[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71AEYQ2HVG6NK7DTC8GAY4Y":3,"skill-same:01M71AEYQ2HVG6NK7DTC8GAY4Y":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},"01M71AEYQ2HVG6NK7DTC8GAY4Y","cyber-analyzing-cobaltstrike-malleable-c2-profiles",null,"Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate network detection signatures.","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-cobaltstrike-malleable-c2-profiles\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"analyzing","profiles","c2","analyzing cobaltstrike malleable c2 profiles","cyber analyzing cobaltstrike malleable c2 profiles","malware","network","strike","threat-hunting","generate","hunting","subdomain","analyze","team","analysis","false","cybersecurity","detection signatures","signatures","parse","2026-11-10 10:12:30",false,"---\nname: cyber-analyzing-cobaltstrike-malleable-c2-profiles\ndescription: \"Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate network detection signatures.\"\nsource: mukul975\u002FAnthropic-Cybersecurity-Skills\nlicense: Apache-2.0\nauthorized_lab: false\norigin_frontmatter: \"name: analyzing-cobaltstrike-malleable-c2-profiles | description: Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike |   and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate |   network detection signatures. | domain: cybersecurity | subdomain: malware-analysis | tags: | - cobalt-strike | - malleable-c2 | - c2-detection | - beacon-analysis | - network-signatures | - threat-hunting | - red-team-tools | version: '1.0' | author: mahipal |\"\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 CobaltStrike Malleable C2 Profiles\n\n## Overview\n\nCobalt Strike Malleable C2 profiles are domain-specific language scripts that customize how Beacon communicates with the team server, defining HTTP request\u002Fresponse transformations, sleep intervals, jitter values, user agents, URI paths, and process injection behavior. Threat actors use malleable profiles to disguise C2 traffic as legitimate services (Amazon, Google, Slack). Analyzing these profiles reveals network indicators for detection: URI patterns, HTTP headers, POST\u002FGET transforms, DNS settings, and process injection techniques. The `dissect.cobaltstrike` library can parse both profile files and extract configurations from beacon payloads, while `pyMalleableC2` provides AST-based parsing using Lark grammar for programmatic profile manipulation and validation.\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing cobaltstrike malleable c2 profiles\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 `dissect.cobaltstrike` and\u002For `pyMalleableC2`\n- Sample Malleable C2 profiles (available from public repositories)\n- Understanding of HTTP protocol and Cobalt Strike beacon communication model\n- Network monitoring tools (Suricata\u002FSnort) for signature deployment\n- PCAP analysis tools for traffic validation\n\n## Steps\n\n1. Install libraries: `pip install dissect.cobaltstrike` or `pip install pyMalleableC2`\n2. Parse profile with `C2Profile.from_path(\"profile.profile\")`\n3. Extract HTTP GET\u002FPOST block configurations (URIs, headers, parameters)\n4. Identify user agent strings and spoof targets\n5. Extract sleep time, jitter percentage, and DNS beacon settings\n6. Analyze process injection settings (spawn-to, allocation technique)\n7. Generate Suricata\u002FSnort signatures from extracted network indicators\n8. Compare profile against known threat actor profile collections\n9. Extract staging URIs and payload delivery mechanisms\n10. Produce detection report with IOCs and recommended network signatures\n\n## Expected Output\n\nA JSON report containing extracted C2 URIs, HTTP headers, user agents, sleep\u002Fjitter settings, process injection config, spawned process paths, DNS settings, and generated Suricata-compatible detection rules.\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 CobaltStrike Malleable C2 Profiles\n\n## Overview\n\nCobalt Strike Malleable C2 profiles are domain-specific language scripts that customize how Beacon communicates with the team server, defining HTTP request\u002Fresponse transformations, sleep intervals, jitter values, user agents, URI paths, and process injection behavior. Threat actors use malleable profiles to disguise C2 traffic as legitimate services (Amazon, Google, Slack). Analyzing these profiles reveals network indicators for detection: URI patterns, HTTP headers, POST\u002FGET transforms, DNS settings, and process injection techniques. The `dissect.cobaltstrike` library can parse both profile files and extract configurations from beacon payloads, while `pyMalleableC2` provides AST-based parsing using Lark grammar for programmatic profile manipulation and validation.