[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ER52GCQJ07C1R46239WJ4A":3,"skill-same:01M6ER52GCQJ07C1R46239WJ4A":86},{"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":68},"01M6ER52GCQJ07C1R46239WJ4A","analyzing-heap-spray-exploitation",null,"Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.","luokai0\u002Fai-agent-skills-by-luo-kai","luokai0","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F266954973?v=4","01M6E16VNT42JB8B3X3254QWJ7","luo kai","01M6E16VTFVP6S5XJF1V1MPV90",14,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F21-external-registries\u002F08-pinkpixel-collection\u002Fanalyzing-heap-spray-exploitation\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"analyzing heap spray exploitation","analyzing","exploitation","detect","suspicious","exploit","process","landing","virtual","analyze","in memory","analysis","exploit-analysis","volatility3","heap-spray","memory-forensics","malware-analysis","plugins","cybersecurity","memory","2026-11-10 10:12:30",false,"---\nname: analyzing-heap-spray-exploitation\ndescription: Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.\ndomain: cybersecurity\nsubdomain: malware-analysis\ntags: [malware-analysis, memory-forensics, heap-spray, volatility3, exploit-analysis]\nversion: \"1.0\"\nauthor: mahipal\nlicense: Apache-2.0\n---\n# Analyzing Heap Spray Exploitation\n\n## Overview\n\nHeap spraying is an exploitation technique that fills large regions of a process's heap with attacker-controlled data (typically NOP sleds followed by shellcode) to increase the reliability of code execution exploits. This skill covers detecting heap spray artifacts in memory dumps using Volatility3's malfind, vadinfo, and memmap plugins, identifying suspicious contiguous memory allocations, scanning for NOP sled patterns (0x90, 0x0c0c0c0c), and extracting embedded shellcode for analysis.\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing heap spray exploitation\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 `volatility3` framework installed\n- Memory dump file (.raw, .vmem, .dmp format)\n- Understanding of virtual memory layout and VAD (Virtual Address Descriptor) trees\n- Familiarity with common shellcode patterns and NOP sled encodings\n\n## Steps\n\n### Step 1: Identify Suspicious Processes\nUse Volatility3 windows.malfind to scan for processes with executable injected memory regions.\n\n### Step 2: Analyze VAD Entries\nExamine VAD tree entries using windows.vadinfo for large contiguous allocations with RWX permissions.\n\n### Step 3: Scan for NOP Sled Patterns\nSearch suspicious memory regions for NOP sled signatures (0x90 sequences, 0x0c0c0c0c patterns).\n\n### Step 4: Extract and Analyze Shellcode\nDump suspicious memory regions and identify shellcode using byte pattern analysis.\n\n## Expected Output\n\nJSON report with suspicious processes, heap spray indicators, NOP sled locations, memory region sizes, and extracted shellcode hashes.\n","# Analyzing Heap Spray Exploitation\n\n## Overview\n\nHeap spraying is an exploitation technique that fills large regions of a process's heap with attacker-controlled data (typically NOP sleds followed by shellcode) to increase the reliability of code execution exploits. This skill covers detecting heap spray artifacts in memory dumps using Volatility3's malfind, vadinfo, and memmap plugins, identifying suspicious contiguous memory allocations, scanning for NOP sled patterns (0x90, 0x0c0c0c0c), and extracting embedded shellcode for analysis.\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing heap spray exploitation\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 `volatility3` framework installed\n- Memory dump file (.raw, .vmem, .dmp format)\n- Understanding of virtual memory layout and VAD (Virtual Address Descriptor) trees\n- Familiarity with common shellcode patterns and NOP sled encodings\n\n## Steps\n\n### Step 1: Identify Suspicious Processes\nUse Volatility3 windows.malfind to scan for processes with executable injected memory regions.\n\n### Step 2: Analyze VAD Entries\nExamine VAD tree entries using windows.vadinfo for large contiguous allocations with RWX permissions.