[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AE9DMD9QZRRMVTQSHH11HT":3,"skill-same:01M6AE9DMD9QZRRMVTQSHH11HT":134},{"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":28,"publishedAt":45,"linkOnly":46,"markdownContent":47,"markdownBody":48,"frontMatter":49,"refName":89,"commitSha":90,"skillDirectory":91,"forksCount":92,"repositoryHtmlUrl":93,"repositoryHomepageUrl":94,"ownerHtmlUrl":95,"ownerBlogUrl":96,"ownerDescription":97,"updatedAt":98,"install":99,"resources":112},"01M6AE9DMD9QZRRMVTQSHH11HT","detecting-aws-cloudtrail-anomalies",null,"Detect unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access.","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",35925,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdetecting-aws-cloudtrail-anomalies\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44],"cloudtrail","aws","detecting aws cloudtrail anomalies","security","cybersecurity","pr","development","logs","cloud","cloud-security","threat-detection","escalation","detection","defense","anomaly-detection","boto3","2026-11-10 10:12:30",false,"---\nname: detecting-aws-cloudtrail-anomalies\ndescription: Detect unusual API call patterns in AWS CloudTrail logs using boto3,\n  statistical baselining, and behavioral analysis to identify credential compromise,\n  privilege escalation, and unauthorized resource access.\ndomain: cybersecurity\nsubdomain: cloud-security\ntags:\n- cloud-security\n- aws\n- cloudtrail\n- anomaly-detection\n- threat-detection\n- boto3\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nnist_csf:\n- PR.IR-01\n- ID.AM-08\n- GV.SC-06\n- DE.CM-01\nmitre_attack:\n- T1078.004\n- T1580\n- T1538\n- T1098.001\n- T1526\nmitre_f3:\n  version: '1.1'\n  tactics:\n  - initial-access\n  - positioning\n  - defense-impairment\n  techniques:\n  - id: F1006.001\n    name: 'Account Takeover: Exposed API Key'\n    tactic: initial-access\n    source: f3\n  - id: T1586.003\n    name: 'Compromise Accounts: Cloud Accounts'\n    tactic: resource-development\n    source: attack\n  - id: F1005\n    name: Account Manipulation\n    tactic: positioning\n    source: f3\n  - id: F1005.002\n    name: 'Account Manipulation: Add Authorized User'\n    tactic: positioning\n    source: f3\n  - id: F1005.001\n    name: 'Account Manipulation: Account Linking'\n    tactic: defense-impairment\n    source: f3\n---\n# Detecting AWS CloudTrail Anomalies\n\n## Overview\n\nAWS CloudTrail records API calls across AWS services. This skill covers querying CloudTrail events with boto3's `lookup_events` API, building statistical baselines of normal API activity, detecting anomalies such as unusual event sources, geographic anomalies, high-frequency API calls, and first-time API usage patterns that indicate compromised credentials or insider threats.\n\n\n## When to Use\n\n- When investigating security incidents that require detecting aws cloudtrail anomalies\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- Python 3.9+ with `boto3` library\n- AWS credentials with CloudTrail read permissions (cloudtrail:LookupEvents)\n- Understanding of AWS IAM and common API patterns\n- CloudTrail enabled in target AWS account (management events at minimum)\n\n## Steps\n\n### Step 1: Query CloudTrail Events\nUse boto3 CloudTrail client's lookup_events to retrieve recent API activity with pagination.\n\n### Step 2: Build Activity Baseline\nAggregate events by user, source IP, event source, and event name to establish normal behavior patterns.\n\n### Step 3: Detect Anomalies\nFlag unusual patterns: new event sources per user, first-time API calls, geographic IP changes, high error rates, and sensitive API usage (IAM, KMS, S3 policy changes).\n\n### Step 4: Generate Detection Report\nProduce a JSON report with anomaly scores, top suspicious users, and recommended investigation actions.