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analyzing-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection

Install / Use

npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-cloud-storage-access-patterns

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

85/100

Category

Security

Supported Platforms

Universal

Our assessment of analyzing-cloud-storage-access-patterns

analyzing-cloud-storage-access-patterns scores 85/100 on our quality scale, 323rd of 461 Security skills we index.

Its SKILL.md is 2.3 KB long, split into 6 sections with 2 code examples: moderately detailed.

With 33,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
20/30
Structure
16/20
Description
15/15
Adoption
19/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 25 days ago, so analyzing-cloud-storage-access-patterns is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

analyzing-cloud-storage-access-patterns compared with similar skills

All 4 of these similar skills score higher than analyzing-cloud-storage-access-patterns; compare them before choosing.

SkillScoreStarsUpdatedFormat
analyzing-cloud-storage-access-patterns (this skill)by mukul9758533.3k25d agoSKILL.md
Agent-Reachby Panniantong10085.4k9d agoCLAUDE.md
headroomby headroomlabs-ai10073.8ktodayCLAUDE.md
Scraplingby D4Vinci10083.5ktodayMCP Server
LocalAIby mudler10049.3ktodayMCP Server

Frequently asked questions

How do I install analyzing-cloud-storage-access-patterns?
Run npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-cloud-storage-access-patterns. The install tabs above show the steps for each supported agent.
Which AI agents does analyzing-cloud-storage-access-patterns work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is analyzing-cloud-storage-access-patterns safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is analyzing-cloud-storage-access-patterns still maintained?
The repository was last updated 25 days ago, so analyzing-cloud-storage-access-patterns is actively maintained.

name: analyzing-cloud-storage-access-patterns description: Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules. domain: cybersecurity subdomain: cloud-security tags:

  • cloud-security
  • aws-s3
  • gcs
  • azure-blob-storage
  • cloudtrail
  • data-access-anomaly
  • exfiltration-detection 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 mitre_attack:
  • T1530
  • T1567.002
  • T1619
  • T1078.004
  • T1048

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"}}

Related Skills

View on GitHub
GitHub Stars33.3k
CategorySecurity
Updated25d ago
Forks4.0k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions