[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71CVSW7YVSC1KS0HXZB4ZS8":3,"skill-same:01M71CVSW7YVSC1KS0HXZB4ZS8":75},{"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":23,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":14,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":53,"updatedAt":54,"install":55,"resources":68},"01M71CVSW7YVSC1KS0HXZB4ZS8","crypto-blockchain-ethereum",null,"JSON report listing vulnerabilities with SWC (Smart Contract Weakness Classification) identifiers, severity ratings, affected functions, and suggested fixes.","DCx7C5\u002Fai-marketplace","DCx7C5","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42419559?v=4","01M71C01G2AZV3NTNGWAWSHJPP","DC","01M71C01GQW6G50S2BYMS7PP3E",0,"MIT","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fcrypto-blockchain-ethereum\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000037","律师与法务","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"ethereum","crypto blockchain ethereum","blockchain","crypto","ratings","vulnerabilities","report","json","affected","with","functions","listing","smart contract","cybersecurity","swc","contract","classification","fixes","severity","2026-11-10 10:12:30",false,"---\nname: crypto-blockchain-ethereum\ndescription: \"JSON report listing vulnerabilities with SWC (Smart Contract Weakness Classification) identifiers, severity ratings, affected functions, and suggested fixes.\"\ndomain: cybersecurity\n---\n\n# Analyzing Ethereum Smart Contract Vulnerabilities\n\n## Overview\n\nSmart contract vulnerabilities have led to billions of dollars in losses across DeFi protocols. Unlike traditional software, deployed smart contracts are immutable and handle real financial assets, making pre-deployment security analysis critical. Slither performs fast static analysis using an intermediate representation to detect over 90 vulnerability patterns in seconds, while Mythril uses symbolic execution and SMT solving to discover complex execution path vulnerabilities like reentrancy and integer overflows. This skill covers running both tools against Solidity contracts, interpreting results, triaging findings by severity, and generating audit reports.\n\n## When to Use\n\n- When investigating security incidents that require analyzing ethereum smart contract vulnerabilities\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 3.10+ with pip\n- Slither (pip install slither-analyzer) and solc compiler\n- Mythril (pip install mythril) with solc-select for compiler version management\n- Solidity source code or compiled contract bytecode\n- Foundry or Hardhat development framework (optional, for project-level analysis)\n\n## Steps\n\n### Step 1: Run Slither Static Analysis\n\nExecute Slither against the contract codebase to identify vulnerability patterns, optimization opportunities, and code quality issues using its 90+ built-in detectors.\n\n### Step 2: Run Mythril Symbolic Execution\n\nRun Mythril deep analysis to explore execution paths and discover reentrancy, unchecked external calls, and arithmetic vulnerabilities that require path-sensitive analysis.\n\n### Step 3: Triage and Correlate Findings\n\nCombine results from both tools, deduplicate findings, assess severity based on exploitability and financial impact, and filter false positives.\n\n### Step 4: Generate Audit Report\n\nProduce a structured audit report with vulnerability descriptions, affected code locations, exploit scenarios, and remediation recommendations.\n\n## Expected Output\n\nJSON report listing vulnerabilities with SWC (Smart Contract Weakness Classification) identifiers, severity ratings, affected functions, and suggested fixes.\n","# Analyzing Ethereum Smart Contract Vulnerabilities\n\n## Overview\n\nSmart contract vulnerabilities have led to billions of dollars in losses across DeFi protocols. Unlike traditional software, deployed smart contracts are immutable and handle real financial assets, making pre-deployment security analysis critical. Slither performs fast static analysis using an intermediate representation to detect over 90 vulnerability patterns in seconds, while Mythril uses symbolic execution and SMT solving to discover complex execution path vulnerabilities like reentrancy and integer overflows. This skill covers running both tools against Solidity contracts, interpreting results, triaging findings by severity, and generating audit reports.\n\n## When to Use\n\n- When investigating security incidents that require analyzing ethereum smart contract vulnerabilities\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 3.10+ with pip\n- Slither (pip install slither-analyzer) and solc compiler\n- Mythril (pip install mythril) with solc-select for compiler version management\n- Solidity source code or compiled contract bytecode\n- Foundry or Hardhat development framework (optional, for project-level analysis)\n\n## Steps\n\n### Step 1: Run Slither Static Analysis\n\nExecute Slither against the contract codebase to identify vulnerability patterns, optimization opportunities, and code quality issues using its 90+ built-in detectors.\n\n### Step 2: Run Mythril Symbolic Execution\n\nRun Mythril deep analysis to explore execution paths and discover reentrancy, unchecked external calls, and arithmetic vulnerabilities that require path-sensitive analysis.\n\n### Step 3: Triage and Correlate Findings\n\nCombine results from both tools, deduplicate findings, assess severity based on exploitability and financial impact, and filter false positives.\n\n### Step 4: Generate Audit Report\n\nProduce a structured audit report with vulnerability descriptions, affected code locations, exploit scenarios, and remediation recommendations.\n\n## Expected Output\n\nJSON report listing vulnerabilities with SWC (Smart Contract Weakness Classification) identifiers, severity ratings, affected functions, and suggested fixes.\n",{"name":5,"domain":37,"description":7},"main","a91f1293287ffa9f4f1b8f486cd6e835a1568c84","skills\u002Fcrypto-blockchain-ethereum","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace","https:\u002F\u002Fgithub.com\u002FDCx7C5","#Python","2026-09-01 11:21:00",{"source":8,"skillName":5,"commands":56,"prompt":66,"zipAvailable":67},[57,60,63],{"tool":58,"command":59},"npx","npx skills add DCx7C5\u002Fai-marketplace --skill crypto-blockchain-ethereum",{"tool":61,"command":62},"bunx","bunx skills add DCx7C5\u002Fai-marketplace --skill crypto-blockchain-ethereum",{"tool":64,"command":65},"pnpm","pnpm dlx skills add DCx7C5\u002Fai-marketplace --skill crypto-blockchain-ethereum","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fcrypto-blockchain-ethereum\u002FSKILL.md",true,[69],{"path":70,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":73,"sourceHtmlUrl":74},"index.json","REFERENCE","参考文档",634,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fcrypto-blockchain-ethereum\u002Findex.json",[76,101,124,146,168,184],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":82,"publishedAt":43},"01M71HAPZ01KQ30RKTB0FFSQ05","services-wmi-persistence-detect","Detect WMI event subscription persistence by enumerating ActiveScriptEventConsumer, CommandLineEventConsumer, and permanent subscriptions in the WMI repository.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fservices\u002Fwmi\u002Fpersistence\u002Fdetect\u002FSKILL.md",[],[83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,37,100],"services","detect","services wmi persistence detect","wmi","persistence","de","cm","process","activescript","event","subscriptions","commandline-consumer","repository","subscription","event-subscription","t1546.003","forensics","process-forensics",{"skillNo":102,"name":103,"nameZh":6,"description":104,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":107,"publishedAt":43},"01M71HAK6JTTTS229T17WJMMCG","services-wmi-exec-exploit","Perform lateral movement across Windows networks using WMI-based remote execution techniques including Impacket wmiexec.py, CrackMapExec, and native WMI commands for stealthy post-exploitation during red team engagements.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fservices\u002Fwmi\u002Fexec\u002Fexploit\u002FSKILL.md",[],[108,83,109,86,110,111,112,37,113,114,115,116,117,118,88,119,120,121,122,123],"exploit","services wmi exec exploit","exec","remote","traffic","Bash","analysis","team","across","crackmapexec","native","command","lateral movement","read","lateral-movement","Impacket",{"skillNo":125,"name":126,"nameZh":6,"description":127,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":128,"categories":129,"keywords":130,"publishedAt":43},"01M71HAG6MHKNQV8KDZKMT4886","registry-artifact-extract","Extract and analyze Windows Registry hives to uncover user activity, installed software, autostart entries, and evidence of system compromise.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fregistry\u002Fartifact\u002Fextract\u002FSKILL.md",[],[131,132,133,134,135,136,37,113,137,114,138,139,88,121,140,141,142,143,144,145],"artifact","registry","registry artifact extract","extract","evidence-collection","artifact-analysis","collection","analyze","uncover","software","activity","digital-forensics","windows-registry","regripper","sonnet",{"skillNo":147,"name":148,"nameZh":6,"description":149,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":152,"publishedAt":43},"01M71HACR4A8XTWTTSXK4124AA","processes-token-impersonate-detect","Detect Windows token impersonation and privilege abuse including SeImpersonatePrivilege exploitation 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QueueUserAPC, NtCreateThreadEx, and thread hijacking via process memory analysis.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Fthread\u002Finjection\u002Fdetect\u002FSKILL.md",[],[175,176,84,177,155,157,178,89,179,159,37,100,114,180,181,182,183,167,88,90],"thread","processes thread injection detect","injection","memory","process-injection","api","apc-injection","thread-injection","nt-api",{"skillNo":185,"name":186,"nameZh":6,"description":187,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":188,"categories":189,"keywords":190,"publishedAt":43},"01M71HA7H311V5G14WMX58HQSS","processes-hollow-technique-detect","Detect process hollowing (RunPE) by identifying processes with mismatched image paths between PEB and VAD tree, or unmapped PE headers in memory.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Fhollow\u002Ftechnique\u002Fdetect\u002FSKILL.md",[],[191,84,155,192,178,89,193,194,37,100,195,196,197,198,199,33,88,90,200,201],"processes hollow technique detect","tree","memory-forensics","process-hollow","peb","runpe","image","pe-header","in memory","mismatched","headers"]