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Analyzing cloud storage access patterns

Skill Mikaru0Mystic/sectinel/arsenal/Anthropic-Cybersecurity-Skills/skills/analyzing-cloud-storage-access-patterns

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Install
npx -y skills add Mikaru0Mystic/sectinel --skill analyzing-cloud-storage-access-patterns

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Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.

The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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Analyzing Cloud Storage Access Patterns

When to Use

  • When investigating security incidents that require analyzing cloud storage access patterns
  • 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

  • Familiarity with cloud security concepts and tools
  • Access to a test or lab environment for safe execution
  • Python 3.8+ with required dependencies installed
  • Appropriate authorization for any testing activities

Instructions

  1. Install dependencies: pip install boto3 requests
  2. Query CloudTrail for S3 Data Events using AWS CLI or boto3.
  3. Build access baselines: hourly request volume, per-user object counts, source IP history.
  4. Detect anomalies:
    • After-hours access (outside 8am-6pm local time)
    • Bulk downloads: >100 GetObject calls from single principal in 1 hour
    • New source IPs not seen in the prior 30 days
    • ListBucket enumeration spikes (reconnaissance indicator)
  5. Generate prioritized findings report.
python scripts/agent.py --bucket my-sensitive-data --hours-back 24 --output s3_access_report.json

Examples

CloudTrail S3 Data Event

{"eventName": "GetObject", "requestParameters": {"bucketName": "sensitive-data", "key": "financials/q4.xlsx"},
 "sourceIPAddress": "203.0.113.50", "userIdentity": {"arn": "arn:aws:iam::123456789012:user/analyst"}}

What ships with it: 3 files

20.4 KB alongside SKILL.md, 1 of them executable

references/

scripts/

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