[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AFNPFX0PYFJGA6SMMGB9MK":3,"skill-same:01M6AFNPFX0PYFJGA6SMMGB9MK":90},{"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":34,"linkOnly":35,"markdownContent":36,"markdownBody":37,"frontMatter":38,"refName":49,"commitSha":50,"skillDirectory":51,"forksCount":52,"repositoryHtmlUrl":53,"repositoryHomepageUrl":54,"ownerHtmlUrl":55,"ownerBlogUrl":56,"ownerDescription":57,"updatedAt":58,"install":59,"resources":72},"01M6AFNPFX0PYFJGA6SMMGB9MK","performing-bluetooth-security-assessment",null,"Assess Bluetooth Low Energy (BLE) device security using Python's bleak asyncio library to discover nearby devices, enumerate GATT services and characteristics, and flag unencrypted or unauthenticated read\u002Fwrite access to sensitive data. Use when auditing IoT, healthcare, fitness, or smart-home BLE devices for weak pairing configurations or known vulnerable device fingerprints.","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",35990,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-bluetooth-security-assessment\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"security","assessment","bluetooth","performing bluetooth security assessment","python","cybersecurity","pr","library","iot","services","data","ble","gatt","wireless-security","devices","2026-11-10 10:12:30",false,"---\nname: performing-bluetooth-security-assessment\ndescription: Assess Bluetooth Low Energy (BLE) device security using Python's bleak asyncio\n  library to discover nearby devices, enumerate GATT services and characteristics, and flag\n  unencrypted or unauthenticated read\u002Fwrite access to sensitive data. Use when auditing IoT,\n  healthcare, fitness, or smart-home BLE devices for weak pairing configurations or known\n  vulnerable device fingerprints.\ndomain: cybersecurity\nsubdomain: wireless-security\ntags:\n- bluetooth\n- ble\n- gatt\n- wireless-security\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nnist_csf:\n- PR.IR-01\n- DE.CM-01\n- ID.AM-03\nmitre_attack:\n- T1557\n- T1040\n---\n\n\n# Performing Bluetooth Security Assessment\n\n## Overview\n\nThis skill covers performing Bluetooth Low Energy (BLE) security assessments using the Python bleak library. BLE devices are ubiquitous in IoT, healthcare, fitness, and smart home applications, and many ship with weak or absent security controls. This assessment identifies unencrypted GATT characteristics, devices broadcasting sensitive data, known vulnerable device fingerprints, and improperly secured pairing configurations.\n\nThe agent uses bleak's asyncio API to discover nearby BLE devices, connect to target devices, enumerate all GATT services and characteristics, and analyze security properties of each characteristic. It flags characteristics that allow unauthenticated read\u002Fwrite access to sensitive data and identifies devices matching known vulnerable profiles.\n\n\n## When to Use\n\n- When conducting security assessments that involve performing bluetooth security assessment\n- When following incident response procedures for related security events\n- When performing scheduled security testing or auditing activities\n- When validating security controls through hands-on testing\n\n## Prerequisites\n\n- Python 3.9 or later\n- bleak library (`pip install bleak`)\n- Bluetooth adapter supporting BLE (Bluetooth 4.0+)\n- Linux: BlueZ 5.43+ with D-Bus permissions\n- Windows: Windows 10 version 1709+ with Bluetooth support\n- macOS: macOS 10.15+ with CoreBluetooth\n\n## Steps\n\n1. **Scan for BLE devices**: Use BleakScanner to discover all advertising BLE devices within range. Capture device name, address (MAC), RSSI signal strength, and advertised service UUIDs.\n\n2. **Identify target devices**: Filter discovered devices by name pattern, address, or minimum signal strength. Flag devices broadcasting default or well-known vulnerable names.\n\n3. **Connect and enumerate GATT services**: Use BleakClient to connect to the target device and iterate over all GATT services. For each service, record the UUID, description, and contained characteristics.\n\n4. **Analyze characteristic properties**: For each characteristic, examine its properties (read, write, write-without-response, notify, indicate). Flag characteristics that expose read or write access without requiring authentication or encryption.\n\n5. **Check for known vulnerable UUIDs**: Compare discovered service and characteristic UUIDs against a database of known vulnerable or sensitive services (Heart Rate, Blood Pressure, Device Information, Battery Level) that should require encryption.