[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71B46W6W3V92RADE2S7KQVM":3,"skill-same:01M71B46W6W3V92RADE2S7KQVM":68},{"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":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":50,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":53,"updatedAt":54,"install":55,"resources":67},"01M71B46W6W3V92RADE2S7KQVM","cyber-hunting-credential-stuffing-attacks",null,"Detects credential stuffing attacks by analyzing authentication logs for login velocity anomalies, ASN diversity, password spray patterns, and geographic distribution of failed logins. Uses statistical analysis on Splunk or raw log data. Use when investigating account takeover campaigns or building detection rules for auth abuse.","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-hunting-credential-stuffing-attacks\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"hunting credential stuffing attacks","hunting","stuffing","cyber hunting credential stuffing attacks","credential","attacks","Rules","false","cybersecurity","use","true","diversity","authentication","takeover","for","account takeover","auth","domain","campaigns","distribution","2026-11-10 10:12:30",false,"---\nname: cyber-hunting-credential-stuffing-attacks\ndescription: \"Detects credential stuffing attacks by analyzing authentication logs for login velocity anomalies, ASN diversity, password spray patterns, and geographic distribution of failed logins. Uses statistical analysis on Splunk or raw log data. Use when investigating account takeover campaigns or building detection rules for auth abuse.\"\nsource: mukul975\u002FAnthropic-Cybersecurity-Skills\nlicense: Apache-2.0\nauthorized_lab: false\norigin_frontmatter: \"name: hunting-credential-stuffing-attacks | description: 'Detects credential stuffing attacks by analyzing authentication logs |   for login velocity anomalies, ASN diversity, password spray patterns, and geographic |   distribution of failed logins. Uses statistical analysis on Splunk or raw log data. |   Use when investigating account takeover campaigns or building detection rules for |   auth abuse. |  |   ' | domain: cybersecurity | subdomain: security-operations | tags: | - credential-stuff\"\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# Hunting Credential Stuffing Attacks\n\n\n## When to Use\n\n- When investigating security incidents that require hunting credential stuffing attacks\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 security operations 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\nAnalyze authentication logs to detect credential stuffing by identifying patterns\nof distributed login failures, high IP diversity, and suspicious ASN distribution.\n\n```python\nimport pandas as pd\nfrom collections import Counter\n\n# Load auth logs\ndf = pd.read_csv(\"auth_logs.csv\", parse_dates=[\"timestamp\"])\n\n# Credential stuffing indicator: many IPs trying few accounts\nip_per_account = df[df[\"status\"] == \"failed\"].groupby(\"username\")[\"source_ip\"].nunique()\naccounts_under_attack = ip_per_account[ip_per_account > 50]\n```\n\nKey detection indicators:\n1. High unique source IPs per failed username\n2. Low success rate across many accounts (\u003C 1%)\n3. ASN concentration from cloud\u002Fproxy providers\n4. Geographic impossibility (same account, distant locations)\n5. User-agent uniformity across distributed IPs\n\n## Examples\n\n```python\n# Password spray: one password tried across many accounts\nspray = df[df[\"status\"] == \"failed\"].groupby([\"source_ip\", \"password_hash\"]).agg(\n    accounts=(\"username\", \"nunique\")).reset_index()\nsprays = spray[spray[\"accounts\"] > 10]\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# Hunting Credential Stuffing Attacks\n\n\n## When to Use\n\n- When investigating security incidents that require hunting credential stuffing attacks\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 security operations 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\nAnalyze authentication logs to detect credential stuffing by identifying patterns\nof distributed login failures, high IP diversity, and suspicious ASN distribution.