What is respond-phishing?

A structured workflow for responding to reported phishing emails using the PICERL incident-response model. Phishing is a deceptive message designed to make people click, disclose information, or open harmful content.

Use it with email headers, bodies, attachments, URLs, recipients, and sender details. It records phishing URLs and categories, affected and clicked users, blocked indicators, restricted accounts, and isolated devices.

It helps determine who received or clicked the message, identify malicious links and files, contain the incident, and remove the email from mailboxes.

respond-phishing — 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-phishing

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-phishing/github.svg)](https://agentmods.dev/skills/dandye/ai-runbooks/respond-phishing)

Your own site

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

Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,599 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	$0.00048	$0.01599
Opus 5.5	$0.00019	$0.00640
Sonnet 5.5	$0.00010	$0.00320
Haiku 4.5	$0.00005	$0.00160

Measured 2mo ago against content hash dd8adbef8a8c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

respond-phishing 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-phishing/SKILL.md · 258 lines

How it starts

The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Phishing Incident Response Skill

Structured workflow for responding to reported phishing emails using the PICERL model.

Inputs

CASE_ID - SOAR case ID for the incident
ALERT_GROUP_IDENTIFIERS - Alert group identifiers from SOAR
REPORTED_EMAIL_ARTIFACTS - Information about the email:
- Email headers
- Email body
- Attached files (hashes)
- URLs in email
- Recipient user ID(s)
- Sender address/domain

Required Outputs

After completing each phase, you MUST report these outputs:

Identification Phase

Output	Description
`PHISHING_URLS`	URLs extracted from email body
`PHISHING_IOCS`	Confirmed malicious indicators (URLs, domains, hashes)
`AFFECTED_USERS`	All users who received the email
`CLICKED_USERS`	Users who clicked/interacted with malicious content
`PHISHING_CATEGORY`	Type: credential phish, spear phishing, BEC, malware delivery

Containment Phase

Output	Description
`BLOCKED_IOCS`	IOCs blocked at email gateway/proxy/firewall
`CONTAINED_USERS`	User accounts with restrictions applied
`ISOLATED_ENDPOINTS`	Endpoints isolated due to suspicious activity

Eradication Phase

Output	Description
`DELETED_EMAILS`	Count of malicious emails removed from mailboxes
`QUARANTINED_EMAILS`	Emails moved to quarantine

Recovery Phase

Output	Description
`RESTORED_ACCOUNTS`	User accounts restored to normal access
`USER_NOTIFICATIONS`	Users notified of incident and required actions

PICERL Phases

Phase 2: Identification

Step 2.1: Get Context & Check Duplicates

secops-soar.get_case_full_details(case_id=CASE_ID)

Use /check-duplicates.

Step 2.2: Analyze Email Artifacts

Extract from email:

All URLs → EXTRACTED_URLS
Sender domain/IP
Attachment hashes → EXTRACTED_HASHES
Reply-to addresses
Header anomalies (SPF/DKIM failures)

Read the full file on GitHub · 258 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 · 258 lines · 48 tokens per session scan A dd8adbef8a8c

Subscribe to this mod's changes

respond-phishing is a skill published in the GitHub repository dandye/ai-runbooks (132 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 48 tokens to every session and 1,599 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.