Classical models classify Ghana mobile-money scam SMS on a 220-message set
Held-out accuracy, F1 and AUC were 1.00 for Naive Bayes and linear SVM; cross-validated accuracy averaged 92.0% to 96.6%.
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Held-out accuracy, F1 and AUC were 1.00 for Naive Bayes and linear SVM; cross-validated accuracy averaged 92.0% to 96.6%.

Malwarebytes tracks an SMS phishing campaign, active since May 2026, impersonating T-Mobile rewards expiry with 1,000+ templates and 81 rotating domains to lure victims.
ReCAST distills a large teacher model's de-obfuscation ability into smaller models for robust classification of obfuscated Chinese SMS fraud messages.
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