Individual skill
analyzing-phishing-emails
Triage and forensically analyze reported phishing safely — extract the raw message, read the Received chain, verify SPF/DKIM/DMARC, detect display-name and lookalike spoofing, unwrap redirects and SafeLinks/URLDefense, decode quishing QR codes, triage attachments, and pull IOCs for hunting. Use when handed a reported phishing email, a suspicious .eml or .msg file, a set of email headers to analyze, a malicious attachment or link to triage, or a business email compromise or spoofing case.
secskills-defense/skills/analyzing-phishing-emails/SKILL.md
Source commit ca53957bcd8e3b83b5d4d190bb3ad008a4f15c84
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- Matches the observed repository HEAD
- Yes
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- No
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- Skill scan complete
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- Observed behavior
- Not checked yet
- Last checked
- Nov 6, 2026
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Repository context
- Repository stars (not skill ratings)
- 188
- Repository last updated
- Sep 4, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- security Repository topic
- skills Repository topic
- engineering Derived category
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# Analyzing Phishing Emails
An email is a stack of claims — who sent it, where it came from, that its
links are safe — and phishing analysis is checking each claim against evidence
the sender could not forge: the Received chain, the authentication results,
and the true destination of every link and attachment. The From header is a
display, not a fact. Anyone can type any address into it; your job is to find
the evidence that agrees or disagrees.
## When to Use
- A user reports a suspicious email and you need a verdict and IOCs
- You have a `.eml` or `.msg` file to analyze offline
- You are handed raw headers and asked whether a message is spoofed