[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ADPQEEPVRRAFN5DKB6HT2K":3,"skill-same:01M6ADPQEEPVRRAFN5DKB6HT2K":123},{"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":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":64,"commitSha":65,"skillDirectory":66,"forksCount":67,"repositoryHtmlUrl":68,"repositoryHomepageUrl":69,"ownerHtmlUrl":70,"ownerBlogUrl":71,"ownerDescription":72,"updatedAt":73,"install":74,"resources":87},"01M6ADPQEEPVRRAFN5DKB6HT2K","analyzing-malicious-url-with-urlscan",null,"URLScan.io is a free service for scanning and analyzing suspicious URLs. It captures screenshots, DOM content, HTTP transactions, JavaScript behavior, and network connections of web pages in an isolat","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",35884,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-malicious-url-with-urlscan\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"malicious","analyzing malicious url with urlscan","engineering","screenshots","url-analysis","awareness","social-engineering","email-security","dmarc","phishing","threat-intelligence","suspicious","email","content","pr","http","web","javascript","cybersecurity","security","2026-11-10 10:12:30",false,"---\nname: analyzing-malicious-url-with-urlscan\ndescription: URLScan.io is a free service for scanning and analyzing suspicious URLs.\n  It captures screenshots, DOM content, HTTP transactions, JavaScript behavior, and\n  network connections of web pages in an isolat\ndomain: cybersecurity\nsubdomain: phishing-defense\ntags:\n- phishing\n- email-security\n- social-engineering\n- dmarc\n- awareness\n- url-analysis\n- threat-intelligence\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\natlas_techniques:\n- AML.T0052\nnist_csf:\n- PR.AT-01\n- DE.CM-09\n- RS.CO-02\n- DE.AE-02\nmitre_attack:\n- T1566.002\n- T1204.001\n- T1598.003\n---\n# Analyzing Malicious URL with URLScan\n\n## Overview\nURLScan.io is a free service for scanning and analyzing suspicious URLs. It captures screenshots, DOM content, HTTP transactions, JavaScript behavior, and network connections of web pages in an isolated environment. This skill covers using URLScan's web interface and API to investigate phishing URLs, credential harvesting pages, and malicious redirects without exposing the analyst's system to risk.\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing malicious url with urlscan\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- URLScan.io account (free tier available, API key for automation)\n- Python 3.8+ with requests library\n- Understanding of HTTP protocols and web technologies\n- Familiarity with phishing URL patterns\n\n## Key Concepts\n\n### URLScan Capabilities\n1. **Safe browsing**: Renders URLs in isolated Chromium instance\n2. **Screenshot capture**: Visual snapshot of the rendered page\n3. **DOM analysis**: Full HTML content after JavaScript execution\n4. **Network log**: All HTTP requests made by the page (HAR format)\n5. **Certificate analysis**: SSL\u002FTLS certificate details\n6. **Technology detection**: Identifies web frameworks and libraries\n7. **IP\u002FASN mapping**: Infrastructure intelligence\n8. **Verdict**: Community and automated classification\n\n### Phishing URL Red Flags\n- Newly registered domains (\u003C 30 days)\n- Free hosting services (Wix, GitHub Pages, Firebase)\n- URL shorteners hiding final destination\n- Excessive subdomain depth (login.microsoft.com.evil.com)\n- Brand name in subdomain or path, not domain\n- Non-standard ports\n- Data URIs or base64-encoded content\n- JavaScript-heavy pages with minimal HTML\n\n## Workflow\n\n### Step 1: Submit URL to URLScan\n```\nWeb: Navigate to https:\u002F\u002Furlscan.io and submit the suspicious URL\nAPI: POST https:\u002F\u002Furlscan.io\u002Fapi\u002Fv1\u002Fscan\u002F\n     Header: API-Key: your-api-key\n     Body: {\"url\": \"https:\u002F\u002Fsuspicious-url.com\", \"visibility\": \"private\"}\n```\n\n### Step 2: Analyze Results\n- Review screenshot for brand impersonation\n- Check redirects and final destination URL\n- Examine DOM for credential input forms\n- Review network requests for data exfiltration endpoints\n- Check SSL certificate validity and issuer\n\n### Step 3: Extract IOCs\n- Domains and IPs contacted\n- URLs in redirect chain\n- SHA-256 hashes of page resources\n- JavaScript file hashes\n\n### Step 4: Cross-Reference with Threat Intelligence\nUse the `scripts\u002Fprocess.py` to automate URL scanning, extract IOCs, and cross-reference with VirusTotal, PhishTank, and Google Safe Browsing.