\n\n6. **Detect unencrypted data exposure**: Attempt to read characteristics that should be protected. Successful unauthenticated reads of sensitive data indicate missing security controls.\n\n7. **Generate security report**: Compile all findings into a structured JSON report with severity classifications and remediation recommendations.\n\n## Expected Output\n\n```json\n{\n  \"assessment_type\": \"ble_security_audit\",\n  \"target_device\": {\n    \"name\": \"SmartBand-XR\",\n    \"address\": \"AA:BB:CC:DD:EE:FF\",\n    \"rssi\": -42\n  },\n  \"services_found\": 5,\n  \"characteristics_found\": 18,\n  \"findings\": [\n    {\n      \"severity\": \"high\",\n      \"finding\": \"Heart Rate Measurement readable without encryption\",\n      \"uuid\": \"00002a37-0000-1000-8000-00805f9b34fb\",\n      \"properties\": [\"read\", \"notify\"],\n      \"remediation\": \"Enable encryption requirement on characteristic\"\n    }\n  ],\n  \"risk_score\": 7.5\n}\n```\n","# Performing Bluetooth Security Assessment\n\n## Overview\n\nThis skill covers performing Bluetooth Low Energy (BLE) security assessments using the Python bleak library. BLE devices are ubiquitous in IoT, healthcare, fitness, and smart home applications, and many ship with weak or absent security controls. This assessment identifies unencrypted GATT characteristics, devices broadcasting sensitive data, known vulnerable device fingerprints, and improperly secured pairing configurations.\n\nThe agent uses bleak's asyncio API to discover nearby BLE devices, connect to target devices, enumerate all GATT services and characteristics, and analyze security properties of each characteristic. It flags characteristics that allow unauthenticated read\u002Fwrite access to sensitive data and identifies devices matching known vulnerable profiles.\n\n\n## When to Use\n\n- When conducting security assessments that involve performing bluetooth security assessment\n- When following incident response procedures for related security events\n- When performing scheduled security testing or auditing activities\n- When validating security controls through hands-on testing\n\n## Prerequisites\n\n- Python 3.9 or later\n- bleak library (`pip install bleak`)\n- Bluetooth adapter supporting BLE (Bluetooth 4.0+)\n- Linux: BlueZ 5.43+ with D-Bus permissions\n- Windows: Windows 10 version 1709+ with Bluetooth support\n- macOS: macOS 10.15+ with CoreBluetooth\n\n## Steps\n\n1. **Scan for BLE devices**: Use BleakScanner to discover all advertising BLE devices within range. Capture device name, address (MAC), RSSI signal strength, and advertised service UUIDs.\n\n2. **Identify target devices**: Filter discovered devices by name pattern, address, or minimum signal strength. Flag devices broadcasting default or well-known vulnerable names.\n\n3. **Connect and enumerate GATT services**: Use BleakClient to connect to the target device and iterate over all GATT services. For each service, record the UUID, description, and contained characteristics.\n\n4. **Analyze characteristic properties**: For each characteristic, examine its properties (read, write, write-without-response, notify, indicate). Flag characteristics that expose read or write access without requiring authentication or encryption.\n\n5. **Check for known vulnerable UUIDs**: Compare discovered service and characteristic UUIDs against a database of known vulnerable or sensitive services (Heart Rate, Blood Pressure, Device Information, Battery Level) that should require encryption.\n\n6. **Detect unencrypted data exposure**: Attempt to read characteristics that should be protected. Successful unauthenticated reads of sensitive data indicate missing security controls.\n\n7. **Generate security report**: Compile all findings into a structured JSON report with severity classifications and remediation recommendations.\n\n## Expected Output\n\n```json\n{\n  \"assessment_type\": \"ble_security_audit\",\n  \"target_device\": {\n    \"name\": \"SmartBand-XR\",\n    \"address\": \"AA:BB:CC:DD:EE:FF\",\n    \"rssi\": -42\n  },\n  \"services_found\": 5,\n  \"characteristics_found\": 18,\n  \"findings\": [\n    {\n      \"severity\": \"high\",\n      \"finding\": \"Heart Rate Measurement readable without encryption\",\n      \"uuid\": \"00002a37-0000-1000-8000-00805f9b34fb\",\n      \"properties\": [\"read\", \"notify\"],\n      \"remediation\": \"Enable encryption requirement on characteristic\"\n    }\n  ],\n  \"risk_score\": 