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Incident Response

Community
hypnguyen1209
incident-response

Use when responding to or forensically investigating an incident — triage acquisition (Velociraptor/KAPE), Volatility 3 memory forensics, Chainsaw/Hayabusa EVTX timelining, anti-forensics detection, cloud IR, ransomware/ESXi response

Overview

Publisherhypnguyen1209
Repositoryoffensive-claude
Skill nameincident-response
Stars
396
Forks
71
Bundled files
16
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 16 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hypnguyen1209 on GitHub. Read the source before you install it.

Installation

Install the Incident Response AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hypnguyen1209/offensive-claude/tree/main/skills/incident-response
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hypnguyen1209/offensive-claude.git /tmp/offensive-claude
mkdir -p .claude/skills
cp -r /tmp/offensive-claude/skills/incident-response .claude/skills/incident-response
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Incident Response in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Incident Response on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Incident Response is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Incident Response & Digital Forensics

When to Activate

  • Active security incident: triage, scoping, evidence acquisition, containment, eradication
  • Memory forensics — process injection, rootkit (incl. eBPF), credential-theft, network artifacts
  • Windows event-log / artifact timelining and super-timeline reconstruction
  • Anti-forensics detection — timestomping, log clearing, secure deletion, VSS recovery
  • Cloud incident response — AWS/Azure/GCP identity-plane attacks and forensic collection
  • Ransomware / extortion response — hypervisor (ESXi) encryption, backup destruction, fast-dwell intrusions
  • Verifying suspect DFIR tooling used as adversary persistence (Velociraptor CVE-2025-6264)
  • Repository-compromise post-mortem — a poisoned public repo / force-pushed malicious commit / deleted PR (recover via dangling commits + GH Archive + Wayback + Events API; see references/repo-compromise-forensics.md)

Technique Map

TechniqueATT&CKCWEReferenceScript
Order-of-volatility live triage (Velociraptor/KAPE/UAC/CatScale)T1074CWE-778references/triage-collection.mdscripts/triage_collector.py
Offline collector build + RAM acquisition (winpmem/LiME/AVML)T1074CWE-778references/triage-collection.mdscripts/triage_collector.py
Suspect-tooling verification (Velociraptor CVE-2025-6264)T1219CWE-269references/triage-collection.mdscripts/triage_collector.py
Volatility 3 process/injection analysis (malfind, hollow)T1055CWE-noinforeferences/memory-forensics.mdscripts/vol3_triage.py
Credential extraction from memory (LSASS, hives)T1003.001CWE-522references/memory-forensics.mdscripts/vol3_triage.py
Kernel + eBPF rootkit detection (LinkPro, linux.ebpf)T1014CWE-269references/memory-forensics.mdscripts/ebpf_rootkit_hunt.sh
EVTX Sigma hunting & fast timeline (Chainsaw/Hayabusa)T1070.001CWE-778references/windows-evtx-timeline.mdscripts/evtx_hunt.sh
Super-timeline (plaso) + Timesketch correlationT1070CWE-778references/windows-evtx-timeline.mdscripts/evtx_hunt.sh
Timestomping detection ($SI vs $FN, USN FILE_CREATE)T1070.006CWE-noinforeferences/anti-forensics-detection.mdscripts/timestomp_detect.py
Log/journal clearing & VSS recoveryT1070.001, T1490CWE-778references/anti-forensics-detection.mdscripts/timestomp_detect.py
Cloud IR — IMDSv2/SSRF cred theft, CloudTrail/GuardDutyT1552.005, T1078.004CWE-918references/cloud-ir.mdscripts/cloud_ir_collect.py
Entra ID / token theft, identity-plane containmentT1528, T1078.004CWE-287references/cloud-ir.mdscripts/cloud_ir_collect.py
Ransomware rapid triage (Windows/Linux)T1486, T1490, T1485CWE-noinforeferences/ransomware-esxi-ir.mdscripts/ransomware_triage.ps1
ESXi / hypervisor ransomware response (UNC3944)T1486CWE-noinforeferences/ransomware-esxi-ir.mdscripts/ransomware_triage.ps1

Quick Start

bash
# 0. PRESERVE ORDER OF VOLATILITY — RAM before disk, never reboot a live host first.
#    Windows RAM:  winpmem_mini_x64.exe mem.raw        Linux RAM: AVML  ./avml mem.lime
# 1. Network-wide / endpoint triage (pick one):
python3 scripts/triage_collector.py --os auto --out /evidence --velociraptor-collector
#    Verify any Velociraptor already on-host is NOT adversary persistence (CVE-2025-6264):
python3 scripts/triage_collector.py --check-velociraptor   # flags <0.73.5 / unknown service

# 2. Memory forensics (Windows or Linux dump):
python3 scripts/vol3_triage.py -f /evidence/mem.raw --os windows --hunt-injection --dump-suspect
bash   scripts/ebpf_rootkit_hunt.sh   # Linux live/IR eBPF rootkit hunt (LinkPro-aware)

# 3. Windows event-log fast timeline + Sigma hunt:
bash scripts/evtx_hunt.sh -d /evidence/C/Windows/System32/winevt/Logs -o /evidence/timeline

# 4. Anti-forensics: timestomp / USN tamper detection from $MFT + $J:
python3 scripts/timestomp_detect.py --mft /evidence/mft.csv --usn /evidence/usn.csv

# 5. Cloud breach (identity-plane first):
python3 scripts/cloud_ir_collect.py aws --collect-cloudtrail --contain-key AKIA... --enforce-imdsv2

# 6. Ransomware on a Windows host (rapid scope, do BEFORE eradication):
powershell -ep bypass -File scripts/ransomware_triage.ps1 -OutDir C:\IR

OPSEC & Detection (summary)

IR is defensive; "OPSEC" below = handling rules that keep evidence admissible and avoid tipping off an adversary who may be monitoring (UNC3944 joins IR bridges in real time).

