Implement Amazon Macie to automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII, financial data, and credentials detection.
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Write scripts to clean messy data, handle missing values, normalize formats
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Automate 80% of data preprocessing work
Perform hypothesis testing, regression, and statistical modeling
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Get statistically sound analysis without PhD in statistics
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epx add mukul975/Anthropic-Cybersecurity-Skills/implementing-aws-macie-for-data-classificationCompatible with
Supported agents
| name | implementing-aws-macie-for-data-classification |
| description | Implement Amazon Macie to automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII, financial data, and credentials detection. |
| domain | cybersecurity |
| subdomain | cloud-security |
| tags | - aws - macie - data-classification - s3 - pii - sensitive-data - dlp - compliance |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| atlas_techniques | - AML.T0043 - AML.T0018 |
| nist_ai_rmf | - GOVERN-1.1 - GOVERN-4.2 - MAP-2.3 - MEASURE-2.7 - MEASURE-2.5 |
| nist_csf | - PR.IR-01 - ID.AM-08 - GV.SC-06 - DE.CM-01 |
Amazon Macie is a fully managed data security and privacy service that uses machine learning and pattern matching to discover and protect sensitive data in Amazon S3. Macie automatically evaluates your S3 bucket inventory on a daily basis and identifies objects containing PII, financial information, credentials, and other sensitive data types. It provides two discovery approaches: automated sensitive data discovery for broad visibility and targeted discovery jobs for deep analysis.
# Enable Macie in the current account/region
aws macie2 enable-macie
# Verify Macie is enabled
aws macie2 get-macie-session
# Enable automated sensitive data discovery
aws macie2 update-automated-discovery-configuration \
--status ENABLED
resource "aws_macie2_account" "main" {}
resource "aws_macie2_classification_export_configuration" "main" {
depends_on = [aws_macie2_account.main]
s3_destination {
bucket_name = aws_s3_bucket.macie_results.id
key_prefix = "macie-findings/"
kms_key_arn = aws_kms_key.macie.arn
}
}
aws macie2 create-classification-job \
--job-type ONE_TIME \
--name "pii-scan-production-buckets" \
--s3-job-definition '{
"bucketDefinitions": [{
"accountId": "123456789012",
"buckets": [
"production-data-bucket",
"customer-records-bucket"
]
}]
}' \
--managed-data-identifier-selector ALL
aws macie2 create-classification-job \
--job-type SCHEDULED \
--name "weekly-sensitive-data-scan" \
--schedule-frequency-details '{
"weekly": {
"dayOfWeek": "MONDAY"
}
}' \
--s3-job-definition '{
"bucketDefinitions": [{
"accountId": "123456789012",
"buckets": ["all-data-bucket"]
}],
"scoping": {
"includes": {
"and": [{
"simpleScopeTerm": {
"comparator": "STARTS_WITH",
"key": "OBJECT_KEY",
"values": ["uploads/", "documents/"]
}
}]
}
}
}'
aws macie2 create-custom-data-identifier \
--name "internal-employee-id" \
--description "Matches internal employee ID format EMP-XXXXXX" \
--regex "EMP-[0-9]{6}" \
--severity-levels '[
{"occurrencesThreshold": 1, "severity": "LOW"},
{"occurrencesThreshold": 10, "severity": "MEDIUM"},
{"occurrencesThreshold": 50, "severity": "HIGH"}
]'
aws macie2 create-custom-data-identifier \
--name "project-code-identifier" \
--description "Matches project codes in format PRJ-XXXX-XX" \
--regex "PRJ-[A-Z]{4}-[0-9]{2}" \
--keywords '["project", "code", "initiative"]' \
--maximum-match-distance 50
aws macie2 create-allow-list \
--name "test-data-exclusions" \
--description "Exclude known test data patterns" \
--criteria '{
"regex": "TEST-[0-9]{4}-[0-9]{4}-[0-9]{4}-[0-9]{4}"
}'
Macie provides 300+ managed data identifiers covering:
| Category | Examples |
|---|---|
| PII | SSN, passport numbers, driver's license, date of birth, names, addresses |
| Financial | Credit card numbers, bank account numbers, SWIFT codes |
| Credentials | AWS secret keys, API keys, SSH private keys, OAuth tokens |
| Health | HIPAA identifiers, health insurance claim numbers |
| Legal | Tax identification numbers, national ID numbers |
# Get sensitive data findings
aws macie2 list-findings \
--finding-criteria '{
"criterion": {
"severity.description": {
"eq": ["High"]
},
"category": {
"eq": ["CLASSIFICATION"]