7.5\n}\n```\n",{"name":5,"tags":39,"author":40,"domain":24,"license":15,"version":41,"nist_csf":42,"subdomain":32,"description":7,"mitre_attack":46},[21,30,31,32],"mahipal","1.0",[43,44,45],"PR.IR-01","DE.CM-01","ID.AM-03",[47,48],"T1557","T1040","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fperforming-bluetooth-security-assessment",4395,"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":60,"prompt":70,"zipAvailable":71},[61,64,67],{"tool":62,"command":63},"npx","npx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill performing-bluetooth-security-assessment",{"tool":65,"command":66},"bunx","bunx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill performing-bluetooth-security-assessment",{"tool":68,"command":69},"pnpm","pnpm dlx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill performing-bluetooth-security-assessment","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-bluetooth-security-assessment\u002FSKILL.md",true,[73,78,84],{"path":74,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":76,"sourceHtmlUrl":77},"LICENSE","许可证",11255,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-bluetooth-security-assessment\u002FLICENSE",{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},"references\u002Fapi-reference.md","REFERENCE","参考文档",2438,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-bluetooth-security-assessment\u002Freferences\u002Fapi-reference.md",{"path":85,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":88,"sourceHtmlUrl":89},"scripts\u002Fagent.py","SCRIPT","脚本",7856,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-bluetooth-security-assessment\u002Fscripts\u002Fagent.py",[91,120,144,172,197,224],{"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":6,"sourceHtmlUrl":95,"categories":96,"keywords":102,"publishedAt":34},"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",[97],{"categoryNo":98,"categoryName":99,"taxonomyType":100,"taxonomyTypeDesc":101},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[103,104,105,106,19,24,107,108,25,109,110,111,112,113,114,115,116,117,118,119],"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":121,"name":122,"nameZh":6,"description":123,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":124,"categories":125,"keywords":127,"publishedAt":34},"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",[126],{"categoryNo":98,"categoryName":99,"taxonomyType":100,"taxonomyTypeDesc":101},[128,116,129,130,19,131,24,25,132,133,134,135,136,137,138,139,140,141,142,143],"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":145,"name":146,"nameZh":6,"description":147,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":148,"categories":149,"keywords":154,"publishedAt":34},"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",[150,153],{"categoryNo":151,"categoryName":152,"taxonomyType":100,"taxonomyTypeDesc":101},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":98,"categoryName":99,"taxonomyType":100,"taxonomyTypeDesc":101},[138,155,156,157,158,24,159,160,132,161,162,163,164,165,166,167,168,169,170,171],"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":173,"name":174,"nameZh":6,"description":175,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":176,"categories":177,"keywords":179,"publishedAt":34},"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",[178],{"categoryNo":98,"categoryName":99,"taxonomyType":100,"taxonomyTypeDesc":101},[180,181,182,24,183,184,185,186,187,188,189,29,190,191,192,193,135,194,195,196],"windows","kape","triaging windows with kape","registry","browser","logs","windows-forensics","dfir","mft","mftecmd","prefetch","eric-zimmerman","digital-forensics","SET","collection","pecmd","artifact-collection",{"skillNo":198,"name":199,"nameZh":6,"description":200,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":201,"categories":202,"keywords":204,"publishedAt":34},"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",[203],{"categoryNo":98,"categoryName":99,"taxonomyType":100,"taxonomyTypeDesc":101},[205,206,207,24,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223],"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":225,"name":226,"nameZh":6,"description":227,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":228,"categories":229,"keywords":231,"publishedAt":34},"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",[230],{"categoryNo":98,"categoryName":99,"taxonomyType":100,"taxonomyTypeDesc":101},[19,232,24,233,234,235,236,237,238,239,240,167,241,168,242,243,244,245,246,247],"triaging security incident","siem","file","ioc","soc","NIST-800-61","NIST","severity","edr","execution","analysis","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]