Build an Email Header Analyzer for Phishing Detection
Design a tool that evaluates email headers to identify signs of phishing — such as forged sender domains, IP mismatches, and missing DKIM/SPF records — helping users detect malicious messages more easily.Email headers contain critical metadata that reveal the true origin of a message. Phishing attempts often spoof sender information to appear legitimate. By parsing and analyzing headers, users can uncover inconsistencies and identify spoofed or malicious messages before they cause harm.
The tool allows users to paste or upload raw email headers, which are then parsed to highlight source IPs, hop history, DKIM/SPF validation, and domain mismatches — flagging emails that show signs of phishing or impersonation.
Header Parser & IP Extraction
Parse `Received` headers and extract IP addresses, hostnames, and mail server chains.
SPF/DKIM/DMARC Validation
Check if the email passed SPF/DKIM authentication and has valid DMARC policies in place.
Domain Mismatch Detection
Compare sender domain with envelope-from and reply-to fields for inconsistencies.
Phishing Risk Score
Calculate a score based on suspicious indicators and provide an interpretation (e.g., Safe, Suspicious, Dangerous).
Users paste an email header into the tool. It parses routing hops, extracts IPs, checks DNS records for SPF and DKIM results, and compares sender identities. Each suspicious element is highlighted, and a cumulative phishing risk score is displayed with recommended actions.
- Users paste raw headers or upload `.eml` files.
- The system parses `Received`, `From`, `Reply-To`, and `Return-Path` fields.
- IP reputation and geolocation are queried via external APIs or local databases.
- SPF and DKIM validation checks are done via DNS queries.
- The tool calculates a phishing likelihood score and explains findings clearly.
Parsing & Analysis
Python (email, re, dkim, dns.resolver), Flask for web interface.
DNS & Validation
dnspython for SPF/DKIM lookups, Postmark/Mailgun APIs for result comparison (optional).
Frontend
React.js or simple HTML forms with syntax highlighting and color-coded warnings.
Phishing Scoring
Heuristic scoring model using predefined risk weights (e.g., missing SPF = +20 points).
1. Build Header Input Parser
Create a module that parses all standard email headers, extracting IPs and domains.
2. Implement SPF/DKIM Validation
Use dnspython to check sender domain records and authentication results.
3. Detect Domain Anomalies
Highlight mismatches between `From`, `Return-Path`, and `Reply-To` fields.
4. Calculate Phishing Risk Score
Assign weights to various suspicious patterns and display a severity score.
5. Add Web Interface and Highlighting
Display color-coded output and provide exportable reports or alerts for flagged headers.
See the Truth Behind Every Email
Build a smart email header analysis tool to protect users from phishing threats and empower security analysts with accurate source validation insights.
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