\n\n```python\nimport pandas as pd\nfrom collections import Counter\n\n# Load auth logs\ndf = pd.read_csv(\"auth_logs.csv\", parse_dates=[\"timestamp\"])\n\n# Credential stuffing indicator: many IPs trying few accounts\nip_per_account = df[df[\"status\"] == \"failed\"].groupby(\"username\")[\"source_ip\"].nunique()\naccounts_under_attack = ip_per_account[ip_per_account > 50]\n```\n\nKey detection indicators:\n1. High unique source IPs per failed username\n2. Low success rate across many accounts (\u003C 1%)\n3. ASN concentration from cloud\u002Fproxy providers\n4. Geographic impossibility (same account, distant locations)\n5. User-agent uniformity across distributed IPs\n\n## Examples\n\n```python\n# Password spray: one password tried across many accounts\nspray = df[df[\"status\"] == \"failed\"].groupby([\"source_ip\", \"password_hash\"]).agg(\n    accounts=(\"username\", \"nunique\")).reset_index()\nsprays = spray[spray[\"accounts\"] > 10]\n```\n",{"hide":44,"name":5,"source":45,"license":15,"description":7,"authorized_lab":40,"origin_frontmatter":46},true,"mukul975\u002FAnthropic-Cybersecurity-Skills","name: hunting-credential-stuffing-attacks | description: 'Detects credential stuffing attacks by analyzing authentication logs |   for login velocity anomalies, ASN diversity, password spray patterns, and geographic |   distribution of failed logins. Uses statistical analysis on Splunk or raw log data. |   Use when investigating account takeover campaigns or building detection rules for |   auth abuse. |  |   ' | domain: cybersecurity | subdomain: security-operations | tags: | - credential-stuff","main","4c6d8d65f3d6096e2fc25b0845e481dda73c2794",".claude\u002Fskills\u002Fcyber-hunting-credential-stuffing-attacks",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":56,"prompt":66,"zipAvailable":44},[57,60,63],{"tool":58,"command":59},"npx","npx skills add nexuslinkproductions\u002Fyuri-os --skill cyber-hunting-credential-stuffing-attacks",{"tool":61,"command":62},"bunx","bunx skills add nexuslinkproductions\u002Fyuri-os --skill cyber-hunting-credential-stuffing-attacks",{"tool":64,"command":65},"pnpm","pnpm dlx skills add nexuslinkproductions\u002Fyuri-os --skill cyber-hunting-credential-stuffing-attacks","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fcyber-hunting-credential-stuffing-attacks\u002FSKILL.md",[],[69,91,114,144,173,192],{"skillNo":70,"name":71,"nameZh":6,"description":72,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":74,"categories":75,"keywords":76,"publishedAt":39},"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",[],[77,78,79,80,81,82,83,29,84,28,85,86,87,88,89,90],"zoom out","zoom","with","harness","how","section","re","understand","perspective","when","you","code","it","context",{"skillNo":92,"name":93,"nameZh":6,"description":94,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":39},"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",[],[98,99,80,100,101,33,102,103,104,105,106,28,107,86,108,109,110,111,112,113],"yuri shura","parallel","architecture review","planning","deployment","vector","strategic review","decision","strategic","ops","workflow","decisions","architecture","review","perspectives","adversarial",{"skillNo":115,"name":116,"nameZh":6,"description":117,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":118,"categories":119,"keywords":125,"publishedAt":39},"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",[120],{"categoryNo":121,"categoryName":122,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000005","邮件与沟通","SCENARIO","使用场景",[126,127,128,129,130,131,132,133,134,86,135,136,137,138,139,140,141,33,142,143],"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":145,"name":146,"nameZh":6,"description":147,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":148,"categories":149,"keywords":158,"publishedAt":39},"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",[150,153],{"categoryNo":151,"categoryName":152,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":154,"categoryName":155,"taxonomyType":156,"taxonomyTypeDesc":157},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[159,88,160,126,80,161,162,163,33,164,165,166,167,168,169,170,171,172,28,86],"yuri code intelligence","code intelligence","reviews","code quality","feature","performance","code review","long","up","issues","clean","techniques","improve","design",{"skillNo":174,"name":175,"nameZh":6,"description":176,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":177,"categories":178,"keywords":179,"publishedAt":39},"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",[],[180,181,182,183,184,185,186,187,188,86,189,108,190,191],"yuri adw","run","engineering loop","software factory","software","agentic engineering","factory","loop","invoke","engineering","agentic","user",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":196,"categories":197,"keywords":210,"publishedAt":39},"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",[198,201,204,207],{"categoryNo":199,"categoryName":200,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":202,"categoryName":203,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":205,"categoryName":206,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":208,"categoryName":209,"taxonomyType":156,"taxonomyTypeDesc":157},"01JBSEEDCAT000000000000036","内容创作者",[211,212,213,86,108,214,80,215,102,28,216],"writing","writing skills","new","work","editing","Existing"]