Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/jessefmoore/offensive-claude-code/incident-responsenpx skills add jessefmoore/offensive-claude-code --skill incident-responsegit clone --depth 1 https://github.com/jessefmoore/offensive-claude-codeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jessefmoore/offensive-claude-code/incident-response)<a href="https://agentmods.dev/skills/jessefmoore/offensive-claude-code/incident-response"><img src="https://agentmods.dev/badge/skills/jessefmoore/offensive-claude-code/incident-response.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00029 | $0.01490 |
| Opus 5 | $0.00015 | $0.00745 |
| Sonnet 5 | $0.00006 | $0.00298 |
| Haiku 4.5 | $0.00003 | $0.00149 |
Grade A, and why
incident-response scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Response
When to Activate
- Active security incident requiring investigation
- Memory forensics and artifact extraction
- Disk forensics and timeline reconstruction
- Malware containment and eradication
- Post-incident analysis and reporting
IR Phases
1. Identification & Scoping
# Determine scope of compromise
# Key questions:
# - What systems are affected?
# - What's the initial access vector?
# - How long has the attacker been present?
# - What data may be compromised?
# - Is the attacker still active?
# Quick triage
chainsaw hunt /path/to/evtx/ -s sigma/ --mapping mappings/sigma-event-log-all.yml
hayabusa csv-timeline -d /path/to/evtx/ -o timeline.csv
2. Evidence Collection
# Memory acquisition (before anything else!)
# Windows: winpmem, DumpIt, FTK Imager
# Linux: LiME (insmod lime.ko "path=/evidence/mem.lime format=lime")
# Disk imaging
dd if=/dev/sda of=/evidence/disk.img bs=4M status=progress
# Or: FTK Imager, dc3dd for forensic imaging
# Log collection
# Windows: Event logs, Sysmon, PowerShell logs
# Linux: /var/log/auth.log, /var/log/syslog, journalctl
# Network: PCAP, NetFlow, DNS logs, proxy logs
# Cloud: CloudTrail, Azure Activity Log, GCP Audit Log
# Volatile data (collect before shutdown)
# - Running processes (ps aux / tasklist)
# - Network connections (netstat -anp / Get-NetTCPConnection)
# - Logged-in users (w / query user)
# - Open files (lsof / handle.exe)
# - Loaded modules (lsmod / listdlls)
3. Memory Forensics (Volatility 3)
# Process analysis
vol3 -f mem.raw windows.pslist
vol3 -f mem.raw windows.pstree
vol3 -f mem.raw windows.cmdline
vol3 -f mem.raw windows.netscan
# Malware detection
vol3 -f mem.raw windows.malfind # injected code
vol3 -f mem.raw windows.hollowprocesses # process hollowing
vol3 -f mem.raw windows.svcscan # suspicious services
# Credential extraction
vol3 -f mem.raw windows.hashdump
vol3 -f mem.raw windows.lsadump
vol3 -f mem.raw windows.cachedump
# File extraction
vol3 -f mem.raw windows.dumpfiles --pid PID
vol3 -f mem.raw windows.filescan | grep -i "suspicious"
# Linux memory
vol3 -f mem.raw linux.pslist
vol3 -f mem.raw linux.bash # bash history from memory
vol3 -f mem.raw linux.check_syscall # rootkit detection
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 218 lines · 29 tokens per session scan A e5693fccf999
incident-response is a skill published in the GitHub repository jessefmoore/offensive-claude-code (2 stars, last pushed 3mo ago), licensed MIT. It adds 29 tokens to every session and 1,490 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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