bundled-skills/digital-forensics/SKILL.md
Authorized digital forensics: memory dumps, disk timelines, PCAP investigation, artifact triage, and incident-response evidence preservation.
npx skillsauth add FrancoStino/opencode-skills-antigravity digital-forensicsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
protocol-reverse/)malware-analysis/ / threat-hunting/)□ 计算 SHA256;记录时区与采集命令
□ 工作在副本上;原始只读
□ chain of custody 备注写入 timeline
vol -f mem.dmp windows.info
vol -f mem.dmp windows.pslist
vol -f mem.dmp windows.netscan
vol -f mem.dmp windows.cmdline
□ 事件日志:Security / PowerShell / Sysmon
□ 持久化:Run 键、服务、计划任务、WMI
□ 执行痕迹:Amcache、Prefetch、BAM
□ tshark 统计会话与 DNS
□ 导出可疑流 → protocol-reverse 或 malware C2 分析
| 工具 | 用途 | |------|------| | Volatility 3 | 内存 | | Timeline Explorer / Plaso | 超级时间线 | | tshark | PCAP | | Eric Zimmerman 工具集 | Windows 伪影 | | Autopsy / FTK Imager | 磁盘 |
references/forensics-triage.md../malware-analysis/ ../threat-hunting/ ../protocol-reverse/上游: MASTER R25
下游: 恶意样本深挖 → malware-analysis;规则 → threat-hunting
Adapted from zhaoxuya520/reverse-skill (MIT).
tools
Authorized security assessment of LLM applications and AI agents: prompt injection, tool abuse, RAG exposure, memory poisoning, system-prompt extraction, and agent-compliance engineering per OWASP LLM/ASI Top 10.
development
Builds two parameterized UI modes—流光溢彩白 (iridescent white) and 五彩斑斓黑 (colorful black)—with OKLCH, WebGL/CSS fallback, vision gating, screenshot QA, and total/per-color intensity reports. Use when a UI request names either mode or needs measured color parameters.
tools
Delegate coding tasks to the Kimi Code CLI (`kimi`) only when the user explicitly requests it, while the orchestrator retains review and landing responsibility.
development
Front-end JavaScript reverse engineering: locate signature chains, analyze encrypted request parameters, sample runtime behavior, and reproduce logic locally in Node for evidence-based output.