\n\n### Step 3: Scan for NOP Sled Patterns\nSearch suspicious memory regions for NOP sled signatures (0x90 sequences, 0x0c0c0c0c patterns).\n\n### Step 4: Extract and Analyze Shellcode\nDump suspicious memory regions and identify shellcode using byte pattern analysis.\n\n## Expected Output\n\nJSON report with suspicious processes, heap spray indicators, NOP sled locations, memory region sizes, and extracted shellcode hashes.\n",{"name":5,"tags":44,"author":45,"domain":37,"license":15,"version":46,"subdomain":35,"description":7},[35,34,33,32,31],"mahipal","1.0","main","4d2fb89cdfb75f3f6fd3c6c5ec9ad90ea129eb3c","ai-agent-skills\u002F21-external-registries\u002F08-pinkpixel-collection\u002Fanalyzing-heap-spray-exploitation",2,"https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai","https:\u002F\u002Fgithub.com\u002Fluokai0","a solo builder.","2026-05-06 04:29:04",{"source":8,"skillName":5,"commands":56,"prompt":66,"zipAvailable":67},[57,60,63],{"tool":58,"command":59},"npx","npx skills add luokai0\u002Fai-agent-skills-by-luo-kai --skill analyzing-heap-spray-exploitation",{"tool":61,"command":62},"bunx","bunx skills add luokai0\u002Fai-agent-skills-by-luo-kai --skill analyzing-heap-spray-exploitation",{"tool":64,"command":65},"pnpm","pnpm dlx skills add luokai0\u002Fai-agent-skills-by-luo-kai --skill analyzing-heap-spray-exploitation","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F21-external-registries\u002F08-pinkpixel-collection\u002Fanalyzing-heap-spray-exploitation\u002FSKILL.md",true,[69,74,80],{"path":70,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":72,"sourceHtmlUrl":73},"LICENSE","许可证",11255,"https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F21-external-registries\u002F08-pinkpixel-collection\u002Fanalyzing-heap-spray-exploitation\u002FLICENSE",{"path":75,"resourceType":76,"resourceTypeDesc":77,"sizeBytes":78,"sourceHtmlUrl":79},"references\u002Fapi-reference.md","REFERENCE","参考文档",2220,"https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F21-external-registries\u002F08-pinkpixel-collection\u002Fanalyzing-heap-spray-exploitation\u002Freferences\u002Fapi-reference.md",{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":84,"sourceHtmlUrl":85},"scripts\u002Fagent.py","SCRIPT","脚本",8294,"https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F21-external-registries\u002F08-pinkpixel-collection\u002Fanalyzing-heap-spray-exploitation\u002Fscripts\u002Fagent.py",[87,115,132,162,195,232],{"skillNo":88,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":91,"licenseFileUrl":6,"sourceHtmlUrl":92,"categories":93,"keywords":94,"publishedAt":39},"01M6F2SKTE208174C7S7JJCZC7","write-contracts","Generates secure Aptos Move V2 smart contracts with Object model, Digital Asset integration, security patterns, and storage type guidance. Includes comprehensive storage decision framework for optimal data structure selection. Triggers on: 'write contract', 'create NFT collection', 'build marketplace', 'implement minting', 'generate Move module', 'create token contract', 'build DAO', 'implement staking'. Ask storage questions when: 'store', 'track', 'registry', 'mapping', 'list', 'collection'.","MIT","https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F22-clawhub-skills\u002Fwrite-contracts\u002FSKILL.md",[],[95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114],"write","contracts","write contracts","storage","secure","create","generate","collection","model","decision","ask","smart-contracts","selection","objects","structure","nft","token","aptos","critical","move",{"skillNo":116,"name":117,"nameZh":6,"description":118,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":91,"licenseFileUrl":6,"sourceHtmlUrl":119,"categories":120,"keywords":121,"publishedAt":39},"01M6F2RFXJ6T9MKW0A7N7GM45B","web-search","通用网络搜索技能，支持多引擎搜索（百度、必应、DuckDuckGo），无需API密钥即可获取实时信息","https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F22-clawhub-skills\u002Fweb-search-ex-skill\u002FSKILL.md",[],[122,123,124,125,126,127,128,129,130,131],"web","search","web search","搜索","baidu","bing","duckduckgo","百度","多引擎","internet",{"skillNo":133,"name":134,"nameZh":6,"description":135,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":91,"licenseFileUrl":6,"sourceHtmlUrl":136,"categories":137,"keywords":143,"publishedAt":39},"01M6F2K968G1FZEZFPW2E6B222","solo-build","Execute implementation plan tasks with TDD workflow, auto-commit, and phase gates. 