Analyze a suspicious email a user reported
Breaks down a reported email's headers, links, and content into a phishing verdict and clear next steps.
The prompt
Help me analyze a suspicious email that an employee reported.
Email headers: [PASTE full headers]
Body text: [PASTE - defang links, e.g. hxxps://example[.]com]
Links and attachments: [URLs, file names, types, hashes]
Who received it: [one person / a team / many users]
Did anyone click, reply, open the attachment, or enter credentials? [YES/NO/UNKNOWN, details]
Analyze:
1. Sender authentication: SPF, DKIM, DMARC results, Return-Path vs. From, Reply-To mismatches, and the sending infrastructure.
2. Lookalike domains, display-name spoofing, or a compromised legitimate account.
3. Social engineering cues: urgency, payment or credential requests, unusual tone, timing.
4. Link and attachment risk: where links really point, redirects, file types that can run code.
5. Verdict: phishing / spam / legitimate / unclear, with confidence.
Then give me the response actions, scaled to what happened:
- No interaction: block sender or domain, search and purge similar messages, update filters.
- Clicked or entered credentials: reset password, revoke sessions and tokens, check MFA changes and inbox rules, review sign-ins.
- Opened attachment: isolate and scan the device, check for persistence.
Rules: do not visit the links or open attachments yourself, and tell me to use a sandbox for detonation. Do not claim a domain or IP is malicious without data I provided; suggest which reputation sources to check.
Return: verdict summary, evidence table (Indicator | Finding | Risk), response checklist, and a list of IOCs to block.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Software Development prompts
What to fill in
- PASTE full headers
- PASTE - defang links, e.g. hxxps://example[.
- URLs, file names, types, hashes
- one person / a team / many users
- YES/NO/UNKNOWN, details
How this prompt is built
This prompt follows the RTF structure (Role, Task, Format). RTF tells the model who to be, what to do and what shape the answer should take. It is the quickest structure that still gives noticeably better results than a bare request.
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