\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing cobaltstrike malleable c2 profiles\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 `dissect.cobaltstrike` and\u002For `pyMalleableC2`\n- Sample Malleable C2 profiles (available from public repositories)\n- Understanding of HTTP protocol and Cobalt Strike beacon communication model\n- Network monitoring tools (Suricata\u002FSnort) for signature deployment\n- PCAP analysis tools for traffic validation\n\n## Steps\n\n1. Install libraries: `pip install dissect.cobaltstrike` or `pip install pyMalleableC2`\n2. Parse profile with `C2Profile.from_path(\"profile.profile\")`\n3. Extract HTTP GET\u002FPOST block configurations (URIs, headers, parameters)\n4. Identify user agent strings and spoof targets\n5. Extract sleep time, jitter percentage, and DNS beacon settings\n6. Analyze process injection settings (spawn-to, allocation technique)\n7. Generate Suricata\u002FSnort signatures from extracted network indicators\n8. Compare profile against known threat actor profile collections\n9. Extract staging URIs and payload delivery mechanisms\n10. Produce detection report with IOCs and recommended network signatures\n\n## Expected Output\n\nA JSON report containing extracted C2 URIs, HTTP headers, user agents, sleep\u002Fjitter settings, process injection config, spawned process paths, DNS settings, and generated Suricata-compatible detection rules.\n",{"hide":44,"name":5,"source":45,"license":15,"description":7,"authorized_lab":40,"origin_frontmatter":46},true,"mukul975\u002FAnthropic-Cybersecurity-Skills","name: analyzing-cobaltstrike-malleable-c2-profiles | description: Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike |   and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate |   network detection signatures. | domain: cybersecurity | subdomain: malware-analysis | tags: | - cobalt-strike | - malleable-c2 | - c2-detection | - beacon-analysis | - network-signatures | - threat-hunting | - red-team-tools | version: '1.0' | author: mahipal |","main","4c6d8d65f3d6096e2fc25b0845e481dda73c2794",".claude\u002Fskills\u002Fcyber-analyzing-cobaltstrike-malleable-c2-profiles",0,"https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions","Building deterministic AI governance and continuity systems. Workflow architect + visual storyteller","2026-11-14 03:05:17",{"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-analyzing-cobaltstrike-malleable-c2-profiles",{"tool":61,"command":62},"bunx","bunx skills add nexuslinkproductions\u002Fyuri-os --skill cyber-analyzing-cobaltstrike-malleable-c2-profiles",{"tool":64,"command":65},"pnpm","pnpm dlx skills add nexuslinkproductions\u002Fyuri-os --skill cyber-analyzing-cobaltstrike-malleable-c2-profiles","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fcyber-analyzing-cobaltstrike-malleable-c2-profiles\u002FSKILL.md",[],[69,93,117,147,176,195],{"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",[],[77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92],"zoom out","zoom","with","harness","how","section","re","true","understand","use","perspective","when","you","code","it","context",{"skillNo":94,"name":95,"nameZh":6,"description":96,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":99,"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",[],[100,101,80,102,103,104,105,106,107,108,109,86,110,88,111,112,113,114,115,116],"yuri shura","parallel","architecture review","planning","for","deployment","vector","strategic review","decision","strategic","ops","workflow","decisions","architecture","review","perspectives","adversarial",{"skillNo":118,"name":119,"nameZh":6,"description":120,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":121,"categories":122,"keywords":128,"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",[123],{"categoryNo":124,"categoryName":125,"taxonomyType":126,"taxonomyTypeDesc":127},"01JBSEEDCAT000000000000005","邮件与沟通","SCENARIO","使用场景",[129,130,131,132,133,134,135,136,137,88,138,139,140,141,142,143,144,104,145,146],"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":148,"name":149,"nameZh":6,"description":150,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":151,"categories":152,"keywords":161,"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",[153,156],{"categoryNo":154,"categoryName":155,"taxonomyType":126,"taxonomyTypeDesc":127},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":157,"categoryName":158,"taxonomyType":159,"taxonomyTypeDesc":160},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[162,90,163,129,80,164,165,166,104,167,168,169,170,171,172,173,174,175,86,88],"yuri code intelligence","code intelligence","reviews","code quality","feature","performance","code review","long","up","issues","clean","techniques","improve","design",{"skillNo":177,"name":178,"nameZh":6,"description":179,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":180,"categories":181,"keywords":182,"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",[],[183,184,185,186,187,188,189,190,191,88,192,111,193,194],"yuri adw","run","engineering loop","software factory","software","agentic engineering","factory","loop","invoke","engineering","agentic","user",{"skillNo":196,"name":197,"nameZh":6,"description":198,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":73,"licenseFileUrl":6,"sourceHtmlUrl":199,"categories":200,"keywords":213,"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",[201,204,207,210],{"categoryNo":202,"categoryName":203,"taxonomyType":126,"taxonomyTypeDesc":127},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":205,"categoryName":206,"taxonomyType":126,"taxonomyTypeDesc":127},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":208,"categoryName":209,"taxonomyType":126,"taxonomyTypeDesc":127},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":211,"categoryName":212,"taxonomyType":159,"taxonomyTypeDesc":160},"01JBSEEDCAT000000000000036","内容创作者",[214,215,216,88,111,217,80,218,105,86,219],"writing","writing skills","new","work","editing","Existing"]