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.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionanalyzing-cloud-storage-access-patternsExecute the skills CLI command in your project's root directory to begin installation:
Fetches analyzing-cloud-storage-access-patterns from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate analyzing-cloud-storage-access-patterns. Access via /analyzing-cloud-storage-access-patterns in your agent's command palette.
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.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
0
total installs
0
this week
8.6K
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
8.6K
stars
| 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 |
pip install boto3 requestspython 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"}}
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
I recommend analyzing-cloud-storage-access-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
analyzing-cloud-storage-access-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: analyzing-cloud-storage-access-patterns is focused, and the summary matches what you get after install.
analyzing-cloud-storage-access-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for analyzing-cloud-storage-access-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
analyzing-cloud-storage-access-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in analyzing-cloud-storage-access-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added analyzing-cloud-storage-access-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for analyzing-cloud-storage-access-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: analyzing-cloud-storage-access-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.
showing 1-10 of 75