analyzing-cloud-storage-access-patterns

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. Use when detecting abnormal access patterns in aws s3, gcs, and azure.
domain	cybersecurity
tags	["analyzing","cloud","storage","access"]
subdomain	cloud-security
version	1.0
author	oyi77
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

Overview

Cybersecurity skill for analyzing cloud storage access patterns. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "analyzing cloud storage access patterns"

• "Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyz"

• 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

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

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

Workflow

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}

1. Scope the Analysis — Define what cloud storage access patterns artifacts or data sources to examine and the investigation timeline.
2. Preserve Evidence — Create forensic copies of relevant data. Maintain chain of custody documentation.