[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7D6ATRDF9CDHZWNDP8VJ17Y":3,"skill-same:01M7D6ATRDF9CDHZWNDP8VJ17Y":82},{"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":16,"sourceHtmlUrl":17,"categories":18,"keywords":19,"publishedAt":20,"linkOnly":21,"markdownContent":22,"markdownBody":23,"frontMatter":24,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":46,"repositoryHtmlUrl":47,"repositoryHomepageUrl":6,"ownerHtmlUrl":48,"ownerBlogUrl":49,"ownerDescription":50,"updatedAt":51,"install":52,"resources":65},"01M7D6ATRDF9CDHZWNDP8VJ17Y","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.","SaiVatsal\u002FSkills-I-Use","SaiVatsal","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F242597752?v=4","01M7D5YM1T4VXW9203M0GFAHZ1","SaiVatsalPolimera","01M7D5YM2D61ST39XVR2V7B7ZJ",3,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002FAnthropic-Cybersecurity-Skills-main\u002Fskills\u002Fanalyzing-heap-spray-exploitation\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002FAnthropic-Cybersecurity-Skills-main\u002Fskills\u002Fanalyzing-heap-spray-exploitation\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: analyzing-heap-spray-exploitation\ndescription: Detect and analyze heap spray attacks in memory dumps using Volatility3\n  plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large\n  allocations in process virtual address space.\ndomain: cybersecurity\nsubdomain: malware-analysis\ntags:\n- malware-analysis\n- memory-forensics\n- heap-spray\n- volatility3\n- exploit-analysis\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nnist_csf:\n- DE.AE-02\n- RS.AN-03\n- ID.RA-01\n- DE.CM-01\nmitre_attack:\n- T1203\n- T1059.007\n- T1106\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":25,"author":31,"domain":32,"license":15,"version":33,"nist_csf":34,"subdomain":26,"description":7,"mitre_attack":39},[26,27,28,29,30],"malware-analysis","memory-forensics","heap-spray","volatility3","exploit-analysis","mahipal","cybersecurity","1.0",[35,36,37,38],"DE.AE-02","RS.AN-03","ID.RA-01","DE.CM-01",[40,41,42],"T1203","T1059.007","T1106","main","8a3b3de73262a4c4db64523949360f3c599c2fb1","Anthropic-Cybersecurity-Skills-main\u002Fskills\u002Fanalyzing-heap-spray-exploitation",0,"https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use","https:\u002F\u002Fgithub.com\u002FSaiVatsal","https:\u002F\u002Fsaivatsal.github.io\u002FPortfolio\u002F","The Longer It Takes The Stronger It Becomes ","2026-09-21 22:45:58",{"source":8,"skillName":5,"commands":53,"prompt":63,"zipAvailable":64},[54,57,60],{"tool":55,"command":56},"npx","npx skills add SaiVatsal\u002FSkills-I-Use --skill analyzing-heap-spray-exploitation",{"tool":58,"command":59},"bunx","bunx skills add SaiVatsal\u002FSkills-I-Use --skill analyzing-heap-spray-exploitation",{"tool":61,"command":62},"pnpm","pnpm dlx skills add SaiVatsal\u002FSkills-I-Use --skill analyzing-heap-spray-exploitation","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002FAnthropic-Cybersecurity-Skills-main\u002Fskills\u002Fanalyzing-heap-spray-exploitation\u002FSKILL.md",true,[66,70,76],{"path":67,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":16},"LICENSE","许可证",11255,{"path":71,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":74,"sourceHtmlUrl":75},"references\u002Fapi-reference.md","REFERENCE","参考文档",2220,"https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002FAnthropic-Cybersecurity-Skills-main\u002Fskills\u002Fanalyzing-heap-spray-exploitation\u002Freferences\u002Fapi-reference.md",{"path":77,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":80,"sourceHtmlUrl":81},"scripts\u002Fagent.py","SCRIPT","脚本",8294,"https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002FAnthropic-Cybersecurity-Skills-main\u002Fskills\u002Fanalyzing-heap-spray-exploitation\u002Fscripts\u002Fagent.py",[83,91,99,108,115,122],{"skillNo":84,"name":85,"nameZh":6,"description":86,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":87,"sourceHtmlUrl":88,"categories":89,"keywords":90,"publishedAt":20},"01M7DJZP6E6KMBQV4CZSDPZEZ8","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002Fwebapp-testing\u002FSKILL.md",[],[],{"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":15,"licenseFileUrl":95,"sourceHtmlUrl":96,"categories":97,"keywords":98,"publishedAt":20},"01M7DJZFTS5TS06K2TV3MDTE67","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002Fweb-artifacts-builder\u002FSKILL.md",[],[],{"skillNo":100,"name":101,"nameZh":6,"description":102,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":103,"licenseFileUrl":104,"sourceHtmlUrl":105,"categories":106,"keywords":107,"publishedAt":20},"01M7DJRK4SRQ908F2TJM6EZ7EV","ui-styling","Create beautiful, accessible user interfaces with shadcn\u002Fui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs. Use when building user interfaces, implementing design systems, creating responsive layouts, adding accessible components (dialogs, dropdowns, forms, tables), customizing themes and colors, implementing dark mode, generating visual designs and posters, or establishing consistent styling patterns across applications.","MIT","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002Fui-ux-pro-max-skill-main\u002Fcli\u002Fassets\u002Fskills\u002Fui-styling\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002Fui-ux-pro-max-skill-main\u002Fcli\u002Fassets\u002Fskills\u002Fui-styling\u002FSKILL.md",[],[],{"skillNo":109,"name":110,"nameZh":6,"description":111,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":103,"licenseFileUrl":6,"sourceHtmlUrl":112,"categories":113,"keywords":114,"publishedAt":20},"01M7DJR902059VEQP23PVM2WA0","design","Comprehensive design skill: brand identity, design tokens, UI styling, logo generation (55 styles, Gemini AI), corporate identity program (50 deliverables, CIP mockups), HTML presentations (Chart.js), banner design (22 styles, social\u002Fads\u002Fweb\u002Fprint), icon design (15 styles, SVG, Gemini 3.1 Pro), social photos (HTML→screenshot, multi-platform). Actions: design logo, create CIP, generate mockups, build slides, design banner, generate icon, create social photos, social media images, brand identity, design system. Platforms: Facebook, Twitter, LinkedIn, YouTube, Instagram, Pinterest, TikTok, Threads, Google Ads.","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002Fui-ux-pro-max-skill-main\u002Fcli\u002Fassets\u002Fskills\u002Fdesign\u002FSKILL.md",[],[],{"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":103,"licenseFileUrl":6,"sourceHtmlUrl":119,"categories":120,"keywords":121,"publishedAt":20},"01M7DJR56QF5N6XYTCPCFHFMNP","design-system","Token architecture, component specifications, and slide generation. Three-layer tokens (primitive→semantic→component), CSS variables, spacing\u002Ftypography scales, component specs, strategic slide creation. Use for design tokens, systematic design, brand-compliant presentations.","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002Fui-ux-pro-max-skill-main\u002Fcli\u002Fassets\u002Fskills\u002Fdesign-system\u002FSKILL.md",[],[],{"skillNo":123,"name":124,"nameZh":6,"description":125,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":103,"licenseFileUrl":6,"sourceHtmlUrl":126,"categories":127,"keywords":128,"publishedAt":20},"01M7DJQXB6M0SFF7NX8J5N01AH","banner-design","Design banners for social media, ads, website heroes, creative assets, and print. Multiple art direction options with AI-generated visuals. Actions: design, create, generate banner. Platforms: Facebook, Twitter\u002FX, LinkedIn, YouTube, Instagram, Google Display, website hero, print. Styles: minimalist, gradient, bold typography, photo-based, illustrated, geometric, retro, glassmorphism, 3D, neon, duotone, editorial, collage. Uses ui-ux-pro-max, frontend-design, ai-artist, ai-multimodal skills.","https:\u002F\u002Fgithub.com\u002FSaiVatsal\u002FSkills-I-Use\u002Fblob\u002Fmain\u002Fui-ux-pro-max-skill-main\u002Fcli\u002Fassets\u002Fskills\u002Fbanner-design\u002FSKILL.md",[],[]]