[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skills:pro6":3,"skills:stats":50,"skills:sce6":55,"skills:creators9":100,"skills:all:stars:118:":195},[4,15,22,29,36,43],{"categoryNo":5,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":8,"categoryNameEn":9,"description":10,"level":11,"skillCount":12,"parentNo":13,"parentName":13,"children":14},"01JBSEEDCAT000000000000030","PROFESSION","适用职业","开发工程师","Software Engineer","从事软件编码、测试与运维的工程师",1,13274,null,[],{"categoryNo":16,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":17,"categoryNameEn":18,"description":19,"level":11,"skillCount":20,"parentNo":13,"parentName":13,"children":21},"01JBSEEDCAT000000000000032","设计师","Designer","视觉、交互与品牌设计人员",7775,[],{"categoryNo":23,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":24,"categoryNameEn":25,"description":26,"level":11,"skillCount":27,"parentNo":13,"parentName":13,"children":28},"01JBSEEDCAT000000000000033","数据分析师","Data Analyst","数据分析、报表与商业智能人员",4988,[],{"categoryNo":30,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":31,"categoryNameEn":32,"description":33,"level":11,"skillCount":34,"parentNo":13,"parentName":13,"children":35},"01JBSEEDCAT000000000000036","内容创作者","Content Creator","作者、编辑与自媒体创作者",3940,[],{"categoryNo":37,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":38,"categoryNameEn":39,"description":40,"level":11,"skillCount":41,"parentNo":13,"parentName":13,"children":42},"01JBSEEDCAT000000000000035","市场营销","Marketer","市场推广、增长与品牌运营人员",3446,[],{"categoryNo":44,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":45,"categoryNameEn":46,"description":47,"level":11,"skillCount":48,"parentNo":13,"parentName":13,"children":49},"01JBSEEDCAT000000000000037","律师与法务","Legal","合同、合规与法律事务人员",3316,[],{"skillCount":51,"professionCount":52,"scenarioCount":53,"creatorCount":54},196852,11,7,1926,[56,65,72,79,86,93],{"categoryNo":57,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":60,"categoryNameEn":61,"description":62,"level":11,"skillCount":63,"parentNo":13,"parentName":13,"children":64},"01JBSEEDCAT000000000000022","SCENARIO","使用场景","智能体与自动化","Agents & Automation","Skill、MCP、智能体与工作流自动化",39458,[],{"categoryNo":66,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":67,"categoryNameEn":68,"description":69,"level":11,"skillCount":70,"parentNo":13,"parentName":13,"children":71},"01JBSEEDCAT000000000000006","软件开发","Software Development","编码、测试、部署等软件研发任务",26531,[],{"categoryNo":73,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":74,"categoryNameEn":75,"description":76,"level":11,"skillCount":77,"parentNo":13,"parentName":13,"children":78},"01JBSEEDCAT000000000000014","设计创意","Design & Creative","视觉设计、品牌与多媒体创作",13569,[],{"categoryNo":80,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":81,"categoryNameEn":82,"description":83,"level":11,"skillCount":84,"parentNo":13,"parentName":13,"children":85},"01JBSEEDCAT000000000000001","办公效率","Office Productivity","日常办公文档、表格、演示与沟通类任务",6289,[],{"categoryNo":87,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":88,"categoryNameEn":89,"description":90,"level":11,"skillCount":91,"parentNo":13,"parentName":13,"children":92},"01JBSEEDCAT000000000000017","内容创作","Content Creation","写作、文案与营销内容生产",6029,[],{"categoryNo":94,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":95,"categoryNameEn":96,"description":97,"level":11,"skillCount":98,"parentNo":13,"parentName":13,"children":99},"01JBSEEDCAT000000000000020","研究与学习","Research & Learning","资料检索、知识整理与学习辅导",5531,[],{"records":101,"total":54,"current":11,"size":194},[102,114,123,133,143,153,163,172,182],{"accountNo":103,"login":104,"displayName":105,"avatarUrl":106,"accountType":107,"accountTypeDesc":108,"profileDescription":109,"skillCount":110,"repoCount":111,"professionCount":52,"scenarioCount":53,"totalStars":112,"updatedAt":113},"01M698VYDXZ6JW5WH3CRV650R8","microsoft","Microsoft","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6154722?v=4","ORGANIZATION","组织","Open source projects and samples from Microsoft",4160,229,828772,"2026-11-13 04:10:52",{"accountNo":115,"login":116,"displayName":116,"avatarUrl":117,"accountType":107,"accountTypeDesc":108,"profileDescription":118,"skillCount":119,"repoCount":120,"professionCount":53,"scenarioCount":53,"totalStars":121,"updatedAt":122},"01M698P3FSAZ6B4R928ZF19KPT","openclaw","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F252820863?v=4","Your personal, open source AI assistant.",362,32,437711,"2026-11-13 03:02:05",{"accountNo":124,"login":125,"displayName":126,"avatarUrl":127,"accountType":107,"accountTypeDesc":108,"profileDescription":13,"skillCount":128,"repoCount":129,"professionCount":53,"scenarioCount":130,"totalStars":131,"updatedAt":132},"01M6AC29YGCR4S2NTJFV0G8B81","openai","OpenAI","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F14957082?v=4",171,23,6,342695,"2026-11-13 04:03:41",{"accountNo":134,"login":135,"displayName":136,"avatarUrl":137,"accountType":107,"accountTypeDesc":108,"profileDescription":13,"skillCount":138,"repoCount":139,"professionCount":140,"scenarioCount":53,"totalStars":141,"updatedAt":142},"01M6AC83E6K4FDKK7HZ8WNMQKE","apache","The Apache Software Foundation","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F47359?v=4",420,75,8,298176,"2026-11-13 03:14:28",{"accountNo":144,"login":145,"displayName":146,"avatarUrl":147,"accountType":107,"accountTypeDesc":108,"profileDescription":148,"skillCount":149,"repoCount":150,"professionCount":52,"scenarioCount":53,"totalStars":151,"updatedAt":152},"01M698VYEFDM0VJBZDYYJ2T83S","google","Google","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F1342004?v=4","Google ❤️ Open Source",535,48,242366,"2026-11-13 04:17:09",{"accountNo":154,"login":155,"displayName":156,"avatarUrl":157,"accountType":107,"accountTypeDesc":108,"profileDescription":158,"skillCount":159,"repoCount":160,"professionCount":52,"scenarioCount":53,"totalStars":161,"updatedAt":162},"01M6AC83DS133TPXFSP1DHNCC6","github","GitHub","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F9919?v=4","How people build software.",940,28,238441,"2026-11-13 03:57:35",{"accountNo":164,"login":165,"displayName":166,"avatarUrl":167,"accountType":107,"accountTypeDesc":108,"profileDescription":13,"skillCount":168,"repoCount":169,"professionCount":52,"scenarioCount":53,"totalStars":170,"updatedAt":171},"01M697XGDPXJAVQ8391V2BCYTE","anthropics","Anthropic","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F76263028?v=4",674,17,231826,"2026-11-13 04:18:26",{"accountNo":173,"login":174,"displayName":175,"avatarUrl":176,"accountType":107,"accountTypeDesc":108,"profileDescription":13,"skillCount":177,"repoCount":178,"professionCount":179,"scenarioCount":53,"totalStars":180,"updatedAt":181},"01M6AC83EPDGBFN19MWYRREJD0","Significant-Gravitas","AutoGPT","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130738209?v=4",86,2,10,188014,"2026-11-13 02:38:59",{"accountNo":183,"login":184,"displayName":185,"avatarUrl":186,"accountType":187,"accountTypeDesc":188,"profileDescription":189,"skillCount":190,"repoCount":191,"professionCount":130,"scenarioCount":53,"totalStars":192,"updatedAt":193},"01M6DJCCDDG53MTYYRTXAXFG17","garrytan","Garry Tan","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F19957?v=4","USER","个人作者","Writes software, dreams. ",324,3,174614,"2026-11-13 04:05:07",9,{"records":196,"total":51,"current":567,"size":568},[197,233,252,281,298,324,348,364,394,409,431,447,462,480,499,518,532,553],{"skillNo":198,"name":199,"nameZh":13,"description":200,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":209,"categories":210,"keywords":211,"publishedAt":232},"01M6AE7CM953J96HVTGR6X2H58","deploying-cloud-deception-with-decoy-resources","Deploy cloud-native deception across AWS, Azure, and GCP using decoy (honey) resources whose only purpose is to generate a high-fidelity alert the instant an attacker touches them: canary IAM access keys, permission-less decoy users\u002Froles\u002Fservice principals, honey object-storage buckets, and decoy secrets in Secrets Manager \u002F Key Vault \u002F Secret Manager. Wires detection through CloudTrail + EventBridge, Azure Sentinel honeytoken watchlists + Defender, and GCP Cloud Audit Logs, so any use of a decoy is routed to the SOC with near-zero false positives. Use when protecting cloud accounts and data stores, when an org has only on-prem honeypots and needs cloud coverage, when seeding fake AWS keys to catch credential theft and code-leak exposure, or when detecting cloud reconnaissance and lateral movement. Keywords: cloud deception, canary token AWS, honey S3 bucket, decoy IAM credentials, CloudTrail alert, GuardDuty, Sentinel honeytoken, decoy secret, honey service account, cloud honeypot, breach detection.","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",35990,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdeploying-cloud-deception-with-decoy-resources\u002FSKILL.md",[],[212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231],"cloud","deception","deploying cloud deception with decoy resources","cybersecurity","storage","defender","azure","generate","code","audit","logs","s3","cloudtrail","soc","ZeRO","data","gcp","iam","sentinel","reconnaissance","2026-11-10 10:12:30",{"skillNo":234,"name":235,"nameZh":13,"description":236,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":237,"categories":238,"keywords":239,"publishedAt":232},"01M6AE78W6PF1RW4GWKF49KVMS","deploying-active-directory-honeytokens","Deploys deception-based honeytokens in Active Directory including fake privileged accounts with AdminCount=1, fake SPNs for Kerberoasting detection (honeyroasting), decoy GPOs with cpassword traps, and fake BloodHound paths. Monitors Windows Security Event IDs 4769, 4625, 4662, 5136 for honeytoken interaction. Use when implementing AD deception defenses for detecting lateral movement, credential theft, and reconnaissance.