\n\n## Expected Output\n\nJSON report with event statistics, baseline deviations, anomalous users\u002FIPs, sensitive API calls, and error rate analysis.\n","# Detecting AWS CloudTrail Anomalies\n\n## Overview\n\nAWS CloudTrail records API calls across AWS services. This skill covers querying CloudTrail events with boto3's `lookup_events` API, building statistical baselines of normal API activity, detecting anomalies such as unusual event sources, geographic anomalies, high-frequency API calls, and first-time API usage patterns that indicate compromised credentials or insider threats.\n\n\n## When to Use\n\n- When investigating security incidents that require detecting aws cloudtrail anomalies\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- Python 3.9+ with `boto3` library\n- AWS credentials with CloudTrail read permissions (cloudtrail:LookupEvents)\n- Understanding of AWS IAM and common API patterns\n- CloudTrail enabled in target AWS account (management events at minimum)\n\n## Steps\n\n### Step 1: Query CloudTrail Events\nUse boto3 CloudTrail client's lookup_events to retrieve recent API activity with pagination.\n\n### Step 2: Build Activity Baseline\nAggregate events by user, source IP, event source, and event name to establish normal behavior patterns.\n\n### Step 3: Detect Anomalies\nFlag unusual patterns: new event sources per user, first-time API calls, geographic IP changes, high error rates, and sensitive API usage (IAM, KMS, S3 policy changes).\n\n### Step 4: Generate Detection Report\nProduce a JSON report with anomaly scores, top suspicious users, and recommended investigation actions.\n\n## Expected Output\n\nJSON report with event statistics, baseline deviations, anomalous users\u002FIPs, sensitive API calls, and error rate analysis.\n",{"name":5,"tags":50,"author":51,"domain":33,"license":15,"version":52,"mitre_f3":53,"nist_csf":78,"subdomain":38,"description":7,"mitre_attack":83},[38,30,29,43,39,44],"mahipal","1.0",{"tactics":54,"version":58,"techniques":59},[55,56,57],"initial-access","positioning","defense-impairment","1.1",[60,64,69,72,75],{"id":61,"name":62,"source":63,"tactic":55},"F1006.001","Account Takeover: Exposed API Key","f3",{"id":65,"name":66,"source":67,"tactic":68},"T1586.003","Compromise Accounts: Cloud Accounts","attack","resource-development",{"id":70,"name":71,"source":63,"tactic":56},"F1005","Account Manipulation",{"id":73,"name":74,"source":63,"tactic":56},"F1005.002","Account Manipulation: Add Authorized User",{"id":76,"name":77,"source":63,"tactic":57},"F1005.001","Account Manipulation: Account Linking",[79,80,81,82],"PR.IR-01","ID.AM-08","GV.SC-06","DE.CM-01",[84,85,86,87,88],"T1078.004","T1580","T1538","T1098.001","T1526","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fdetecting-aws-cloudtrail-anomalies",4384,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills","https:\u002F\u002Fmahipal.engineer\u002FAnthropic-Cybersecurity-Skills\u002F","https:\u002F\u002Fgithub.com\u002Fmukul975","Mahipal.engineer","🔐 Cybersecurity | 💻 Dev | 📷 Street Photographer\r\n🎓 MSc | 📚 Research & AI Security","2026-08-31 12:32:44",{"source":8,"skillName":5,"commands":100,"prompt":110,"zipAvailable":111},[101,104,107],{"tool":102,"command":103},"npx","npx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill detecting-aws-cloudtrail-anomalies",{"tool":105,"command":106},"bunx","bunx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill detecting-aws-cloudtrail-anomalies",{"tool":108,"command":109},"pnpm","pnpm dlx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill detecting-aws-cloudtrail-anomalies","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdetecting-aws-cloudtrail-anomalies\u002FSKILL.md",true,[113,119,124,128],{"path":114,"resourceType":115,"resourceTypeDesc":116,"sizeBytes":117,"sourceHtmlUrl":118},"agents\u002Fopenai.yaml","REFERENCE","参考文档",135,"https:\u002F\u002Fgithub.com\u002Fhareki\u002Fdotfiles\u002Fblob\u002Fmain\u002Fagents\u002F.agents\u002Fskills\u002Fto-spec\u002Fagents\u002Fopenai.yaml",{"path":120,"resourceType":120,"resourceTypeDesc":121,"sizeBytes":122,"sourceHtmlUrl":123},"LICENSE","许可证",11255,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdetecting-aws-cloudtrail-anomalies\u002FLICENSE",{"path":125,"resourceType":115,"resourceTypeDesc":116,"sizeBytes":126,"sourceHtmlUrl":127},"references\u002Fapi-reference.md",2110,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdetecting-aws-cloudtrail-anomalies\u002Freferences\u002Fapi-reference.md",{"path":129,"resourceType":130,"resourceTypeDesc":131,"sizeBytes":132,"sourceHtmlUrl":133},"scripts\u002Fagent.py","SCRIPT","脚本",7468,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdetecting-aws-cloudtrail-anomalies\u002Fscripts\u002Fagent.py",[135,162,186,213,238,265],{"skillNo":136,"name":137,"nameZh":6,"description":138,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":139,"categories":140,"keywords":144,"publishedAt":45},"01M6AGDM3HJXTKXX15ZZ0ZVCJ3","verifying-build-provenance-with-slsa-sigstore","Verifies artifact signatures and SLSA provenance using Sigstore's cosign (verify, verify-attestation, verify-blob-attestation) and slsa-verifier (verify-artifact), enforcing keyless OIDC builder identity and source repo against SLSA Build levels. Use in CI\u002FCD before deploying artifacts, when consuming third-party attestations, establishing a SLSA Build L3 pipeline, or confirming provenance during incident response or admission control.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fverifying-build-provenance-with-slsa-sigstore\u002FSKILL.md",[141],{"categoryNo":142,"categoryName":143,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[145,146,147,148,32,33,149,150,34,151,152,153,154,155,156,157,158,159,160,161],"sigstore","provenance","slsa","verifying build provenance with slsa sigstore","incident response","identity","code","artifacts","ci","supply-chain","pipeline","supply-chain-security","t1195","attestation","code-signing","cosign","keyless",{"skillNo":163,"name":164,"nameZh":6,"description":165,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":166,"categories":167,"keywords":169,"publishedAt":45},"01M6AGDGBPWYVZ2F11GFKJ4HZ9","validating-tpm-measured-boot-attestation","Verifies TPM 2.0 measured-boot integrity and remote attestation with tpm2-tools -- reading PCRs (tpm2_pcrread), replaying the boot event log, generating and checking signed quotes (tpm2_quote\u002Ftpm2_checkquote), and sealing secrets to a PCR policy. Use to confirm a system booted trusted firmware\u002Fkernel for Zero Trust device posture, detect boot-chain tampering via PCR drift, or build a golden-value baseline for fleet attestation.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fvalidating-tpm-measured-boot-attestation\u002FSKILL.md",[168],{"categoryNo":142,"categoryName":143,"taxonomyType":21,"taxonomyTypeDesc":22},[170,158,171,172,32,173,33,34,174,175,176,177,178,179,180,181,182,183,184,185],"boot","TPM","validating tpm measured boot attestation","policy","verification","ZeRO","firmware","Tools","measured-boot","PCR","integrity","secrets","remote-attestation","tpm2-tools","integrity-verification","trusted-computing",{"skillNo":187,"name":188,"nameZh":6,"description":189,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":190,"categories":191,"keywords":196,"publishedAt":45},"01M6AGDCW0Y4FXZ3362GT1941M","validating-backup-integrity-for-recovery","Validates backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to confirm backups are reliable for disaster recovery and ransomware response. Use before relying on backups for recovery, when building post-backup validation pipelines, auditing backup infrastructure for compliance, or checking immutable\u002Fair-gapped backups for silent corruption or tampering.