\n\n## Tools & Resources\n- **URLScan.io**: https:\u002F\u002Furlscan.io\u002F\n- **URLScan API**: https:\u002F\u002Furlscan.io\u002Fdocs\u002Fapi\u002F\n- **VirusTotal URL Scanner**: https:\u002F\u002Fwww.virustotal.com\u002F\n- **PhishTank**: https:\u002F\u002Fphishtank.org\u002F\n- **Google Safe Browsing**: https:\u002F\u002Ftransparencyreport.google.com\u002Fsafe-browsing\u002Fsearch\n- **Any.Run**: https:\u002F\u002Fany.run\u002F (interactive sandbox)\n- **Hybrid Analysis**: https:\u002F\u002Fwww.hybrid-analysis.com\u002F\n\n## Validation\n- Successfully scan a suspicious URL via API\n- Extract screenshot and identify brand impersonation\n- Document complete redirect chain\n- Generate IOC list from scan results\n- Cross-reference findings with at least 2 threat intelligence sources\n","# Analyzing Malicious URL with URLScan\n\n## Overview\nURLScan.io is a free service for scanning and analyzing suspicious URLs. It captures screenshots, DOM content, HTTP transactions, JavaScript behavior, and network connections of web pages in an isolated environment. This skill covers using URLScan's web interface and API to investigate phishing URLs, credential harvesting pages, and malicious redirects without exposing the analyst's system to risk.\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing malicious url with urlscan\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- URLScan.io account (free tier available, API key for automation)\n- Python 3.8+ with requests library\n- Understanding of HTTP protocols and web technologies\n- Familiarity with phishing URL patterns\n\n## Key Concepts\n\n### URLScan Capabilities\n1. **Safe browsing**: Renders URLs in isolated Chromium instance\n2. **Screenshot capture**: Visual snapshot of the rendered page\n3. **DOM analysis**: Full HTML content after JavaScript execution\n4. **Network log**: All HTTP requests made by the page (HAR format)\n5. **Certificate analysis**: SSL\u002FTLS certificate details\n6. **Technology detection**: Identifies web frameworks and libraries\n7. **IP\u002FASN mapping**: Infrastructure intelligence\n8. **Verdict**: Community and automated classification\n\n### Phishing URL Red Flags\n- Newly registered domains (\u003C 30 days)\n- Free hosting services (Wix, GitHub Pages, Firebase)\n- URL shorteners hiding final destination\n- Excessive subdomain depth (login.microsoft.com.evil.com)\n- Brand name in subdomain or path, not domain\n- Non-standard ports\n- Data URIs or base64-encoded content\n- JavaScript-heavy pages with minimal HTML\n\n## Workflow\n\n### Step 1: Submit URL to URLScan\n```\nWeb: Navigate to https:\u002F\u002Furlscan.io and submit the suspicious URL\nAPI: POST https:\u002F\u002Furlscan.io\u002Fapi\u002Fv1\u002Fscan\u002F\n     Header: API-Key: your-api-key\n     Body: {\"url\": \"https:\u002F\u002Fsuspicious-url.com\", \"visibility\": \"private\"}\n```\n\n### Step 2: Analyze Results\n- Review screenshot for brand impersonation\n- Check redirects and final destination URL\n- Examine DOM for credential input forms\n- Review network requests for data exfiltration endpoints\n- Check SSL certificate validity and issuer\n\n### Step 3: Extract IOCs\n- Domains and IPs contacted\n- URLs in redirect chain\n- SHA-256 hashes of page resources\n- JavaScript file hashes\n\n### Step 4: Cross-Reference with Threat Intelligence\nUse the `scripts\u002Fprocess.py` to automate URL scanning, extract IOCs, and cross-reference with VirusTotal, PhishTank, and Google Safe Browsing.