Email Security,
Forensically Analyzed.
Upload suspicious emails for automated AI threat detection, header forensics, and geolocation intelligence. Secure your inbox with precision.
Phishing Attempt Detected
Suspicious URL found in email body. Sender domain mismatch detected.
Precision Intelligence for Cyber Defense
Eliminate blind spots. Our platform converts raw email headers into actionable forensic evidence, providing real-time threat scoring and deep-dive analysis.
Total volume of suspicious email traffic processed by our engine.
Verified precision rate for identifying phishing and malicious payloads.
Neural decision-making latency for real-time threat classification.
Confirmed malicious indicators neutralized by our security stack.
End-to-End Threat Detection
Automated forensic intelligence workflow designed for rapid incident response and email security analysis.
System extracts metadata, routing paths, and payload signatures while maintaining strict isolation.
Logistic regression models analyze text features and header anomalies to detect malicious intent.
Final assessment includes evidence summaries, risk scoring, and recommended defensive actions.
Advanced Threat Detection Capabilities
MAILFORCE provides automated forensic analysis, AI-driven threat scoring, and protocol verification to secure your email infrastructure.
Explainable Threat Scoring
Our ML engine classifies emails with transparent risk scores. Identify phishing, spam, or suspicious payloads using explainable feature-based classification.
Transparent ML-based risk assessment for phishing, spam, and suspicious email payloads.
Automated SPF, DKIM, and DMARC validation to detect spoofing and sender anomalies.
Deep header parsing and evidence preservation for incident response and forensic investigation.
Approximate network intelligence mapping for observed IP addresses in email headers.
Ready to secure your email infrastructure?
Discover how MAILFORCE provides automated forensic intelligence and threat detection.
Transparent Threat Scoring Framework
Every analyzed email receives a calibrated threat rating from 0 to 100. Rather than delivering an unexplained single score, MAILFORCE reveals the exact heuristic weights and evidentiary factors shaping the security assessment.
| Score Range | Threat Level | Heuristic Weight | Primary Indicators | Triage Protocol |
|---|---|---|---|---|
| 00–29 | Low Risk | 15% Max Combined | Valid SPF/DKIM/DMARC, clean URLs, benign TF-IDF text features | Normal : PASS |
| 30–59 | Medium Risk | 35% Weighted Factor | Reply-To mismatch, unauthenticated relay, low-urgency marketing phrasing | Quarantine : REVIEW |
| 60–79 | High Risk | 60% Cumulative Impact | Domain spoofing flag, newly registered domain link, failed DKIM/DMARC | Automated : CONTAIN |
| 80–100 | Critical Threat | 85–100% Deterministic | Credential harvesting form, high AI phishing score, malicious IP relay | Immediate : BLOCK |
Individual Factor Contributions
Mathematical allocation across multi-layer static and ML telemetry pipelines
Evaluates token distribution, urgency syntax, and deceptive context via trained Scikit-learn classifier.
Evaluates redirection chains, punycode characters, and newly registered host reputations.
Correlates envelope sender discrepancies with cryptographic domain validation policies.
Discovers forged Received headers, private network discrepancies, and relay irregularities.
Inspects double extensions, script payloads, and nested archive heuristics without execution.
Initialize Forensic Analysis in Seconds.
Upload suspicious EML files to our AI-powered platform. Extract technical evidence, map IP geolocation, and generate professional threat reports for your incident response team.
Rapid Forensic Sandbox
Initialize secure analysis environments for suspicious EML files with automated threat isolation.
Automated Threat Scoring
Real-time risk assessment (0-100) using ML-driven indicators for phishing and spoofing detection.
Centralized Evidence Ledger
Immutable storage for all extracted headers, IP intelligence, and forensic investigation timelines.