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fvalidating-backup-integrity-for-recovery\u002FSKILL.md",[192,195],{"categoryNo":193,"categoryName":194,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":142,"categoryName":143,"taxonomyType":21,"taxonomyTypeDesc":22},[180,197,198,199,200,33,201,202,174,203,204,205,206,207,41,208,209,210,211,212],"backup","recovery","validating backup integrity for recovery","testing","infrastructure","validation","compliance","hash-verification","incident-response","ransomware","cryptocurrency","t1078","t1490","immutable","disaster-recovery","restore-testing",{"skillNo":214,"name":215,"nameZh":6,"description":216,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":217,"categories":218,"keywords":220,"publishedAt":45},"01M6AGD9GBG2KZ336AE763J3WH","triaging-windows-with-kape","Runs KAPE (Kroll Artifact Parser and Extractor) to collect targeted forensic artifacts (registry hives, $MFT, event logs, prefetch, browser data) via Targets and parse them with Modules wrapping Eric Zimmerman's EZ Tools (PECmd, MFTECmd, RECmd). Use during early incident containment\u002Ftriage when full disk imaging is impractical but a defensible, parseable Windows artifact set is needed quickly, including at-scale remote collection.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-windows-with-kape\u002FSKILL.md",[219],{"categoryNo":142,"categoryName":143,"taxonomyType":21,"taxonomyTypeDesc":22},[221,222,223,33,224,225,36,226,227,228,229,230,231,232,233,234,177,235,236,237],"windows","kape","triaging windows with kape","registry","browser","windows-forensics","dfir","mft","mftecmd","data","prefetch","eric-zimmerman","digital-forensics","SET","collection","pecmd","artifact-collection",{"skillNo":239,"name":240,"nameZh":6,"description":241,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":242,"categories":243,"keywords":245,"publishedAt":45},"01M6AGD5PW5J4EVZM958WD74ZQ","triaging-vulnerabilities-with-ssvc-framework","Triages and prioritizes vulnerabilities with CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree, weighing exploitation status (via the CISA KEV catalog and FIRST EPSS API), technical impact, automatability, and mission prevalence to output Track\u002FTrack*\u002FAttend\u002FAct decisions. Use when prioritizing vulnerability scan results (OpenVAS, Nessus, Qualys) for remediation planning beyond raw CVSS scores.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-vulnerabilities-with-ssvc-framework\u002FSKILL.md",[244],{"categoryNo":142,"categoryName":143,"taxonomyType":21,"taxonomyTypeDesc":22},[246,247,248,33,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264],"vulnerabilities","framework","triaging vulnerabilities with ssvc framework","status","planning","CISA","vulnerability-management","risk-management","nessus","qualys","openvas","cvss","remediation","risk","vulnerability","api","prioritization","ssvc","decision-tree",{"skillNo":266,"name":267,"nameZh":6,"description":268,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":269,"categories":270,"keywords":272,"publishedAt":45},"01M6AGD24TTQQM4CXG69E3B9TJ","triaging-security-incident","Performs initial triage of security incidents using the NIST SP 800-61r3 and SANS PICERL frameworks, classifying incident type, assigning priority by business impact, and routing to the appropriate response team. Use when a SIEM\u002FEDR alert needs human classification, concurrent alerts must be prioritized, or a user report or threat-intel IOC match requires initial incident categorization.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-security-incident\u002FSKILL.md",[271],{"categoryNo":142,"categoryName":143,"taxonomyType":21,"taxonomyTypeDesc":22},[32,273,33,274,275,276,277,278,279,280,281,208,282,209,283,284,285,286,287,288],"triaging security incident","siem","file","ioc","soc","NIST-800-61","NIST","severity","edr","execution","analysis","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]