Agent skill

Implementing AWS Macie For Data Classification

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Enable and configure Amazon Macie via AWS CLI/Terraform to discover, classify, and protect sensitive data (PII, financial data, credentials) in S3 using ML and pattern matching, including discovery…

Apache-2.0Auto-check passedDevOps & Cloud

Install Implementing AWS Macie For Data Classification

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-aws-macie-for-data-classification -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-aws-macie-for-data-classification --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implementing-aws-macie-for-data-classification .claude/skills/implementing-aws-macie-for-data-classification && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
implementing-aws-macie-for-data-classification
GitHub stars
34k
Token cost
~2.1k tokens
SKILL.md length
309 words
Files
8 (incl. scripts, references, assets)
Skills in repo
637
Repo updated
First seen
Licence
Apache-2.0

At a glance

Enable and configure Amazon Macie via AWS CLI/Terraform to discover, classify, and protect sensitive data (PII, financial data, credentials) in S3 using ML and pattern matching, including discovery…

  • Setting up S3 data classification
  • SKILL.md covers Overview, When to Use, Prerequisites and Enable Macie, plus 9 more sections
  • Runs Python scripts from its folder; calls aws
  • Auditing S3 for unprotected sensitive data

What it does

Implementing AWS Macie For Data Classification is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Enable and configure Amazon Macie via AWS CLI/Terraform to discover, classify, and protect sensitive data (PII, financial data, credentials) in S3 using ML and pattern matching, including discovery jobs, custom data identifiers, allow lists, and EventBridge-based remediation. Use when setting up S3 data classification, cloud DLP, or auditing S3 for unprotected sensitive data.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/api-reference.md` and `references/standards.md`).

It sits in DevOps & Cloud, covering File uploads and storage and Infrastructure as code. It works with Amazon Web Services and Terraform. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Setting up S3 data classification
  • Auditing S3 for unprotected sensitive data

Example prompts

  • “/implementing-aws-macie-for-data-classification”

Requirements

  • Python 3
  • A credential in OBJECT_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • aws

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.aws.amazon.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Implementing AWS Macie For Data Classification loads about 2.1k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 106 tokens; SKILL.md has 309 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~106
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 309 words, ~2,138 tokens.

Download SKILL.mdSave it as .claude/skills/implementing-aws-macie-for-data-classification/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
implementing-aws-macie-for-data-classification
description
Enable and configure Amazon Macie via AWS CLI/Terraform to discover, classify, and protect sensitive data (PII, financial data, credentials) in S3 using ML and pattern matching, including discovery jobs, custom data identifiers, allow lists, and EventBridge-based remediation. Use when setting up S3 data classification, cloud DLP, or auditing S3 for unprotected sensitive data.
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
mitre_attack
T1078.004, T1530, T1537, T1580, T1003

Implementing AWS Macie for Data Classification

Overview

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.

When to Use

  • When deploying or configuring implementing aws macie for data classification capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • AWS account with S3 buckets containing data to classify
  • IAM permissions for Macie service configuration
  • AWS Organizations setup (for multi-account deployment)
  • S3 buckets in supported regions

Enable Macie

Via AWS CLI
bash
# 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
Via Terraform
hcl
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
  }
}

Configure Discovery Jobs

Create a classification job for specific buckets
bash
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
Create a scheduled recurring job
bash
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/"]
          }
        }]
      }
    }
  }'

Custom Data Identifiers

Create a custom identifier for internal IDs
bash
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"}
  ]'
Create identifier for project codes
bash
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

Allow Lists

Create an allow list to suppress false positives
bash
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}"
  }'

Managed Data Identifiers

Macie provides 300+ managed data identifiers covering:

CategoryExamples
PIISSN, passport numbers, driver's license, date of birth, names, addresses
FinancialCredit card numbers, bank account numbers, SWIFT codes
CredentialsAWS secret keys, API keys, SSH private keys, OAuth tokens
HealthHIPAA identifiers, health insurance claim numbers
LegalTax identification numbers, national ID numbers

Findings Management

List findings
bash
# 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
Get finding details
bash
aws macie2 get-findings \
  --finding-ids '["finding-id-1", "finding-id-2"]'
Export findings to Security Hub
bash
# Macie automatically publishes findings to Security Hub
# Verify integration:
aws macie2 get-macie-session --query 'findingPublishingFrequency'

EventBridge Integration for Automated Response

json
{
  "source": ["aws.macie"],
  "detail-type": ["Macie Finding"],
  "detail": {
    "severity": {
      "description": ["High", "Critical"]
    }
  }
}
Lambda function for automated remediation
python
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}

