102 个 · 按相关度排序
FETIH Siber Güvenlik Ana Orkestratörü — 912+ skill ile tüm siber güvenlik alanlarını kapsar. Tehdit avı, zararlı yazılım analizi, dijital adli bilişim, olay müdahalesi, bulut güvenliği, ağ güvenliği, web uygulama güvenliği, API güvenliği, sızma testi, red team, SOC operasyonları, OT/ICS güvenliği ve daha 25+ alt kategori. ljagiello/ctf-skills ve Eyadkelleh/awesome-claude-skills-security entegre edildi.
中文简介正在准备中。当前显示原文说明。
Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.
中文简介正在准备中。当前显示原文说明。
Systematically deobfuscate multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure.
中文简介正在准备中。当前显示原文说明。
Responds to malware infections across enterprise endpoints by identifying the malware family, determining infection vectors, assessing spread, and executing eradication procedures. Covers the full lifecycle from detection through containment, analysis, removal, and recovery. Activates for requests involving malware response, malware eradication, trojan removal, worm containment, malware triage, or infected endpoint remediation.
中文简介正在准备中。当前显示原文说明。
Investigate supply chain attack artifacts including trojanized software updates, compromised build pipelines, and sideloaded dependencies to identify intrusion vectors and scope of compromise.
中文简介正在准备中。当前显示原文说明。
Builds an automated malware submission and analysis pipeline that collects suspicious files from endpoints and email gateways, submits them to sandbox environments and multi-engine scanners, and generates verdicts with IOCs for SIEM integration. Use when SOC teams need to scale malware analysis beyond manual sandbox submissions for high-volume alert triage.
中文简介正在准备中。当前显示原文说明。
Parse Windows Prefetch files using the windowsprefetch Python library to reconstruct application execution history, detect renamed or masquerading binaries, and identify suspicious program execution patterns.
中文简介正在准备中。当前显示原文说明。
Detect and analyze covert communication channels used by malware including DNS tunneling, ICMP exfiltration, steganographic HTTP, and protocol abuse for C2 and data exfiltration.
中文简介正在准备中。当前显示原文说明。
Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.
中文简介正在准备中。当前显示原文说明。
Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.
中文简介正在准备中。当前显示原文说明。
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
中文简介正在准备中。当前显示原文说明。
Extract and analyze Cobalt Strike beacon configuration from PE files and memory dumps to identify C2 infrastructure, malleable profiles, and operator tradecraft.
中文简介正在准备中。当前显示原文说明。
Detect sandbox evasion techniques in malware samples by analyzing timing checks, VM artifact queries, user interaction detection, and sleep inflation patterns from Cuckoo/AnyRun behavioral reports
中文简介正在准备中。当前显示原文说明。
Use Sysinternals Autoruns to systematically identify and analyze malware persistence mechanisms across registry keys, scheduled tasks, services, drivers, and startup locations on Windows systems.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
Analyze suspicious artifacts in an isolated lab to contain and recover. For incident responders on owned estates. Never write, improve, or distribute malware.
中文简介正在准备中。当前显示原文说明。
Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.
中文简介正在准备中。当前显示原文说明。
Systematically deobfuscate multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure.
中文简介正在准备中。当前显示原文说明。
Responds to malware infections across enterprise endpoints by identifying the malware family, determining infection vectors, assessing spread, and executing eradication procedures. Covers the full lifecycle from detection through containment, analysis, removal, and recovery. Activates for requests involving malware response, malware eradication, trojan removal, worm containment, malware triage, or infected endpoint remediation.
中文简介正在准备中。当前显示原文说明。
Parse Windows Prefetch files using the windowsprefetch Python library to reconstruct application execution history, detect renamed or masquerading binaries, and identify suspicious program execution patterns.
中文简介正在准备中。当前显示原文说明。
Builds an automated malware submission and analysis pipeline that collects suspicious files from endpoints and email gateways, submits them to sandbox environments and multi-engine scanners, and generates verdicts with IOCs for SIEM integration. Use when SOC teams need to scale malware analysis beyond manual sandbox submissions for high-volume alert triage.
中文简介正在准备中。当前显示原文说明。
Investigate supply chain attack artifacts including trojanized software updates, compromised build pipelines, and sideloaded dependencies to identify intrusion vectors and scope of compromise.
中文简介正在准备中。当前显示原文说明。
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
中文简介正在准备中。当前显示原文说明。
Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.
中文简介正在准备中。当前显示原文说明。