detecting-aws-guardduty-findings-automation

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/detecting-aws-guardduty-findings-automation
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summary

Automate AWS GuardDuty threat detection findings processing using EventBridge and Lambda to enable real-time incident response, automatic quarantine of compromised resources, and security notification workflows.

skill.md
name
detecting-aws-guardduty-findings-automation
description
Automate AWS GuardDuty threat detection findings processing using EventBridge and Lambda to enable real-time incident response, automatic quarantine of compromised resources, and security notification workflows.
domain
cybersecurity
subdomain
cloud-security
tags
- aws - guardduty - eventbridge - lambda - threat-detection - automation - incident-response - siem
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- PR.IR-01 - ID.AM-08 - GV.SC-06 - DE.CM-01

Detecting AWS GuardDuty Findings Automation

Overview

Amazon GuardDuty is a threat detection service that continuously monitors AWS accounts for malicious activity and unauthorized behavior. By integrating GuardDuty with Amazon EventBridge and AWS Lambda, security teams achieve automated, real-time responses to threats, reducing mean time to response (MTTR) from hours to seconds. GuardDuty analyzes VPC Flow Logs, CloudTrail management and data events, DNS logs, EKS audit logs, and S3 data events.

When to Use

  • When investigating security incidents that require detecting aws guardduty findings automation
  • When building detection rules or threat hunting queries for this domain
  • When SOC analysts need structured procedures for this analysis type
  • When validating security monitoring coverage for related attack techniques

Prerequisites

  • AWS account with GuardDuty enabled
  • IAM roles for Lambda execution
  • EventBridge configured for GuardDuty events
  • SNS topic for security notifications
  • Security Hub integration (recommended)

Enable GuardDuty

# Enable GuardDuty
aws guardduty create-detector --enable --finding-publishing-frequency FIFTEEN_MINUTES

# Enable additional data sources
aws guardduty update-detector \
  --detector-id DETECTOR_ID \
  --data-sources '{
    "S3Logs": {"Enable": true},
    "Kubernetes": {"AuditLogs": {"Enable": true}},
    "MalwareProtection": {"ScanEc2InstanceWithFindings": {"EbsVolumes": true}},
    "RuntimeMonitoring": {"Enable": true}
  }'

EventBridge Rule Configuration

Rule for high-severity findings

{
  "source": ["aws.guardduty"],
  "detail-type": ["GuardDuty Finding"],
  "detail": {
    "severity": [{"numeric": [">=", 7.0]}]
  }
}

Create EventBridge rule via CLI

aws events put-rule \
  --name "guardduty-high-severity" \
  --event-pattern '{
    "source": ["aws.guardduty"],
    "detail-type": ["GuardDuty Finding"],
    "detail": {
      "severity": [{"numeric": [">=", 7.0]}]
    }
  }'

aws events put-targets \
  --rule "guardduty-high-severity" \
  --targets "Id"="lambda-handler","Arn"="arn:aws:lambda:us-east-1:123456789012:function:guardduty-response"

Lambda Automated Response Functions

EC2 Instance Isolation

import boto3
import json
import os

ec2 = boto3.client('ec2')
sns = boto3.client('sns')

QUARANTINE_SG = os.environ.get('QUARANTINE_SECURITY_GROUP')
SNS_TOPIC = os.environ.get('SNS_TOPIC_ARN')

def lambda_handler(event, context):
    finding = event['detail']
    finding_type = finding['type']
    severity = finding['severity']
    account_id = finding['accountId']
    region = finding['region']

    # Extract resource information
    resource = finding.get('resource', {})
    resource_type = resource.get('resourceType', '')

    if resource_type == 'Instance':
        instance_id = resource['instanceDetails']['instanceId']
        instance_tags = {t['key']: t['value']
                        for t in resource['instanceDetails'].get('tags', [])}

        # Skip if already quarantined
        if instance_tags.get('SecurityStatus') == 'Quarantined':
            return {'statusCode': 200, 'body': 'Already quarantined'}