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Do NOT use for planning (use \u002Fplan) or scaffolding (use \u002Fscaffold).","https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F22-clawhub-skills\u002Fsolo-build\u002FSKILL.md",[138],{"categoryNo":139,"categoryName":140,"taxonomyType":141,"taxonomyTypeDesc":142},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[144,145,146,147,148,149,150,151,123,152,153,154,95,155,156,157,158,159,160,161],"build","solo","solo build","MCP","workflow","commit","tasks","code","Bash","plan","read","auto","references","context7","query","scaffolding","ship it","project",{"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":91,"licenseFileUrl":6,"sourceHtmlUrl":166,"categories":167,"keywords":174,"publishedAt":39},"01M6F2GKN39SGHSPWYB3662YC8","react-email","Use when building HTML email templates with React components, adding a visual email editor to an application using the React Email visual editor, rendering emails to HTML, or sending emails with Resend. Covers welcome emails, password resets, notifications, order confirmations, newsletters, transactional emails, and the embeddable email editor component.","https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F22-clawhub-skills\u002Freact-email-skills\u002FSKILL.md",[168,171],{"categoryNo":169,"categoryName":170,"taxonomyType":141,"taxonomyTypeDesc":142},"01JBSEEDCAT000000000000005","邮件与沟通",{"categoryNo":172,"categoryName":173,"taxonomyType":141,"taxonomyTypeDesc":142},"01JBSEEDCAT000000000000009","前端开发",[175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194],"react","email","react email","github","editor","components","react components","component","welcome","https","notifications","password","node","use","html","resend","visual","emails","rendering","with",{"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":91,"licenseFileUrl":6,"sourceHtmlUrl":199,"categories":200,"keywords":213,"publishedAt":39},"01M6F2FBVGVDFSG8SSFJGXA40C","APITester Agent-Driven API Testing","Test API endpoints and document responses. Define tests in plain English, run them, get formatted results. Agent-driven Postman alternative.","https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F22-clawhub-skills\u002Fopenclaw-api-tester\u002FSKILL.md",[201,204,207,208],{"categoryNo":202,"categoryName":203,"taxonomyType":141,"taxonomyTypeDesc":142},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":205,"categoryName":206,"taxonomyType":141,"taxonomyTypeDesc":142},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":139,"categoryName":140,"taxonomyType":141,"taxonomyTypeDesc":142},{"categoryNo":209,"categoryName":210,"taxonomyType":211,"taxonomyTypeDesc":212},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231],"testing","api","api testing","driven","APITester Agent Driven API Testing","test","run","postman","results","plain english","tester","endpoints","document","get","define","tests","english","api-tester",{"skillNo":233,"name":234,"nameZh":6,"description":235,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":91,"licenseFileUrl":6,"sourceHtmlUrl":236,"categories":237,"keywords":238,"publishedAt":39},"01M6F273Y3NGAPVJZ608BC0G9G","hubspot-implementation-plan","Generate a phased implementation plan from a HubSpot audit report. Creates prioritized, sequenced cleanup processes with effort estimates, dependencies, and automation feasibility. Use after running \u002Fhubspot-audit.","https:\u002F\u002Fgithub.com\u002Fluokai0\u002Fai-agent-skills-by-luo-kai\u002Fblob\u002Fmain\u002Fai-agent-skills\u002F22-clawhub-skills\u002Fhubspot-implementation-plan\u002FSKILL.md",[],[153,239,240,241,242,243,244,101,245,246,247,248,249,188,250,251,194,252],"implementation","hubspot","hubspot implementation plan","automation","feasibility","cleanup","planning","report","audit","audit report","phased implementation","dependencies","processes","hubspot audit"]