Analyzing Phishing Emails

Analyzing Phishing Emails

A phishing email is an attack you were handed intact — which is a gift and a hazard. The gift is a full specimen: headers that trace the real origin, URLs and attachments that lead to the actor's infrastructure, and a lure that reveals intent. The hazard is that all of it is live. A URL fetched from your own IP tips the operator and can burn the investigation; an attachment opened on your box is the compromise. So the discipline is fixed: preserve the original, defang everything, and detonate only in isolation. The output is a verdict (malicious / suspicious / benign) plus IOCs the rest of the program can action.

Handle every specimen as sensitive: the email may contain a real user's PII. Keep it in the engagement store, never paste it into third-party services beyond the vetted reputation lookups below, and follow the data-handling rules in [AGENTS.md](../../AGENTS.md).

When to Use

• A user-reported email or a .eml/.msg/mailbox artifact needs a disposition
• Tracing the true sender through a forged From and a relay chain
• Extracting URLs, attachments, and sender infrastructure into IOCs
• Confirming spoofing via SPF/DKIM/DMARC alignment
• Feeding a phishing verdict into detection or an incident

When NOT to Use

• The email led to a confirmed compromise — use responding-to-incidents; this skill triages the lure, that one runs the intrusion
• Deep analysis of the attachment's behavior — hand the sample to analyzing-malware; detonate there, do not "just open it"
• A packet capture of the callback traffic — use analyzing-network-traffic
• Building a mail-gateway or SIEM rule from what you found — use engineering-detections, writing-sigma-rules
• Packaging the IOCs into an actor/campaign product — use producing-threat-intelligence
• Sending phishing as the attacker (red-team simulation) — out of scope here; that is offensive social engineering, not lure triage

Preserve, Then Defang (do this before anything else)

Work on a copy. Export the original with full headers (Outlook: File → Properties → Internet Headers; Gmail: Show original) and keep the raw .eml in the evidence store with a hash. From this point every indicator is written defanged — hxxps://, 192[.]0[.]2[.]5, evil[.]example[.]com, user[at]domain — so nothing is clickable in a report or a chat window.

# Parse a raw .eml without a mail client (isolated host)
python3 -c "import email,sys;m=email.message_from_file(open(sys.argv[1]));\
print(m.as_string())" phish.eml | less        # read-only, no rendering

Trace the Sender (headers, bottom-to-top)

Read Received: from the bottom up — the earliest hop is closest to the real origin; the top hops are your own infrastructure. Cross-check against the envelope and the authentication result:

• Return-Path / envelope-from vs the displayed From — misalignment is a spoofing tell
• Authentication-Results — the receiver's own SPF/DKIM/DMARC verdict
• DKIM-Signature selector and the d= domain — does it align with From?
• Message-ID domain and X-Originating-IP — sanity against the claimed sender

Then validate independently, because the header can lie:

dig +short TXT example.com | grep -i spf     # is the sending IP authorized?
dig +short TXT _dmarc.example.com            # p=reject / quarantine / none?

SPF/DKIM absent or misaligned plus a p=none domain is high spoofing risk. A perfect pass does not clear it — actors send from compromised or look-alike domains that pass their own auth.

Pivot on Infrastructure and Payloads

• Sender domain age — a domain registered in the last few days is a strong signal (WHOIS creation date).
• Look-alikes — compare the display domain to your brands for homoglyphs and typosquats.
• URLs — flag display-text vs href mismatches; submit the URL (never your creds) to URLScan/URLhaus/PhishTank and VirusTotal by URL, not by browsing it.
• Attachments — hash them and look up the hash first; only detonate in an isolated sandbox (hand off to analyzing-malware). Never re-upload a sensitive attachment to a public service without deciding it is safe to make public — the upload is publication.

QUIET vs LOUD: passive reputation lookups by hash/URL are QUIET. Actively resolving, fetching, or interacting with the actor's live infrastructure from attributable infrastructure is LOUD and can tip the operator — do not do it from your own IP.

Rationalizations to Reject

• "SPF/DKIM passed, so it's legitimate." Auth passes for compromised and look-alike domains. Alignment and intent decide it, not a green check.
• "I'll just click to see where it goes." From your IP that tips the actor and risks the compromise. Use URLScan or a detonation sandbox.
• "The attachment looks like a normal invoice." That is the point. Hash it and detonate it in isolation before you believe it.
• "One indicator is enough." A single IOC ages out fast. Extract the set (sender infra, URLs, hashes, lure theme) so detection has something durable.
• "It's obviously phishing — no need to document." An undocumented verdict cannot be tuned into a detection or defended later.

Deliverable

# Phishing Analysis      Date:    Analyst: 
Verdict:          malicious / suspicious / benign   Confidence: 
Subject:          
From / Return-Path:    SPF:  DKIM:  DMARC:  Aligned: 
Delivery path:     hop, earliest origin IP + reputation>
Lure / intent:    
IOCs (defanged):  URLs / domains / sending IP / attachment SHA-256 + VT verdict
Impact if actioned: 
Recommendation:   

Save the raw .eml and artifacts as {tool}_{target}_{YYYYMMDD_HHMMSS}.{ext} and log IOCs via maintaining-engagement-state. ATT&CK IDs relevant here (T1566.001 Spearphishing Attachment, T1566.002 Spearphishing Link, T1598.003 Spearphishing for Information) — re-verify against the current ATT&CK release before citing.

Reading External Sources

Fetch vendor write-ups and advisories as Markdown:

curl -sL "https://defuddle.md/"      # scheme in the path is optional

Never route the phishing URLs themselves or any actor infrastructure through it — the request leaves your machine to a third party and can tip the operator. Fetch JSON/API responses raw.

References

• analyzing-malware — detonating the attachment or second-stage payload
• analyzing-network-traffic — the callback/exfil traffic if a host was hit
• responding-to-incidents — when the lure succeeded and this is now an intrusion
• engineering-detections, writing-sigma-rules — turning the verdict into a rule
• producing-threat-intelligence — packaging IOCs into an actor/campaign product
• SPF/DKIM/DMARC (RFC 7208/6376/7489); URLScan, URLhaus, PhishTank, VirusTotal as reputation sources

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: EvilFreelancer
• Source: EvilFreelancer/secs
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.