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdeploying-active-directory-honeytokens\u002FSKILL.md",[],[240,241,242,215,243,244,245,231,246,247,248,249,213,250,251],"directory","deploying active directory honeytokens","security","windows","pr","active-directory","bloodhound","ids","honeytokens","kerberoasting","detection","gpo",{"skillNo":253,"name":254,"nameZh":13,"description":255,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":256,"categories":257,"keywords":261,"publishedAt":232},"01M6AE75GC90ZFSDKQVJJ954HB","deobfuscating-powershell-obfuscated-malware","Systematically deobfuscates multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure. Use during incident response or malware analysis when a PowerShell script is obfuscated with encoding, string manipulation, or invocation tricks and you need to recover the underlying commands, dropped payloads, or C2 endpoints.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdeobfuscating-powershell-obfuscated-malware\u002FSKILL.md",[258],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},"01JBSEEDCAT000000000000023","Skill与智能体开发",[262,263,264,215,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280],"malware","powershell","deobfuscating powershell obfuscated malware","incident response","validation","content","metadata","file","tracing","encoding","malware analysis","c2","malware-analysis","incident-response","T1059.001","deobfuscation","scripting","obfuscation","ast-analysis",{"skillNo":282,"name":283,"nameZh":13,"description":284,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":285,"categories":286,"keywords":288,"publishedAt":232},"01M6AE72JAKAK80DJAPRY8NQFR","deobfuscating-javascript-malware","Deobfuscates malicious JavaScript found in phishing pages, web skimmers, and dropper scripts by reversing encoding layers, eval chains, string manipulation, and control-flow obfuscation to reveal the original malicious logic. Use when investigating a phishing page's obfuscated JavaScript, analyzing a Magecart-style web skimmer, or deobfuscating a JavaScript dropper that fetches second-stage malware.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdeobfuscating-javascript-malware\u002FSKILL.md",[287],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[289,262,290,291,215,292,271,293,274,294,295,277,296,297],"javascript","deobfuscating javascript malware","malicious","web","phishing","analyzing","flow","web-malware","script-analysis",{"skillNo":299,"name":300,"nameZh":13,"description":301,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":302,"categories":303,"keywords":306,"publishedAt":232},"01M6AE6YTDENVGBXK7C1PZ2S5N","defending-llms-with-guardrails","Deploys Llama Guard 3 safety classification, NeMo Guardrails programmable dialogue rails, and LLM Guard input\u002Foutput scanner pipelines as complementary runtime defenses that inspect and constrain LLM prompts and responses. Use when adding a production runtime safety layer to an LLM, RAG, or agent application to block jailbreaks, prompt injection (OWASP LLM01), toxic content, or sensitive-data leakage before it reaches or leaves the model.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdefending-llms-with-guardrails\u002FSKILL.md",[304,305],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},{"categoryNo":30,"categoryName":31,"taxonomyType":6,"taxonomyTypeDesc":7},[307,308,309,310,242,215,311,312,227,313,314,315,316,317,318,319,320,321,322,323],"llms","Guardrails","defending llms with guardrails","prompt injection","rag","NeMo","ai-security","Safety Classification","NeMo Guardrails","Runtime Safety","owasp","llm-guardrails","llama-guard","nemo-guardrails","llm-guard","prompt-injection","content-moderation",{"skillNo":325,"name":326,"nameZh":13,"description":327,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":328,"categories":329,"keywords":335,"publishedAt":232},"01M6AE6VJ3E6F7XVK4XB3KRKQW","correlating-threat-campaigns","Correlates disparate security incidents, IOCs, and adversary behaviors across time and organizations to identify unified threat campaigns, attribute them to common threat actors, and extract shared indicators for improved detection. Use when multiple incidents exhibit overlapping indicators, when sector-wide attack campaigns require cross-organizational analysis, or when building campaign-level intelligence products. Activates for requests involving campaign analysis, incident clustering, cross-organizational IOC correlation, or MISP correlation engine.