TechniqueTelemetry / IOCDetection (Sigma / EDR)OPSEC / evidence note
Live triageNew service/scheduled task for collector; large file writes to evidence pathBaseline expected DFIR tooling; alert on unsigned collectorsCollect RAM first; never write evidence to the suspect volume; hash everything
Velociraptor abusevelociraptor.exe svc <0.73.5; MSI from Azure Blob; relaunch after isolationSigma: unexpected Velociraptor service install; CVE-2025-6264 UpdateConfigTreat unexpected Velociraptor as persistence, not your tooling
Memory injectionRX/RWX private VAD not file-backed (malfind); reparented svchostVol3 malfind/hollowprocesses; EDR unbacked-execDocument plugin+offset provenance; keep raw dump read-only
eBPF rootkitbpf_override_return; getdents/sys_bpf hooks; XDP magic-packet (win=54321); /etc/ld.so.preloadlinux.ebpf vs baseline; ss(netlink) vs /proc/net diff; YARA MAL_LinkPro_*bpftool/ps/ss lie on host — acquire RAM out-of-band (hypervisor/LiME RO)
EVTX clearing1102 (Security cleared), 104 (System cleared), gaps in EventRecordIDChainsaw/Hayabusa Sigma; alert on 1102/104Pull EVTX from VSS/disk image, not the tampered live log
Timestomp$SI ≠ $FN create time; sub-second zeros; USN FILE_CREATE mismatchtimestomp_detect.py; MFTECmd Created0x10 vs Created0x30$FN is harder to forge — anchor truth to it + USN/$LogFile
Cloud cred theftInstanceCredentialExfiltration.OutsideAWS; impossible-travel sign-in; CloudTrail StopLoggingGuardDuty findings; Sentinel KQL risky sign-insSnapshot+immutable-export BEFORE remediation; logs to a SIEM the attacker can't reach
Ransomware/ESXiMass file rename/ext change; vCenter/ESXi SSH on; bulk vim-cmd VM power-offSIEM: high-volume VM power-off from one host; vpxuser anomaliesImage before decrypt attempts; preserve note + sample; assume comms compromised

Deep Dives

  • references/triage-collection.md — Order of volatility, RAM acquisition (winpmem/AVML/LiME), Velociraptor 0.75 offline collectors & hunts, KAPE targets, UAC/CatScale for Unix/ESXi, suspect-tooling verification incl. Velociraptor CVE-2025-6264.
  • references/memory-forensics.md — Volatility 3 symbol-table workflow, Windows injection/credential/rootkit plugins, Linux pslist/check_syscall/hidden_modules, eBPF rootkit detection (LinkPro, linux.ebpf, bpf_override_return), dump extraction.
  • references/windows-evtx-timeline.md — Chainsaw v2 & Hayabusa v3 Sigma hunting, key Event IDs, EvtxECmd/Eric Zimmerman parsers, plaso super-timeline, Timesketch + Dissect/Acquire enterprise scaling.
  • references/anti-forensics-detection.md — Timestomping ($SI/$FN + USN cross-validation), log/journal clearing (1102/104, $LogFile gaps), secure-deletion artifacts, VSS recovery, $MFT/$J/$LogFile QuadLink correlation.
  • references/cloud-ir.md — NIST SP 800-61r3 / SP 800-201, AWS CloudTrail/GuardDuty/IMDSv2-SSRF, Azure Entra ID token theft & KQL, GCP audit logs, identity-plane containment, automated evidence preservation.
  • references/ransomware-esxi-ir.md — Ransomware rapid triage & decision flow, Scattered Spider/UNC3944 ESXi LotL chain, backup destruction, cross-platform builders (LockBit 5.0/DragonForce), containment & negotiation hygiene.
  • references/repo-compromise-forensics.md — poisoned public-repo post-mortem from four INDEPENDENT, attacker-uncontrollable sources: dangling/force-pushed commits (dangling_commit_finder.py, git fsck via git_safe), GH Archive + Wayback CDX + live Events API (gharchive_recover.py); hypothesis→verify-at-source (evidence_kit)→adversarial-check→report, attribution-with-confidence, BigQuery kept optional.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Incident Response AI skill do?

Use when responding to or forensically investigating an incident — triage acquisition (Velociraptor/KAPE), Volatility 3 memory forensics, Chainsaw/Hayabusa EVTX timelining, anti-forensics detection, cloud IR, ransomware/ESXi response

Why use Incident Response on TypingMind?

Because you install it once and use it with any model. Incident Response is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Incident Response in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hypnguyen1209/offensive-claude/tree/main/skills/incident-response. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Incident Response?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Incident Response?

As many as you like. As long as a model supports skills, you can use Incident Response with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Incident Response AI skill free?

Yes. It is published on GitHub by hypnguyen1209 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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