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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.","henriquescastilho\u002Fmy-claude","henriquescastilho","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F153296945?v=4","01M6ESH7EXPXTH9CVQ4K16SRG8","Henrique Scheer","01M6ESH7JHEK2PTNNH4HEH787Z",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fanalyzing-cloud-storage-access-patterns\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"storage","cloud","analyzing cloud storage access patterns","analyzing","access","patterns","bulk","cybersecurity","de","aws s3","ip","time-series","time","map","cm","aml","api","t1078","exfiltration","logs","2026-11-10 10:12:30",false,"---\nname: analyzing-cloud-storage-access-patterns\ndescription: Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage\n  by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics.\n  Identifies after-hours bulk downloads, access from new IP addresses, unusual API\n  calls (GetObject spikes), and potential data exfiltration using statistical baselines\n  and time-series anomaly detection.\ndomain: cybersecurity\nsubdomain: cloud-security\ntags:\n- cloud-security\n- aws-s3\n- gcs\n- azure-blob-storage\n- cloudtrail\n- data-access-anomaly\n- exfiltration-detection\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\natlas_techniques:\n- AML.T0024\n- AML.T0056\nnist_ai_rmf:\n- MEASURE-2.7\n- MAP-5.1\n- MANAGE-2.4\nnist_csf:\n- PR.IR-01\n- ID.AM-08\n- GV.SC-06\n- DE.CM-01\nmitre_attack:\n- T1530\n- T1567.002\n- T1619\n- T1078.004\n- T1048\n---\n\n\n# Analyzing Cloud Storage Access Patterns\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing cloud storage access patterns\n- When building detection rules or threat hunting queries for this domain\n- When SOC analysts need structured procedures for this analysis type\n- When validating security monitoring coverage for related attack techniques\n\n## Prerequisites\n\n- Familiarity with cloud security concepts and tools\n- Access to a test or lab environment for safe execution\n- Python 3.8+ with required dependencies installed\n- Appropriate authorization for any testing activities\n\n## Instructions\n\n1. Install dependencies: `pip install boto3 requests`\n2. Query CloudTrail for S3 Data Events using AWS CLI or boto3.\n3. Build access baselines: hourly request volume, per-user object counts, source IP history.\n4. Detect anomalies:\n   - After-hours access (outside 8am-6pm local time)\n   - Bulk downloads: >100 GetObject calls from single principal in 1 hour\n   - New source IPs not seen in the prior 30 days\n   - ListBucket enumeration spikes (reconnaissance indicator)\n5. Generate prioritized findings report.\n\n```bash\npython scripts\u002Fagent.py --bucket my-sensitive-data --hours-back 24 --output s3_access_report.json\n```\n\n## Examples\n\n### CloudTrail S3 Data Event\n```json\n{\"eventName\": \"GetObject\", \"requestParameters\": {\"bucketName\": \"sensitive-data\", \"key\": \"financials\u002Fq4.xlsx\"},\n \"sourceIPAddress\": \"203.0.113.50\", \"userIdentity\": {\"arn\": \"arn:aws:iam::123456789012:user\u002Fanalyst\"}}\n```\n","# Analyzing Cloud Storage Access Patterns\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing cloud storage access patterns\n- When building detection rules or threat hunting queries for this domain\n- When SOC analysts need structured procedures for this analysis type\n- When validating security monitoring coverage for related attack techniques\n\n## Prerequisites\n\n- Familiarity with cloud security concepts and tools\n- Access to a test or lab environment for safe execution\n- Python 3.8+ with required dependencies installed\n- Appropriate authorization for any testing activities\n\n## Instructions\n\n1. Install dependencies: `pip install boto3 requests`\n2. Query CloudTrail for S3 Data Events using AWS CLI or boto3.\n3. Build access baselines: hourly request volume, per-user object counts, source IP history.