        # Get current security groups for forensics
        instance = ec2.describe_instances(InstanceIds=[instance_id])
        current_sgs = [sg['GroupId'] for sg in
                       instance['Reservations'][0]['Instances'][0]['SecurityGroups']]

        # Tag instance with finding info and original SGs
        ec2.create_tags(
            Resources=[instance_id],
            Tags=[
                {'Key': 'SecurityStatus', 'Value': 'Quarantined'},
                {'Key': 'GuardDutyFinding', 'Value': finding_type},
                {'Key': 'OriginalSecurityGroups', 'Value': ','.join(current_sgs)},
                {'Key': 'QuarantineTime', 'Value': finding['updatedAt']}
            ]
        )

        # Move to quarantine security group (blocks all traffic)
        if QUARANTINE_SG:
            ec2.modify_instance_attribute(
                InstanceId=instance_id,
                Groups=[QUARANTINE_SG]
            )

        # Create EBS snapshots for forensics
        volumes = ec2.describe_volumes(
            Filters=[{'Name': 'attachment.instance-id', 'Values': [instance_id]}]
        )
        for vol in volumes['Volumes']:
            ec2.create_snapshot(
                VolumeId=vol['VolumeId'],
                Description=f'GuardDuty forensic snapshot - {finding_type}',
                TagSpecifications=[{
                    'ResourceType': 'snapshot',
                    'Tags': [
                        {'Key': 'Purpose', 'Value': 'ForensicCapture'},
                        {'Key': 'SourceInstance', 'Value': instance_id},
                        {'Key': 'FindingType', 'Value': finding_type}
                    ]
                }]
            )

        # Notify security team
        sns.publish(
            TopicArn=SNS_TOPIC,
            Subject=f'[GuardDuty] {finding_type} - Instance {instance_id} Quarantined',
            Message=json.dumps({
                'action': 'instance_quarantined',
                'instance_id': instance_id,
                'finding_type': finding_type,
                'severity': severity,
                'account': account_id,
                'region': region,
                'original_security_groups': current_sgs,
                'description': finding.get('description', '')
            }, indent=2)
        )

        return {
            'statusCode': 200,
            'body': f'Instance {instance_id} quarantined and snapshots created'
        }

    return {'statusCode': 200, 'body': 'Non-EC2 finding processed'}

IAM Credential Compromise Response

import boto3
import json
import os

iam = boto3.client('iam')
sns = boto3.client('sns')

SNS_TOPIC = os.environ.get('SNS_TOPIC_ARN')

def lambda_handler(event, context):
    finding = event['detail']
    finding_type = finding['type']

    if 'IAMUser' not in finding_type and 'UnauthorizedAccess' not in finding_type:
        return {'statusCode': 200, 'body': 'Not an IAM finding'}

    resource = finding.get('resource', {})
    access_key_details = resource.get('accessKeyDetails', {})
    user_name = access_key_details.get('userName', '')
    access_key_id = access_key_details.get('accessKeyId', '')

    if not user_name:
        return {'statusCode': 200, 'body': 'No user identified'}

    actions_taken = []

    # Deactivate the compromised access key
    if access_key_id and access_key_id != 'GeneratedFindingAccessKeyId':
        try:
            iam.update_access_key(
                UserName=user_name,
                AccessKeyId=access_key_id,
                Status='Inactive'
            )
            actions_taken.append(f'Deactivated access key {access_key_id}')
        except Exception as e:
            actions_taken.append(f'Failed to deactivate key: {str(e)}')

    # Attach deny-all policy to user
    deny_policy = {
        "Version": "2012-10-17",
        "Statement": [{
            "Effect": "Deny",
            "Action": "*",
            "Resource": "*"
        }]
    }

    try:
        iam.put_user_policy(
            UserName=user_name,
            PolicyName='GuardDuty-DenyAll-Quarantine',
            PolicyDocument=json.dumps(deny_policy)
        )
        actions_taken.append(f'Applied deny-all policy to {user_name}')
    except Exception as e:
        actions_taken.append(f'Failed to apply deny policy: {str(e)}')

    # Notify
    sns.publish(
        TopicArn=SNS_TOPIC,
        Subject=f'[GuardDuty] IAM Compromise - {user_name}',
        Message=json.dumps({
            'finding_type': finding_type,
            'user': user_name,
            'access_key': access_key_id,
            'actions_taken': actions_taken,
            'severity': finding['severity']
        }, indent=2)
    )

    return {'statusCode': 200, 'body': json.dumps(actions_taken)}

Terraform Deployment

resource "aws_guardduty_detector" "main" {
  enable = true
  finding_publishing_frequency = "FIFTEEN_MINUTES"

  datasources {
    s3_logs { enable = true }
    kubernetes { audit_logs { enable = true } }
    malware_protection {
      scan_ec2_instance_with_findings {
        ebs_volumes { enable = true }
      }
    }
  }
}

resource "aws_cloudwatch_event_rule" "guardduty_high" {
  name        = "guardduty-high-severity"
  description = "GuardDuty high severity findings"

  event_pattern = jsonencode({
    source      = ["aws.guardduty"]
    detail-type = ["GuardDuty Finding"]
    detail = {
      severity = [{ numeric = [">=", 7.0] }]
    }
  })
}

resource "aws_cloudwatch_event_target" "lambda" {
  rule = aws_cloudwatch_event_rule.guardduty_high.name
  arn  = aws_lambda_function.guardduty_response.arn
}

Finding Categories

CategorySeverity RangeExamples
Backdoor5.0 - 8.0Backdoor:EC2/C&CActivity
CryptoCurrency5.0 - 8.0CryptoCurrency:EC2/BitcoinTool
Trojan5.0 - 8.0Trojan:EC2/BlackholeTraffic
UnauthorizedAccess5.0 - 8.0UnauthorizedAccess:IAMUser/ConsoleLogin
Recon2.0 - 5.0Recon:EC2/PortProbeUnprotected
Persistence5.0 - 8.0Persistence:IAMUser/AnomalousBehavior

Multi-Account Setup

# Designate GuardDuty administrator
aws guardduty enable-organization-admin-account \
  --admin-account-id 111111111111

# Auto-enable for new accounts
aws guardduty update-organization-configuration \
  --detector-id DETECTOR_ID \
  --auto-enable

References

how to use detecting-aws-guardduty-findings-automation

How to use detecting-aws-guardduty-findings-automation on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add detecting-aws-guardduty-findings-automation
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/detecting-aws-guardduty-findings-automation

The skills CLI fetches detecting-aws-guardduty-findings-automation from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/detecting-aws-guardduty-findings-automation

Reload or restart Cursor to activate detecting-aws-guardduty-findings-automation. Access the skill through slash commands (e.g., /detecting-aws-guardduty-findings-automation) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.651 reviews
  • Isabella Zhang· Dec 24, 2024

    We added detecting-aws-guardduty-findings-automation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Diego Shah· Dec 24, 2024

    Useful defaults in detecting-aws-guardduty-findings-automation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Min Wang· Dec 4, 2024

    detecting-aws-guardduty-findings-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Min Li· Nov 27, 2024

    I recommend detecting-aws-guardduty-findings-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sakshi Patil· Nov 23, 2024

    I recommend detecting-aws-guardduty-findings-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Diego Gupta· Nov 23, 2024

    detecting-aws-guardduty-findings-automation has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Isabella Liu· Nov 19, 2024

    detecting-aws-guardduty-findings-automation reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Aditi Malhotra· Nov 15, 2024

    Solid pick for teams standardizing on skills: detecting-aws-guardduty-findings-automation is focused, and the summary matches what you get after install.

  • Min Abbas· Oct 18, 2024

    Useful defaults in detecting-aws-guardduty-findings-automation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chaitanya Patil· Oct 14, 2024

    Useful defaults in detecting-aws-guardduty-findings-automation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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