\n\n## Tools & Resources\n- **URLScan.io**: https:\u002F\u002Furlscan.io\u002F\n- **URLScan API**: https:\u002F\u002Furlscan.io\u002Fdocs\u002Fapi\u002F\n- **VirusTotal URL Scanner**: https:\u002F\u002Fwww.virustotal.com\u002F\n- **PhishTank**: https:\u002F\u002Fphishtank.org\u002F\n- **Google Safe Browsing**: https:\u002F\u002Ftransparencyreport.google.com\u002Fsafe-browsing\u002Fsearch\n- **Any.Run**: https:\u002F\u002Fany.run\u002F (interactive sandbox)\n- **Hybrid Analysis**: https:\u002F\u002Fwww.hybrid-analysis.com\u002F\n\n## Validation\n- Successfully scan a suspicious URL via API\n- Extract screenshot and identify brand impersonation\n- Document complete redirect chain\n- Generate IOC list from scan results\n- Cross-reference findings with at least 2 threat intelligence sources\n",{"name":5,"tags":49,"author":50,"domain":42,"license":15,"version":51,"nist_csf":52,"subdomain":57,"description":7,"mitre_attack":58,"atlas_techniques":62},[33,31,30,32,29,28,34],"mahipal","1.0",[53,54,55,56],"PR.AT-01","DE.CM-09","RS.CO-02","DE.AE-02","phishing-defense",[59,60,61],"T1566.002","T1204.001","T1598.003",[63],"AML.T0052","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fanalyzing-malicious-url-with-urlscan",4379,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills","https:\u002F\u002Fmahipal.engineer\u002FAnthropic-Cybersecurity-Skills\u002F","https:\u002F\u002Fgithub.com\u002Fmukul975","Mahipal.engineer","🔐 Cybersecurity | 💻 Dev | 📷 Street Photographer\r\n🎓 MSc | 📚 Research & AI Security","2026-08-31 12:32:44",{"source":8,"skillName":5,"commands":75,"prompt":85,"zipAvailable":86},[76,79,82],{"tool":77,"command":78},"npx","npx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill 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artifact signatures and SLSA provenance using Sigstore's cosign (verify, verify-attestation, verify-blob-attestation) and slsa-verifier (verify-artifact), enforcing keyless OIDC builder identity and source repo against SLSA Build levels. Use in CI\u002FCD before deploying artifacts, when consuming third-party attestations, establishing a SLSA Build L3 pipeline, or confirming provenance during incident response or admission control.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fverifying-build-provenance-with-slsa-sigstore\u002FSKILL.md",[130],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[132,133,134,135,43,42,136,137,38,138,139,140,141,142,143,144,145,146,147,148],"sigstore","provenance","slsa","verifying build provenance with slsa sigstore","incident response","identity","code","artifacts","ci","supply-chain","pipeline","supply-chain-security","t1195","attestation","code-signing","cosign","keyless",{"skillNo":150,"name":151,"nameZh":6,"description":152,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":153,"categories":154,"keywords":156,"publishedAt":44},"01M6AGDGBPWYVZ2F11GFKJ4HZ9","validating-tpm-measured-boot-attestation","Verifies TPM 2.0 measured-boot integrity and remote attestation with tpm2-tools -- reading PCRs (tpm2_pcrread), replaying the boot event log, generating and checking signed quotes (tpm2_quote\u002Ftpm2_checkquote), and sealing secrets to a PCR policy. Use to confirm a system booted trusted firmware\u002Fkernel for Zero Trust device posture, detect boot-chain tampering via PCR drift, or build a golden-value baseline for fleet attestation.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fvalidating-tpm-measured-boot-attestation\u002FSKILL.md",[155],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[157,145,158,159,43,160,42,38,161,162,163,164,165,166,167,168,169,170,171,172],"boot","TPM","validating tpm measured boot attestation","policy","verification","ZeRO","firmware","Tools","measured-boot","PCR","integrity","secrets","remote-attestation","tpm2-tools","integrity-verification","trusted-computing",{"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":15,"licenseFileUrl":6,"sourceHtmlUrl":177,"categories":178,"keywords":183,"publishedAt":44},"01M6AGDCW0Y4FXZ3362GT1941M","validating-backup-integrity-for-recovery","Validates backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to confirm backups are reliable for disaster recovery and ransomware response. Use before relying on backups for recovery, when building post-backup validation pipelines, auditing backup infrastructure for compliance, or checking immutable\u002Fair-gapped backups for silent corruption or tampering.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fvalidating-backup-integrity-for-recovery\u002FSKILL.md",[179,182],{"categoryNo":180,"categoryName":181,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[167,184,185,186,187,42,188,189,161,190,191,192,193,194,195,196,197,198,199,200],"backup","recovery","validating backup integrity for recovery","testing","infrastructure","validation","compliance","hash-verification","incident-response","ransomware","cryptocurrency","detection","t1078","t1490","immutable","disaster-recovery","restore-testing",{"skillNo":202,"name":203,"nameZh":6,"description":204,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":205,"categories":206,"keywords":208,"publishedAt":44},"01M6AGD9GBG2KZ336AE763J3WH","triaging-windows-with-kape","Runs KAPE (Kroll Artifact Parser and Extractor) to collect targeted forensic artifacts (registry hives, $MFT, event logs, prefetch, browser data) via Targets and parse them with Modules wrapping Eric Zimmerman's EZ Tools (PECmd, MFTECmd, RECmd). Use during early incident containment\u002Ftriage when full disk imaging is impractical but a defensible, parseable Windows artifact set is needed quickly, including at-scale remote collection.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-windows-with-kape\u002FSKILL.md",[207],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[209,210,211,42,212,213,214,215,216,217,218,219,220,221,222,223,164,224,225,226],"windows","kape","triaging windows with kape","registry","browser","logs","windows-forensics","dfir","mft","mftecmd","data","prefetch","eric-zimmerman","digital-forensics","SET","collection","pecmd","artifact-collection",{"skillNo":228,"name":229,"nameZh":6,"description":230,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":231,"categories":232,"keywords":234,"publishedAt":44},"01M6AGD5PW5J4EVZM958WD74ZQ","triaging-vulnerabilities-with-ssvc-framework","Triages and prioritizes vulnerabilities with CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree, weighing exploitation status (via the CISA KEV catalog and FIRST EPSS API), technical impact, automatability, and mission prevalence to output Track\u002FTrack*\u002FAttend\u002FAct decisions. Use when prioritizing vulnerability scan results (OpenVAS, Nessus, Qualys) for remediation planning beyond raw CVSS scores.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-vulnerabilities-with-ssvc-framework\u002FSKILL.md",[233],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[235,236,237,42,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253],"vulnerabilities","framework","triaging vulnerabilities with ssvc framework","status","planning","CISA","vulnerability-management","risk-management","nessus","qualys","openvas","cvss","remediation","risk","vulnerability","api","prioritization","ssvc","decision-tree",{"skillNo":255,"name":256,"nameZh":6,"description":257,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":258,"categories":259,"keywords":261,"publishedAt":44},"01M6AGD24TTQQM4CXG69E3B9TJ","triaging-security-incident","Performs initial triage of security incidents using the NIST SP 800-61r3 and SANS PICERL frameworks, classifying incident type, assigning priority by business impact, and routing to the appropriate response team. Use when a SIEM\u002FEDR alert needs human classification, concurrent alerts must be prioritized, or a user report or threat-intel IOC match requires initial incident categorization.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-security-incident\u002FSKILL.md",[260],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[43,262,42,263,264,265,266,267,268,269,270,196,271,197,272,273,274,275,276,277],"triaging security incident","siem","file","ioc","soc","NIST-800-61","NIST","severity","edr","execution","analysis","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]