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fcorrelating-threat-campaigns\u002FSKILL.md",[330,333,334],{"categoryNo":331,"categoryName":332,"taxonomyType":58,"taxonomyTypeDesc":59},"01JBSEEDCAT000000000000019","营销推广",{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},{"categoryNo":37,"categoryName":38,"taxonomyType":6,"taxonomyTypeDesc":7},[336,242,215,337,338,339,340,341,342,343,344,345,346,347],"correlating threat campaigns","threat-actor","threat-intelligence","cti","ioc","campaign-analysis","MISP","clustering","correlation","SET","ATT&CK","intrusion-set",{"skillNo":349,"name":350,"nameZh":13,"description":351,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":352,"categories":353,"keywords":355,"publishedAt":232},"01M6AE6RHJY9MGAF425P0WSSST","correlating-security-events-in-qradar","Correlates security events in IBM QRadar SIEM using AQL (Ariel Query Language), custom rules, building blocks, and offense management to detect multi-stage attacks across network, endpoint, and application log sources. Use when SOC analysts need to investigate QRadar offenses, build correlation rules, or tune detection logic for reducing false positives.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fcorrelating-security-events-in-qradar\u002FSKILL.md",[354],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[242,356,215,357,225,358,344,359,360,361,362,363],"correlating security events in qradar","siem","network","endpoint","qradar","aql","offense-management","ibm",{"skillNo":365,"name":366,"nameZh":13,"description":367,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":368,"categories":369,"keywords":377,"publishedAt":232},"01M6AE6MZ5JK03TPC24YBZP3N3","continuous-llm-red-teaming-with-promptfoo","Wires Promptfoo and DeepTeam into CI\u002FCD for automated, repeatable red-teaming of LLM apps against OWASP LLM Top 10, OWASP Agentic, and MITRE ATLAS presets, failing the build when jailbreak or injection vulnerabilities regress. Use for continuous adversarial testing in CI\u002FCD, a merge-blocking security gate, or comparing model\u002Fprompt versions for compliance reporting.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fcontinuous-llm-red-teaming-with-promptfoo\u002FSKILL.md",[370,373,376],{"categoryNo":371,"categoryName":372,"taxonomyType":58,"taxonomyTypeDesc":59},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":374,"categoryName":375,"taxonomyType":58,"taxonomyTypeDesc":59},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[378,379,380,242,215,381,382,383,384,385,386,313,317,387,388,389,390,391,392,393],"continuous llm red teaming with promptfoo","testing","agentic","merge","owasp agentic","owasp llm","ci","reporting","compliance","llm-red-teaming","promptfoo","deepteam","ci-cd","owasp-llm-top10","jailbreak","regression-testing",{"skillNo":395,"name":396,"nameZh":13,"description":397,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":398,"categories":399,"keywords":401,"publishedAt":232},"01M6AE6HKSF64WW4NFR9ZYHNJ0","containing-active-breach","Executes containment strategies to stop active adversary operations and prevent lateral movement during a confirmed security breach. Implements short-term and long-term containment using network segmentation, endpoint isolation, credential revocation, and access control modifications. Activates for requests involving breach containment, lateral movement prevention, network isolation, active threat containment, or live incident response.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fcontaining-active-breach\u002FSKILL.md",[400],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[402,242,215,265,275,358,403,404,359,405,406,407,408],"containing active breach","containment","lateral-movement","breach-containment","network-isolation","credential-revocation","live-response",{"skillNo":410,"name":411,"nameZh":13,"description":412,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":413,"categories":414,"keywords":416,"publishedAt":232},"01M6AE6DSR92HHAN29D3PP8SC6","configuring-zscaler-private-access-for-ztna","Configures Zscaler Private Access (ZPA) to replace traditional VPN with zero trust network access by deploying App Connectors, defining application segments, configuring identity- and device-posture-based access policies, and integrating with IdPs. Use when replacing VPN concentrators with ZTNA or providing remote users secure access to internal applications without network-level connectivity.