EmailXpose — Updated!
EmailXpose is an open source AI-powered email security system that detects phishing, spam, scams, malware, and social engineering attacks. It goes beyond traditional email filters by combining natural language processing, behavioral analysis, and multi-modal intelligence to analyze text, images, and video content. The system also includes advanced features like sender trust scoring, attachment sandboxing, explainable risk reports, and symbolic/contextual interpretation of email content. Its goal is to provide transparent, privacy-first “AI-powered email clarity” so users can understand both threats and intent behind every message. https://roxanneardary.com/emailxpose/
EmailXpose Specification
AI-Powered Email Clarity
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Specification Overview
EmailXpose is an open source, modular AI email security and intelligence system designed to analyze email content, sender identity, links, attachments, images, and video to identify phishing, spam, scams, malware, social engineering, deception, and contextual anomalies.
EmailXpose combines conventional email security analysis with natural language processing, computer vision, multi-modal intelligence, behavioral analysis, threat intelligence, and symbolism interpretation. The system is designed to explain its findings rather than simply assigning a threat classification.
The architecture shall support local-first and offline operation, modular AI models, configurable detection policies, human review, extensible threat intelligence, and optional plugins without requiring users to depend on a specific vendor or cloud provider.
Design Principles
- Open source implementation
- Modular architecture
- Local-first processing
- Offline-capable analysis
- Privacy-preserving operation
- No automatic execution of untrusted email content
- Human-in-the-loop decision making
- Explainable AI
- Multi-modal analysis
- Vendor-neutral integrations
- Replaceable AI models
- Configurable detection policies
- Extensible plugin architecture
- Reproducible analysis
- Secure-by-default behavior
Core System Requirements
EmailXpose shall provide a unified analysis pipeline capable of accepting email messages from local files, mailboxes, supported protocols, APIs, or compatible integrations.
The system shall separate ingestion, normalization, analysis, scoring, explanation, storage, and presentation into independent modules.
Each analysis component shall produce structured findings that can be independently evaluated, combined, displayed, exported, or passed to another analysis module.
The system shall never execute untrusted email attachments directly on the host system.
Core Modules
Email Ingestion Module
The Email Ingestion Module shall provide secure mechanisms for importing email messages into EmailXpose.
Features:
- IMAP email ingestion
- SMTP-compatible message processing
- Local email file import
- MIME message parsing
- Multipart message processing
- HTML email extraction
- Plain-text extraction
- Embedded-content extraction
- Attachment identification
- Message metadata extraction
- Message normalization
- Duplicate message detection
- Message integrity tracking
- Configurable mailbox scanning
The module shall pass normalized email objects to downstream analysis modules without executing active content.
Email Header Forensics Module
The Email Header Forensics Module shall inspect technical metadata associated with email delivery and authentication.
Features:
- Complete header inspection
- SPF analysis
- DKIM analysis
- DMARC analysis
- Authentication-results analysis
- Return-Path inspection
- Reply-To analysis
- Sender and recipient relationship analysis
- Display-name mismatch detection
- Received-header analysis
- Routing anomaly detection
- Domain alignment analysis
- Spoofing indicators
- Authentication confidence scoring
- Header timeline generation
The module shall produce structured authentication and routing findings that can be incorporated into the overall threat assessment.
Sender Identity & Trust Module
The Sender Identity & Trust Module shall evaluate whether the apparent sender is consistent with known identities and organizational relationships.
Features:
- Sender identity profiles
- Sender trust scoring
- Known-contact recognition
- First-time sender detection
- Trusted-domain recognition
- Sender behavior history
- Display-name impersonation detection
- Executive impersonation detection
- Contact impersonation detection
- Organization identity validation
- Sender relationship mapping
- Sender identity graph generation
- Lookalike sender detection
The module shall support local trust information without requiring centralized collection of user contacts.
Domain Intelligence Module
The Domain Intelligence Module shall analyze domains associated with senders, links, redirects, and embedded content.
Features:
- Domain reputation analysis
- Domain age analysis
- Newly registered domain detection
- Lookalike domain detection
- Homograph detection
- IDN attack detection
- Suspicious subdomain detection
- Domain relationship analysis
- Domain consistency checks
- Organization-domain validation
- IP reputation analysis
- Domain threat scoring
The module shall support replaceable and configurable intelligence sources.
Link Analysis Module
The Link Analysis Module shall inspect URLs without requiring the user to open them.
Features:
- URL extraction
- URL normalization
- Destination analysis
- Redirect-chain inspection
- URL shortening analysis
- Suspicious parameter detection
- Encoded URL detection
- Domain mismatch detection
- Displayed-link versus destination comparison
- Malicious-domain detection
- Phishing URL pattern detection
- Link reputation scoring
- Safe link inspection
Link analysis shall occur within controlled network and security boundaries.
Threat Intelligence Module
The Threat Intelligence Module shall correlate EmailXpose findings with available threat intelligence.
Features:
- Threat-feed integration
- Known malicious domain matching
- Known malicious URL matching
- IP reputation
- Phishing campaign fingerprinting
- Malware indicator matching
- Scam pattern matching
- Threat signature matching
- Emerging threat identification
- Threat intelligence correlation
- Local threat database support
- Community threat intelligence support
Threat intelligence sources shall be optional and replaceable.
Natural Language Analysis Module
The Natural Language Analysis Module shall analyze the semantic and linguistic characteristics of email content.
Features:
- Text classification
- Semantic analysis
- Intent classification
- Entity recognition
- Suspicious phrase detection
- Phishing language detection
- Scam language detection
- Spam classification
- Credential request detection
- Payment request detection
- Sensitive-information request detection
- Semantic similarity analysis
- Writing-style analysis
- Language identification
- Multilingual analysis
- AI-generated content indicators
The module shall support multiple models and allow models to be replaced without redesigning the core application.
Behavioral & Psychological Analysis Module
The Behavioral & Psychological Analysis Module shall identify social engineering and manipulation patterns within messages.
Features:
- Urgency detection
- Fear-based persuasion detection
- Authority pressure detection
- Emotional manipulation detection
- Reward manipulation detection
- Threat-based persuasion detection
- Social engineering analysis
- Coercion indicators
- Pressure tactics
- Isolation tactics
- False scarcity detection
- Artificial deadline detection
- Secrecy requests
- Unusual behavioral requests
- Tone analysis
- Tone-shift detection
- Writing-style anomaly detection
- Possible compromised-account indicators
Findings shall be presented as probabilistic indicators rather than definitive statements about the sender's psychological state or intentions.
Scam & Fraud Detection Module
The Scam & Fraud Detection Module shall identify patterns associated with fraudulent communications.
Features: