[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ADQC6CTJTZGSHFPWETXEG2":3,"skill-same:01M6ADQC6CTJTZGSHFPWETXEG2":103},{"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":36,"linkOnly":37,"markdownContent":38,"markdownBody":39,"frontMatter":40,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":61,"ownerHtmlUrl":62,"ownerBlogUrl":63,"ownerDescription":64,"updatedAt":65,"install":66,"resources":79},"01M6ADQC6CTJTZGSHFPWETXEG2","analyzing-memory-forensics-with-lime-and-volatility",null,"Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux memory images. Use when performing incident response on compromised Linux systems.","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",36078,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-memory-forensics-with-lime-and-volatility\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35],"forensics","analyzing memory forensics with lime and volatility","Volatility","memory","cybersecurity","incident response","code","framework","kernel","security-operations","memory-forensics","linux-forensics","incident-response","security","lime","kernel-modules","linux","2026-11-10 10:12:30",false,"---\nname: analyzing-memory-forensics-with-lime-and-volatility\ndescription: 'Performs Linux memory acquisition using LiME (Linux Memory Extractor)\n  kernel module and analysis with Volatility 3 framework. Extracts process lists,\n  network connections, bash history, loaded kernel modules, and injected code from\n  Linux memory images. Use when performing incident response on compromised Linux\n  systems.\n\n  '\ndomain: cybersecurity\nsubdomain: security-operations\ntags:\n- memory-forensics\n- linux-forensics\n- lime\n- volatility\n- incident-response\n- kernel-modules\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nnist_csf:\n- DE.CM-01\n- RS.MA-01\n- GV.OV-01\n- DE.AE-02\nmitre_attack:\n- T1055\n- T1003.001\n- T1620\n- T1564.001\n---\n\n# Analyzing Memory Forensics with LiME and Volatility\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing memory forensics with lime and volatility\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- Familiarity with security operations concepts and tools\n- Access to a test or lab environment for safe execution\n- Python 3.8+ with required dependencies installed\n- Appropriate authorization for any testing activities\n\n## Instructions\n\nAcquire Linux memory using LiME kernel module, then analyze with Volatility 3\nto extract forensic artifacts from the memory image.\n\n```bash\n# LiME acquisition\ninsmod lime-$(uname -r).ko \"path=\u002Fevidence\u002Fmemory.lime format=lime\"\n\n# Volatility 3 analysis\nvol3 -f \u002Fevidence\u002Fmemory.lime linux.pslist\nvol3 -f \u002Fevidence\u002Fmemory.lime linux.bash\nvol3 -f \u002Fevidence\u002Fmemory.lime linux.sockstat\n```\n\n```python\nimport volatility3\nfrom volatility3.framework import contexts, automagic\nfrom volatility3.plugins.linux import pslist, bash, sockstat\n\n# Programmatic Volatility 3 usage\ncontext = contexts.Context()\nautomagics = automagic.available(context)\n```\n\nKey analysis steps:\n1. Acquire memory with LiME (format=lime or format=raw)\n2. List processes with linux.pslist, compare with linux.psscan\n3. Extract bash command history with linux.bash\n4. List network connections with linux.sockstat\n5. Check loaded kernel modules with linux.lsmod for rootkits\n\n## Examples\n\n```bash\n# Full forensic workflow\nvol3 -f memory.lime linux.pslist | grep -v \"\\[kthread\\]\"\nvol3 -f memory.lime linux.bash\nvol3 -f memory.lime linux.malfind\nvol3 -f memory.lime linux.lsmod\n```\n","# Analyzing Memory Forensics with LiME and Volatility\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing memory forensics with lime and volatility\n- When building detection rules or threat hunting queries for this domain\n- When SOC analysts need structured procedures for this analysis type\n- When validating security monitoring coverage for related attack techniques\n\n## Prerequisites\n\n- Familiarity with security operations concepts and tools\n- Access to a test or lab environment for safe execution\n- Python 3.8+ with required dependencies installed\n- Appropriate authorization for any testing activities\n\n## Instructions\n\nAcquire Linux memory using LiME kernel module, then analyze with Volatility 3\nto extract forensic artifacts from the memory image.\n\n```bash\n# LiME acquisition\ninsmod lime-$(uname -r).ko \"path=\u002Fevidence\u002Fmemory.lime format=lime\"\n\n# Volatility 3 analysis\nvol3 -f \u002Fevidence\u002Fmemory.lime linux.pslist\nvol3 -f \u002Fevidence\u002Fmemory.lime linux.bash\nvol3 -f \u002Fevidence\u002Fmemory.lime linux.sockstat\n```\n\n```python\nimport volatility3\nfrom volatility3.framework import contexts, automagic\nfrom volatility3.plugins.linux import pslist, bash, sockstat\n\n# Programmatic Volatility 3 usage\ncontext = contexts.Context()\nautomagics = automagic.available(context)\n```\n\nKey analysis steps:\n1. Acquire memory with LiME (format=lime or format=raw)\n2. List processes with linux.pslist, compare with linux.psscan\n3. Extract bash command history with linux.bash\n4. List network connections with linux.sockstat\n5. Check loaded kernel modules with linux.lsmod for rootkits\n\n## Examples\n\n```bash\n# Full forensic workflow\nvol3 -f memory.lime linux.pslist | grep -v \"\\[kthread\\]\"\nvol3 -f memory.lime linux.bash\nvol3 -f memory.lime linux.malfind\nvol3 -f memory.lime linux.lsmod\n```\n",{"name":5,"tags":41,"author":43,"domain":23,"license":15,"version":44,"nist_csf":45,"subdomain":28,"description":50,"mitre_attack":51},[29,30,33,42,31,34],"volatility","mahipal","1.0",[46,47,48,49],"DE.CM-01","RS.MA-01","GV.OV-01","DE.AE-02","Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux memory images. Use when performing incident response on compromised Linux systems.\n",[52,53,54,55],"T1055","T1003.001","T1620","T1564.001","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fanalyzing-memory-forensics-with-lime-and-volatility",4414,"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":67,"prompt":77,"zipAvailable":78},[68,71,74],{"tool":69,"command":70},"npx","npx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill analyzing-memory-forensics-with-lime-and-volatility",{"tool":72,"command":73},"bunx","bunx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill analyzing-memory-forensics-with-lime-and-volatility",{"tool":75,"command":76},"pnpm","pnpm dlx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill analyzing-memory-forensics-with-lime-and-volatility","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-memory-forensics-with-lime-and-volatility\u002FSKILL.md",true,[80,85,91,97],{"path":81,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":83,"sourceHtmlUrl":84},"LICENSE","许可证",11255,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-memory-forensics-with-lime-and-volatility\u002FLICENSE",{"path":86,"resourceType":87,"resourceTypeDesc":88,"sizeBytes":89,"sourceHtmlUrl":90},"references\u002Fapi-reference.md","REFERENCE","参考文档",1626,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-memory-forensics-with-lime-and-volatility\u002Freferences\u002Fapi-reference.md",{"path":92,"resourceType":93,"resourceTypeDesc":94,"sizeBytes":95,"sourceHtmlUrl":96},"scripts\u002Fagent.py","SCRIPT","脚本",7393,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-memory-forensics-with-lime-and-volatility\u002Fscripts\u002Fagent.py",{"path":98,"resourceType":99,"resourceTypeDesc":100,"sizeBytes":101,"sourceHtmlUrl":102},"SKILL.md.tmpl","OTHER","其他",3743,"https:\u002F\u002Fgithub.com\u002Fshengdabai\u002FTony-Claude-Code-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fgstack\u002Fios-clean\u002FSKILL.md.tmpl",[104,132,156,183,209,235],{"skillNo":105,"name":106,"nameZh":6,"description":107,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":115,"publishedAt":36},"01M6AGDM3HJXTKXX15ZZ0ZVCJ3","verifying-build-provenance-with-slsa-sigstore","Verifies 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",[110],{"categoryNo":111,"categoryName":112,"taxonomyType":113,"taxonomyTypeDesc":114},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[116,117,118,119,32,23,24,120,121,25,122,123,124,125,126,127,128,129,130,131],"sigstore","provenance","slsa","verifying build provenance with slsa sigstore","identity","pr","artifacts","ci","supply-chain","pipeline","supply-chain-security","t1195","attestation","code-signing","cosign","keyless",{"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":15,"licenseFileUrl":6,"sourceHtmlUrl":136,"categories":137,"keywords":139,"publishedAt":36},"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",[138],{"categoryNo":111,"categoryName":112,"taxonomyType":113,"taxonomyTypeDesc":114},[140,128,141,142,32,143,23,121,144,145,146,147,148,149,150,151,152,153,154,155],"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":157,"name":158,"nameZh":6,"description":159,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":160,"categories":161,"keywords":166,"publishedAt":36},"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",[162,165],{"categoryNo":163,"categoryName":164,"taxonomyType":113,"taxonomyTypeDesc":114},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":111,"categoryName":112,"taxonomyType":113,"taxonomyTypeDesc":114},[150,167,168,169,170,23,171,172,144,173,174,31,175,176,177,178,179,180,181,182],"backup","recovery","validating backup integrity for recovery","testing","infrastructure","validation","compliance","hash-verification","ransomware","cryptocurrency","detection","t1078","t1490","immutable","disaster-recovery","restore-testing",{"skillNo":184,"name":185,"nameZh":6,"description":186,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":187,"categories":188,"keywords":190,"publishedAt":36},"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",[189],{"categoryNo":111,"categoryName":112,"taxonomyType":113,"taxonomyTypeDesc":114},[191,192,193,23,194,195,196,197,198,199,200,201,202,203,204,205,147,206,207,208],"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":210,"name":211,"nameZh":6,"description":212,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":213,"categories":214,"keywords":216,"publishedAt":36},"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",[215],{"categoryNo":111,"categoryName":112,"taxonomyType":113,"taxonomyTypeDesc":114},[217,26,218,23,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234],"vulnerabilities","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":236,"name":237,"nameZh":6,"description":238,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":239,"categories":240,"keywords":242,"publishedAt":36},"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",[241],{"categoryNo":111,"categoryName":112,"taxonomyType":113,"taxonomyTypeDesc":114},[32,243,23,244,245,246,247,248,249,250,251,178,252,179,253,254,255,256,257,258],"triaging security incident","siem","file","ioc","soc","NIST-800-61","NIST","severity","edr","execution","analysis","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]