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fconfiguring-zscaler-private-access-for-ztna\u002FSKILL.md",[415],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[417,418,419,215,420,421,422,423,244,226,358,424,425,426,427,428,429,430],"ztna","configuring zscaler private access for ztna","policy","architecture","identity","connectors","secure","zero-trust","device-posture","zscaler","zpa","app-connector","access-policy","sase",{"skillNo":432,"name":433,"nameZh":13,"description":434,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":435,"categories":436,"keywords":438,"publishedAt":232},"01M6AE69YDAPNADC06YEJEQ2GY","configuring-windows-event-logging-for-detection","Configures Windows Event Logging with advanced audit policies to generate high-fidelity security events for threat detection and forensic investigation. Use when enabling audit policies for logon events, process creation, privilege use, and object access to feed SIEM detection rules. Activates for requests involving Windows audit policy, event log configuration, security logging, or detection-oriented logging.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fconfiguring-windows-event-logging-for-detection\u002FSKILL.md",[437],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[243,439,440,242,419,215,357,244,219,221,441,276,442,443,359,444,445,446],"logging","configuring windows event logging for detection","engineering","endpoint-security","detection-engineering","windows-security","event-logging","audit-policy",{"skillNo":448,"name":449,"nameZh":13,"description":450,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":451,"categories":452,"keywords":454,"publishedAt":232},"01M6AE6645JZKG919QE1EFKWG0","configuring-windows-defender-advanced-settings","Configures Microsoft Defender for Endpoint (MDE) advanced protection settings including attack surface reduction rules, controlled folder access, network protection, and exploit protection. Use when hardening Windows endpoints beyond default Defender settings, deploying enterprise-grade endpoint protection, or meeting compliance requirements for advanced malware defense. Activates for requests involving Windows Defender configuration, ASR rules, MDE tuning, or Microsoft endpoint security.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fconfiguring-windows-defender-advanced-settings\u002FSKILL.md",[453],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[243,217,455,242,215,104,244,386,262,456,358,276,442,457,359,444,458,459,460,461],"configuring windows defender advanced settings","Enterprise","hardening","Microsoft-Defender","ASR","exploit-protection","MDE",{"skillNo":463,"name":464,"nameZh":13,"description":465,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":466,"categories":467,"keywords":470,"publishedAt":232},"01M6AE62KYYEC3ZCMXPRS234HD","configuring-tls-1-3-for-secure-communications","Configures TLS 1.3 (RFC 8446) on servers, covering cipher suite and key-exchange group selection, and validates the resulting configuration with openssl s_client and testssl.sh. Use when deploying or hardening TLS 1.3 for secure communications, or when testing a server for common TLS misconfigurations and vulnerabilities.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fconfiguring-tls-1-3-for-secure-communications\u002FSKILL.md",[468,469],{"categoryNo":371,"categoryName":372,"taxonomyType":58,"taxonomyTypeDesc":59},{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[423,471,379,242,215,472,244,473,474,358,475,457,476,477,478,479],"configuring tls 1 3 for secure communications","vulnerabilities","server","ssl","network-security","cryptography","openssl","tls","transport-security",{"skillNo":481,"name":482,"nameZh":13,"description":483,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":484,"categories":485,"keywords":487,"publishedAt":232},"01M6AE5Z9Y6ZBF50K7BY6Z483H","configuring-suricata-for-network-monitoring","Deploys and configures Suricata IDS\u002FIPS with Emerging Threats rulesets, EVE JSON logging, and custom rules for high-throughput, protocol-aware traffic inspection (HTTP, TLS, DNS, SMB) and SIEM integration. Use when running Suricata in IDS or inline IPS mode to detect or block malicious traffic, or when combining signature-based and protocol anomaly detection with file extraction.