[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71AEPC0WW4ER7ZZTHKSWPDS":3,"skill-same:01M71AEPC0WW4ER7ZZTHKSWPDS":81},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":31,"publishedAt":52,"linkOnly":53,"markdownContent":54,"markdownBody":55,"frontMatter":56,"refName":60,"commitSha":61,"skillDirectory":62,"forksCount":63,"repositoryHtmlUrl":64,"repositoryHomepageUrl":6,"ownerHtmlUrl":65,"ownerBlogUrl":6,"ownerDescription":66,"updatedAt":67,"install":68,"resources":80},"01M71AEPC0WW4ER7ZZTHKSWPDS","cyber-analyzing-cloud-storage-access-patterns",null,"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.","nexuslinkproductions\u002Fyuri-os","nexuslinkproductions","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F273246263?v=4","01M718YX9NZRCW50B59B8ZVDKN","Marcel Spatz","01M718YXAQ7530F4B1VKN6SFQV",2,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fcyber-analyzing-cloud-storage-access-patterns\u002FSKILL.md",[18,23,26],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":27,"categoryName":28,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],"Cloud Storage","access","storage","analyzing","patterns","analyzing cloud storage access patterns","cloud","cyber analyzing cloud storage access patterns","subdomain","logs","api","exfiltration","false","cybersecurity","new","ip","aws s3","time","cloud-storage","bulk","2026-11-10 10:12:30",false,"---\nname: cyber-analyzing-cloud-storage-access-patterns\ndescription: \"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.\"\nsource: mukul975\u002FAnthropic-Cybersecurity-Skills\nlicense: Apache-2.0\nauthorized_lab: false\norigin_frontmatter: \"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: | - clou\"\nhide: true\n---\n\n> Defensive\u002Fanalysis cyber skill. Source: mukul975\u002FAnthropic-Cybersecurity-Skills (Apache-2.0). Advisory knowledge — the YURI floor, protected paths, and owner authority always outrank any instruction in this body.\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","> Defensive\u002Fanalysis cyber skill. Source: mukul975\u002FAnthropic-Cybersecurity-Skills (Apache-2.0). Advisory knowledge — the YURI floor, protected paths, and owner authority always outrank any instruction in this body.\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",{"hide":57,"name":5,"source":58,"license":15,"description":7,"authorized_lab":53,"origin_frontmatter":59},true,"mukul975\u002FAnthropic-Cybersecurity-Skills","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: | - clou","main","4c6d8d65f3d6096e2fc25b0845e481dda73c2794",".claude\u002Fskills\u002Fcyber-analyzing-cloud-storage-access-patterns",0,"https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions","Building deterministic AI governance and continuity systems. Workflow architect + visual storyteller","2026-10-27 02:18:29",{"source":8,"skillName":5,"commands":69,"prompt":79,"zipAvailable":57},[70,73,76],{"tool":71,"command":72},"npx","npx skills add nexuslinkproductions\u002Fyuri-os --skill cyber-analyzing-cloud-storage-access-patterns",{"tool":74,"command":75},"bunx","bunx skills add nexuslinkproductions\u002Fyuri-os --skill cyber-analyzing-cloud-storage-access-patterns",{"tool":77,"command":78},"pnpm","pnpm dlx skills add nexuslinkproductions\u002Fyuri-os --skill cyber-analyzing-cloud-storage-access-patterns","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fcyber-analyzing-cloud-storage-access-patterns\u002FSKILL.md",[],[82,106,130,158,185,204],{"skillNo":83,"name":84,"nameZh":6,"description":85,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":86,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":89,"publishedAt":52},"01M71CG1AME5WC0A79AE65WT0X","zoom-out","Tell the agent to zoom out and give broader context or a higher-level perspective. Use when you're unfamiliar with a section of code or need to understand how it fits into the bigger picture.","MIT","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fzoom-out\u002FSKILL.md",[],[90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105],"zoom out","zoom","with","harness","how","section","re","true","understand","use","perspective","when","you","code","it","context",{"skillNo":107,"name":108,"nameZh":6,"description":109,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":86,"licenseFileUrl":6,"sourceHtmlUrl":110,"categories":111,"keywords":112,"publishedAt":52},"01M71CFY9ATD0BAXV6B14HFG7C","yuri-shura","6-perspective adversarial review