Multi-Account Deployment

Designate Macie administrator account
bash
# From the management account
aws macie2 enable-organization-admin-account \
  --admin-account-id 111111111111
Add member accounts
bash
# From the administrator account
aws macie2 create-member \
  --account '{"accountId": "222222222222", "email": "security@example.com"}'

Monitoring Macie Operations

Usage statistics
bash
aws macie2 get-usage-statistics \
  --filter-by '[{"comparator": "GT", "key": "accountId", "values": []}]' \
  --sort-by '{"key": "accountId", "orderBy": "ASC"}'
Classification job status
bash
aws macie2 list-classification-jobs \
  --filter-criteria '{"includes": [{"comparator": "EQ", "key": "jobStatus", "values": ["RUNNING"]}]}'

References

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references, assets) in skills/implementing-aws-macie-for-data-classification of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • assets/template.md
  • references/api-reference.md
  • references/standards.md
  • references/workflows.md
  • scripts/agent.py
  • scripts/process.py

Open the folder on GitHubat commit 54a7988

Compare with similar skills

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SkillStarsUsed inTokensAuto-checkLicenceRepo updated
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AWS Cloud Patternsrohitg00/awesome-claude-code-toolkit2.7k—~1.1kAutomated safety check: PassApache-2.0
Msk Operationsaws/tools-for-devops-agent100—~6.6kAutomated safety check: PassApache-2.0
AWS Iamaws/agent-toolkit-for-aws2.8k—~1.7kAutomated safety check: PassApache-2.0
AWS Solution Architectborghei/Claude-Skills881—~1.8kAutomated safety check: PassMIT

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Questions about Implementing AWS Macie For Data Classification

What does Implementing AWS Macie For Data Classification do?

Enable and configure Amazon Macie via AWS CLI/Terraform to discover, classify, and protect sensitive data (PII, financial data, credentials) in S3 using ML and pattern matching, including discovery…. Implementing AWS Macie For Data Classification is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Enable and configure Amazon Macie via AWS CLI/Terraform to discover, classify, and protect sensitive data (PII, financial data, credentials) in S3 using ML and pattern matching, including discovery jobs, custom data identifiers, allow lists, and EventBridge-based remediation.

When should I use Implementing AWS Macie For Data Classification?

Implementing AWS Macie For Data Classification fits situations like: setting up S3 data classification; auditing S3 for unprotected sensitive data.

How do I install Implementing AWS Macie For Data Classification in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-aws-macie-for-data-classification -a claude-code`. Or copy the skill folder (skills/implementing-aws-macie-for-data-classification in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/implementing-aws-macie-for-data-classification in your project. Claude Code loads it when a task matches its description.

How do I install Implementing AWS Macie For Data Classification in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-aws-macie-for-data-classification -a codex`. Or copy the skill folder (skills/implementing-aws-macie-for-data-classification in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/implementing-aws-macie-for-data-classification in your project. Codex loads it when a task matches its description.

Can I use Implementing AWS Macie For Data Classification in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-aws-macie-for-data-classification -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-aws-macie-for-data-classification, .gemini/skills/implementing-aws-macie-for-data-classification, .github/skills/implementing-aws-macie-for-data-classification and .opencode/skills/implementing-aws-macie-for-data-classification in your project.

What does Implementing AWS Macie For Data Classification need to run?

Going by SKILL.md and its folder, Implementing AWS Macie For Data Classification needs Python for the scripts in its folder and the command-line tools its instructions call (aws). Our summary lists: Python 3; A credential in OBJECT_KEY.

Does Implementing AWS Macie For Data Classification access the network?

SKILL.md names 1 domain. As links in the text: docs.aws.amazon.com. This is read from the text; nothing was executed.

Is Implementing AWS Macie For Data Classification safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Implementing AWS Macie For Data Classification use?

Implementing AWS Macie For Data Classification is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Implementing AWS Macie For Data Classification use?

About 2.1k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 882 tokens, read only when the agent opens those files.

What are the alternatives to Implementing AWS Macie For Data Classification?

Skills that share tags, products or a category with Implementing AWS Macie For Data Classification: AWS Advisor (diegosouzapw/awesome-omni-skills, 159 stars), AWS Cloud Patterns (rohitg00/awesome-claude-code-toolkit, 2.7k stars), Msk Operations (aws/tools-for-devops-agent, 100 stars) and AWS Iam (aws/agent-toolkit-for-aws, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Implementing AWS Macie For Data Classification?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,922 GitHub stars. The repository holds 637 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.