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mukul975
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Complete skill folder anatomy across all cybersecurity skills: - scripts/agent.py: 80-150 line Python agents using real libraries (impacket, boto3, azure-mgmt-*, kubernetes, pefile, yara, scapy, shodan, stix2, etc.) - references/api-reference.md: real API documentation with method signatures - LICENSE: MIT license for all skill folders
2.0 KiB
2.0 KiB
API Reference: AWS Macie Data Classification Agent
Dependencies
| Library | Version | Purpose |
|---|---|---|
| boto3 | >=1.28 | AWS SDK for Macie2 sensitive data discovery |
CLI Usage
python scripts/agent.py \
--profile security-audit \
--region us-east-1 \
--output-dir /reports/ \
--output macie_report.json
Functions
get_macie_client(profile, region)
Creates boto3 Macie2 client with optional named profile.
enable_macie(client) -> dict
Calls client.get_macie_session() to check status, then client.enable_macie() if needed.
list_s3_buckets_summary(client) -> list
Calls client.describe_buckets() to get bucket inventory with encryption, public access, and classifiable object counts.
create_classification_job(client, bucket_names, job_name) -> dict
Calls client.create_classification_job(jobType="ONE_TIME", s3JobDefinition={...}) for targeted sensitive data discovery.
get_finding_statistics(client) -> dict
Calls client.get_finding_statistics(groupBy=...) for severity and type breakdowns.
list_findings(client, severity, max_results) -> list
Calls client.list_findings() with severity criterion, then client.get_findings(findingIds=[...]) for details.
generate_report(client) -> dict
Orchestrates all functions and compiles summary with public bucket identification.
boto3 Macie2 Methods Used
| Method | Purpose |
|---|---|
enable_macie(status) |
Enable Macie service |
describe_buckets(criteria) |
S3 bucket inventory |
create_classification_job(...) |
Start discovery job |
get_finding_statistics(groupBy) |
Finding aggregations |
list_findings(findingCriteria) |
Filter findings |
get_findings(findingIds) |
Detailed finding data |
Output Schema
{
"summary": {"total_buckets": 45, "public_buckets": 2, "high_findings": 12},
"bucket_inventory": [{"name": "my-bucket", "public_access": "NOT_PUBLIC"}],
"high_findings": [{"type": "SensitiveData:S3Object/Personal", "bucket": "data-lake"}]
}