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.

mukul975/Anthropic-Cybersecurity-Skills|Updated May 25, 2026

Works with

Claude CodeCursorClineWindsurf

Installation Guide

Select your AI agent

How to use analyzing-cloud-storage-access-patterns on Cursor

AI-first code editor with Composer

Prerequisites

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

›Cursor installed and configured on your machine
›Node.js 16+ with npm — verify with node --version
›Active project directory where you want to add analyzing-cloud-storage-access-patterns

Run the install command

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

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/analyzing-cloud-storage-access-patterns

Fetches analyzing-cloud-storage-access-patterns from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ────────────────

│ · Cline · Codex · Goose · Windsurf

│ ●Cursor(selected)

│ · Cursor · Aider · Continue

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/analyzing-cloud-storage-access-patterns

Restart Cursor to activate analyzing-cloud-storage-access-patterns. Access via /analyzing-cloud-storage-access-patterns in your agent's command palette.

⚠

Security 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 environment. Always review source, verify the publisher, and test in isolation before production.

›View source on GitHub ›Skills CLI docs ›About Cursor ›What are agent skills?

Documentation

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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

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

Instructions

Install dependencies: pip install boto3 requests

Query CloudTrail for S3 Data Events using AWS CLI or boto3.

Build access baselines: hourly request volume, per-user object counts, source IP history.

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)

Generate prioritized findings report.

python scripts/agent.py --bucket my-sensitive-data --hours-back 24 --output s3_access_report.json

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

name	analyzing-cloud-storage-access-patterns
description	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.
domain	cybersecurity
subdomain	cloud-security
tags	- analyzing - cloud - storage - access
version	'1.0'
author	mahipal
license	Apache-2.0
atlas_techniques	- AML.T0024 - AML.T0056
nist_ai_rmf	- MEASURE-2.7 - MAP-5.1 - MANAGE-2.4
nist_csf	- PR.IR-01 - ID.AM-08 - GV.SC-06 - DE.CM-01

analyzing-cloud-storage-access-patterns

Installation Guide

How to use analyzing-cloud-storage-access-patterns on Cursor

Prerequisites

Run the install command

Select Cursor when prompted

Verify installation

Security Notice

Documentation

List & Monetize Your Skill

Use Cases

Task Automation & Efficiency

Knowledge Enhancement

Quality Improvement

Install Skill

Analyzing Cloud Storage Access Patterns

When to Use

Prerequisites

Instructions

Examples

CloudTrail S3 Data Event

Implementation Guide

Best Practices

When to Use This

Learning Path

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