What is respond-malware?

A structured malware-incident response workflow based on PICERL: preparation, identification, containment, eradication, recovery, and lessons learned.

Use it after malware is detected on endpoints. It records affected hosts and users, malware samples and network indicators, isolated systems, blocked indicators, cleaned hosts, and removed persistence.

It gives responders a defined way to track what happened, limit damage, remove malware, and restore affected systems.

respond-malware — Skill for Claude Code and Codex by dandye

Install

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.

Any agent

npx skills add dandye/ai-runbooks --skill respond-malware

Clone the repo

git clone --depth 1 https://github.com/dandye/ai-runbooks

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/dandye/ai-runbooks/respond-malware/github.svg)](https://agentmods.dev/skills/dandye/ai-runbooks/respond-malware)

Your own site

<a href="https://agentmods.dev/skills/dandye/ai-runbooks/respond-malware"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/respond-malware/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/dandye/ai-runbooks/respond-malware"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/respond-malware.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,450 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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 5.1	$0.00047	$0.01450
Opus 5.5	$0.00019	$0.00580
Sonnet 5.5	$0.00009	$0.00290
Haiku 4.5	$0.00005	$0.00145

Measured 2mo ago against content hash 4e30a2851180, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

respond-malware 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 2mo 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.

skills/respond-malware/SKILL.md · 249 lines

How it starts

The opening of the file, as written. The whole thing — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Malware Incident Response Skill

Structured workflow for responding to suspected malware incidents using the PICERL model.

Inputs

CASE_ID - SOAR case ID for the incident
ALERT_GROUP_IDENTIFIERS - Alert group identifiers from SOAR
INITIAL_INDICATORS - Details from initial alerts:
- File hashes
- IPs/domains
- Affected hosts
- Affected users

Required Outputs

After completing each phase, you MUST report these outputs:

Identification Phase

Output	Description
`AFFECTED_HOSTS`	Hosts with confirmed malware
`MALWARE_SAMPLES`	File hashes requiring triage/analysis
`MALWARE_IOCS`	Network indicators (IPs, domains, URLs)
`AFFECTED_USERS`	Users who executed/accessed malware

Containment Phase

Output	Description
`ISOLATED_HOSTS`	Hosts successfully isolated from network
`BLOCKED_IOCS`	IOCs blocked at firewall/proxy

Eradication Phase

Output	Description
`CLEANED_HOSTS`	Hosts with malware removed
`REMOVED_PERSISTENCE`	Persistence mechanisms removed

Recovery Phase

Output	Description
`RESTORED_HOSTS`	Hosts restored to operational state
`VALIDATION_STATUS`	Post-recovery scan results

PICERL Phases

Phase 2: Identification

Step 2.1: Initial Triage

Use /triage-alert with CASE_ID for initial assessment.

secops-soar.get_case_full_details(case_id=CASE_ID)

Use /check-duplicates.

Step 2.2: Malware Triage

If file hash is primary indicator:

Use /triage-malware:

/triage-malware FILE_HASH=abc123 CASE_ID=1234

This provides:

GTI classification
Behavioral indicators
Network IOCs
Affected hosts/users

Step 2.3: IOC Enrichment

For other key IOCs (IPs, domains, URLs):

Use /enrich-ioc for each.

Step 2.4: Initial Scope Assessment

Compile:

AFFECTED_ENDPOINTS - Hosts with malware
AFFECTED_USERS - Users who executed/accessed
MALICIOUS_IOCs - Network indicators

Read the full file on GitHub · 249 lines

Changes

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.

2mo ago First seen · 249 lines · 47 tokens per session scan A 4e30a2851180

Subscribe to this mod's changes

respond-malware is a skill published in the GitHub repository dandye/ai-runbooks (132 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 47 tokens to every session and 1,450 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.