}
}
}' \
--sort-criteria '{"attributeName": "updatedAt", "orderBy": "DESC"}' \
--max-results 25
aws macie2 get-findings \
--finding-ids '["finding-id-1", "finding-id-2"]'
# Macie automatically publishes findings to Security Hub
# Verify integration:
aws macie2 get-macie-session --query 'findingPublishingFrequency'
{
"source": ["aws.macie"],
"detail-type": ["Macie Finding"],
"detail": {
"severity": {
"description": ["High", "Critical"]
}
}
}
import boto3
import json
s3 = boto3.client('s3')
sns = boto3.client('sns')
def lambda_handler(event, context):
finding = event['detail']
severity = finding['severity']['description']
bucket = finding['resourcesAffected']['s3Bucket']['name']
key = finding['resourcesAffected']['s3Object']['key']
sensitive_types = [d['type'] for d in finding.get('classificationDetails', {}).get('result', {}).get('sensitiveData', [])]
if severity in ['High', 'Critical']:
# Tag the object for review
s3.put_object_tagging(
Bucket=bucket,
Key=key,
Tagging={
'TagSet': [
{'Key': 'macie-finding', 'Value': severity},
{'Key': 'sensitive-data', 'Value': ','.join(sensitive_types)},
{'Key': 'requires-review', 'Value': 'true'}
]
}
)
# Notify security team
sns.publish(
TopicArn='arn:aws:sns:us-east-1:123456789012:security-alerts',
Subject=f'Macie {severity} Finding: {bucket}/{key}',
Message=json.dumps({
'bucket': bucket,
'key': key,
'severity': severity,
'sensitive_data_types': sensitive_types,
'finding_id': finding['id']
}, indent=2)
)
return {'statusCode': 200}
# From the management account
aws macie2 enable-organization-admin-account \
--admin-account-id 111111111111
# From the administrator account
aws macie2 create-member \
--account '{"accountId": "222222222222", "email": "security@example.com"}'
aws macie2 get-usage-statistics \
--filter-by '[{"comparator": "GT", "key": "accountId", "values": []}]' \
--sort-by '{"key": "accountId", "orderBy": "ASC"}'
aws macie2 list-classification-jobs \
--filter-criteria '{"includes": [{"comparator": "EQ", "key": "jobStatus", "values": ["RUNNING"]}]}'
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionimplementing-aws-macie-for-data-classificationExecute the skills CLI command in your project's root directory to begin installation:
epx add mukul975/Anthropic-Cybersecurity-Skills/implementing-aws-macie-for-data-classificationFetches implementing-aws-macie-for-data-classification from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/implementing-aws-macie-for-data-classification
Restart Cursor to activate implementing-aws-macie-for-data-classification. Access via /implementing-aws-macie-for-data-classificationin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Time estimate: 20-40 minutes to set up and run first analysis
Prerequisites
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Use for exploratory data analysis, data cleaning, statistical testing, visualization prototyping, and learning new analysis techniques. Best for initial exploration and rapid insights.
✗ Avoid when
Avoid for mission-critical financial analysis, medical research requiring regulatory compliance, production ML models, or when deep statistical expertise is required for nuanced interpretation.
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Keeps context tight: implementing-aws-macie-for-data-classification is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for implementing-aws-macie-for-data-classification matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: implementing-aws-macie-for-data-classification is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: implementing-aws-macie-for-data-classification is focused, and the summary matches what you get after install.
We added implementing-aws-macie-for-data-classification from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in implementing-aws-macie-for-data-classification — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
implementing-aws-macie-for-data-classification fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend implementing-aws-macie-for-data-classification for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: implementing-aws-macie-for-data-classification is focused, and the summary matches what you get after install.
Keeps context tight: implementing-aws-macie-for-data-classification is the kind of skill you can hand to a new teammate without a long onboarding doc.
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