\n4. Detect anomalies:\n   - After-hours access (outside 8am-6pm local time)\n   - Bulk downloads: >100 GetObject calls from single principal in 1 hour\n   - New source IPs not seen in the prior 30 days\n   - ListBucket enumeration spikes (reconnaissance indicator)\n5. Generate prioritized findings report.\n\n```bash\npython scripts\u002Fagent.py --bucket my-sensitive-data --hours-back 24 --output s3_access_report.json\n```\n\n## Examples\n\n### CloudTrail S3 Data Event\n```json\n{\"eventName\": \"GetObject\", \"requestParameters\": {\"bucketName\": \"sensitive-data\", \"key\": \"financials\u002Fq4.xlsx\"},\n \"sourceIPAddress\": \"203.0.113.50\", \"userIdentity\": {\"arn\": \"arn:aws:iam::123456789012:user\u002Fanalyst\"}}\n```\n",{"name":5,"tags":49,"author":57,"domain":31,"license":15,"version":58,"nist_csf":59,"subdomain":50,"description":7,"nist_ai_rmf":64,"mitre_attack":68,"atlas_techniques":74},[50,51,52,53,54,55,56],"cloud-security","aws-s3","gcs","azure-blob-storage","cloudtrail","data-access-anomaly","exfiltration-detection","mahipal","1.0",[60,61,62,63],"PR.IR-01","ID.AM-08","GV.SC-06","DE.CM-01",[65,66,67],"MEASURE-2.7","MAP-5.1","MANAGE-2.4",[69,70,71,72,73],"T1530","T1567.002","T1619","T1078.004","T1048",[75,76],"AML.T0024","AML.T0056","main","7925716f065257435fdb12e97f7e52842147d5ad",".claude\u002Fskills\u002Fanalyzing-cloud-storage-access-patterns","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude","https:\u002F\u002Fclaude.com\u002Fclaude-code","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho","Software · Applied AI · Quantitative Modeling · Building with Claude.","2026-06-10 12:24:46",{"source":8,"skillName":5,"commands":86,"prompt":96,"zipAvailable":97},[87,90,93],{"tool":88,"command":89},"npx","npx skills add henriquescastilho\u002Fmy-claude --skill analyzing-cloud-storage-access-patterns",{"tool":91,"command":92},"bunx","bunx skills add henriquescastilho\u002Fmy-claude --skill analyzing-cloud-storage-access-patterns",{"tool":94,"command":95},"pnpm","pnpm dlx skills add henriquescastilho\u002Fmy-claude --skill analyzing-cloud-storage-access-patterns","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fanalyzing-cloud-storage-access-patterns\u002FSKILL.md",true,[99,104,110,114,118],{"path":100,"resourceType":100,"resourceTypeDesc":101,"sizeBytes":102,"sourceHtmlUrl":103},"LICENSE","许可证",11255,"https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fanalyzing-cloud-storage-access-patterns\u002FLICENSE",{"path":105,"resourceType":106,"resourceTypeDesc":107,"sizeBytes":108,"sourceHtmlUrl":109},"README.md","REFERENCE","参考文档",4297,"https:\u002F\u002Fgithub.com\u002Fmarcelfahle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzight\u002FREADME.md",{"path":111,"resourceType":106,"resourceTypeDesc":107,"sizeBytes":112,"sourceHtmlUrl":113},"reference.md",5297,"https:\u002F\u002Fgithub.com\u002Fmarcelfahle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzight\u002Freference.md",{"path":115,"resourceType":106,"resourceTypeDesc":107,"sizeBytes":116,"sourceHtmlUrl":117},"references\u002Fapi-reference.md",1539,"https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fanalyzing-cloud-storage-access-patterns\u002Freferences\u002Fapi-reference.md",{"path":119,"resourceType":120,"resourceTypeDesc":121,"sizeBytes":122,"sourceHtmlUrl":123},"scripts\u002Fagent.py","SCRIPT","脚本",8058,"https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fanalyzing-cloud-storage-access-patterns\u002Fscripts\u002Fagent.py",[125,166,175,184,203,231],{"skillNo":126,"name":127,"nameZh":6,"description":128,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":129,"licenseFileUrl":6,"sourceHtmlUrl":130,"categories":131,"keywords":146,"publishedAt":44},"01M6F0B6XPQ65AX2X0DWK8KT3E","markitdown","Convert files and office documents to Markdown. 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