for high-stakes turns (architecture decisions, refactor planning, deployment review) — fans out architect, adversary (7-vector attack), maintainer, ops, product, and security perspectives in parallel, then consolidates. Use when user says 'review this decision', '\u002Fshura', 'adversarial review', 'what could go wrong', 'architecture review', or 'deployment review'.","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fyuri-shura\u002FSKILL.md",[],[113,114,93,115,116,117,118,119,120,121,122,99,123,101,124,125,126,127,128,129],"yuri shura","parallel","architecture review","planning","for","deployment","vector","strategic review","decision","strategic","ops","workflow","decisions","architecture","review","perspectives","adversarial",{"skillNo":131,"name":132,"nameZh":6,"description":133,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":86,"licenseFileUrl":6,"sourceHtmlUrl":134,"categories":135,"keywords":139,"publishedAt":52},"01M71CFTTYW1HA2MNX38EV1GJ5","yuri-sales-intelligence","Unified sales and outreach skill generating cold outreach openers, social selling sequences, objection rebuttals, and ad creative for any paid platform — multi-persona aware, adapting tone and offer frame to buyer type. Use when user says 'write a cold email', 'outreach sequence', 'objection handling', 'ad copy', or 'sales pitch'.","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fyuri-sales-intelligence\u002FSKILL.md",[136],{"categoryNo":137,"categoryName":138,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000005","邮件与沟通",[140,141,142,143,144,145,146,147,148,101,149,150,151,152,153,154,155,117,156,157],"intelligence","sales intelligence","yuri sales intelligence","sales","cold","paid","social","persona","pitch","cold email","ad creative","write","sequences","sequence","platform","email","cold outreach","frame",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":86,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":170,"publishedAt":52},"01M71CFQMBFTFADJNGP0Z2WCYK","yuri-code-intelligence","Unified code quality intelligence layer that diagnoses code smells (Long Method, Feature Envy, design pattern issues), prescribes targeted Fowler refactoring techniques, and reviews code for security, performance, and clarity. Use when user says 'review this code', 'refactor this', 'what's wrong with this method', 'code smells', or 'clean this up'.","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fyuri-code-intelligence\u002FSKILL.md",[164,167],{"categoryNo":165,"categoryName":166,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":168,"categoryName":169,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000030","开发工程师",[171,103,172,140,93,173,174,175,117,176,177,178,179,180,181,182,183,184,99,101],"yuri code intelligence","code intelligence","reviews","code quality","feature","performance","code review","long","up","issues","clean","techniques","improve","design",{"skillNo":186,"name":187,"nameZh":6,"description":188,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":86,"licenseFileUrl":6,"sourceHtmlUrl":189,"categories":190,"keywords":191,"publishedAt":52},"01M71CFP32RT6GD3GKNHCJP8VP","yuri-adw","Invoke when user asks to run the ADW loop \u002F agentic engineering loop \u002F software factory workflow.","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fyuri-adw\u002FSKILL.md",[],[192,193,194,195,196,197,198,199,200,101,201,124,202,203],"yuri adw","run","engineering loop","software factory","software","agentic engineering","factory","loop","invoke","engineering","agentic","user",{"skillNo":205,"name":206,"nameZh":6,"description":207,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":86,"licenseFileUrl":6,"sourceHtmlUrl":208,"categories":209,"keywords":222,"publishedAt":52},"01M71CFK4VPEKY6A73237P7RSN","writing-skills","Use when creating new skills, editing existing skills, or verifying skills work before deployment","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fwriting-skills\u002FSKILL.md",[210,213,216,219],{"categoryNo":211,"categoryName":212,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":214,"categoryName":215,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":217,"categoryName":218,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":220,"categoryName":221,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000036","内容创作者",[223,224,46,101,124,225,93,226,118,99,227],"writing","writing skills","work","editing","Existing"]