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fconfiguring-suricata-for-network-monitoring\u002FSKILL.md",[486],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[488,358,489,291,242,215,357,490,244,491,492,269,493,494,495,475,247,496,497,498],"monitoring","configuring suricata for network monitoring","http","protocol","extraction","integration","eve","dns","suricata","ips","network-monitoring",{"skillNo":500,"name":501,"nameZh":13,"description":502,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":503,"categories":504,"keywords":510,"publishedAt":232},"01M6AE5VNT2QTNSJK7YQX3FN5M","configuring-snort-ids-for-intrusion-detection","Installs, configures, and tunes Snort 3 to monitor network traffic for malicious activity using custom and community rulesets, preprocessors, and alert output plugins. Use when deploying network-based intrusion detection at key boundaries, writing custom Snort rules, tuning rulesets to reduce false positives, or integrating Snort alerts with a SIEM.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fconfiguring-snort-ids-for-intrusion-detection\u002FSKILL.md",[505,508,509],{"categoryNo":506,"categoryName":507,"taxonomyType":58,"taxonomyTypeDesc":59},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},{"categoryNo":30,"categoryName":31,"taxonomyType":6,"taxonomyTypeDesc":7},[511,512,291,242,215,357,244,513,514,515,358,475,516,247,517],"configuring snort ids for intrusion detection","writing","monitor","plugins","intrusion-detection","snort","rule-writing",{"skillNo":519,"name":520,"nameZh":13,"description":521,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":522,"categories":523,"keywords":525,"publishedAt":232},"01M6AE5R539HD08CV3AW33SC0T","configuring-pfsense-firewall-rules","Configures pfSense firewall rules, NAT policies, IPsec\u002FOpenVPN tunnels, and traffic shaping to enforce network segmentation and control traffic between zones such as DMZ, internal, guest, and IoT. Use when deploying a pfSense perimeter or internal firewall, setting up port-forwarding NAT, configuring site-to-site or remote-access VPNs, or applying QoS\u002Fbandwidth policies.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fconfiguring-pfsense-firewall-rules\u002FSKILL.md",[524],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[526,242,215,244,527,358,475,528,529,530,531],"configuring pfsense firewall rules","iot","network-segmentation","pfsense","firewall","nat",{"skillNo":533,"name":534,"nameZh":13,"description":535,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":536,"categories":537,"keywords":543,"publishedAt":232},"01M6AE5M7GQH1VA5WMQ2G2KPB6","configuring-oauth2-authorization-flow","Configures secure OAuth 2.0 authorization flows, including Authorization Code with PKCE, Client Credentials, and Device Authorization Grant, covering flow selection, PKCE implementation, token lifecycle management, and scope design per OAuth 2.1. Use when implementing or hardening OAuth 2.0 authentication\u002Fauthorization for web, mobile, SPA, or machine-to-machine clients.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fconfiguring-oauth2-authorization-flow\u002FSKILL.md",[538,541,542],{"categoryNo":539,"categoryName":540,"taxonomyType":58,"taxonomyTypeDesc":59},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},{"categoryNo":5,"categoryName":8,"taxonomyType":6,"taxonomyTypeDesc":7},[295,544,545,215,292,421,423,244,220,546,547,548,229,457,549,550,551,552],"configuring oauth2 authorization flow","design","authentication","OAuth","access-control","authorization","oauth2","oidc","pkce",{"skillNo":554,"name":555,"nameZh":13,"description":556,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":557,"categories":558,"keywords":560,"publishedAt":232},"01M6AE5GS2EQ0AC2V17V9SJ1DS","configuring-network-segmentation-with-vlans","Designs and implements VLAN-based (802.1Q) network segmentation on managed switches to isolate zones such as corporate, servers, DMZ, guest, and IoT, and to limit lateral movement paths. Use when segmenting an enterprise network into isolated security zones, meeting compliance mandates (PCI-DSS, HIPAA, SOC 2) for network isolation, or reducing blast radius from a security incident.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fconfiguring-network-segmentation-with-vlans\u002FSKILL.md",[559],{"categoryNo":259,"categoryName":260,"taxonomyType":58,"taxonomyTypeDesc":59},[358,561,242,215,244,562,527,386,225,563,456,475,564,528,565,566],"configuring network segmentation with vlans","blast radius","hipaa","vlan","switch-security","802.1q",118,18]