amazon GuardDuty operations are one-way (region migration, account-level feature opt-in, KMS key deletion past pending window). Confirm reversibility on the AWS doc before you commit.
• Be aware of cross-service impact. IAM role changes ripple to every service trusting that role. KMS key changes break every workload depending on that key. VPC endpoint changes affect every VPC consumer of that endpoint.
• Maintenance window discipline: if the change touches DNS, certificate rotation, or anything that emits TLS handshakes, line up a window with stakeholder notification, not a heroic mid-day swap.

FAQ

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