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AI-Driven Phishing Detection through Persuasion Analysis

Phishing is one of the most prevalent cyberthreats, increasingly relying on social engineering rather than technical exploits. Modern phishing campaigns are often targeted, multilingual and fast-evolving, exploiting behavioural and psychological tactics including false urgency, authority impersonation and the imitation of trusted sources. Traditional detection approaches based on signatures, sender reputation or static rules struggle to identify these novel attacks, particularly when infrastructure and content are previously unseen. Solution: An AI-driven phishing detection solution was deployed as an augmentation layer into email security operations at Santander Global SOC. The solution combines multiple analytical capabilities, including domain analysis, brand and visual inspection and advanced semantic analysis. A key differentiator is an internally trained, multilingual LLM designed to identify psychological persuasion traits embedded in phishing messages, such as scarcity, authority, reciprocity and commitment. By focusing on semantic intent and human-centric manipulation patterns, the system improves detection of previously unseen, highly targeted phishing campaigns that evade traditional controls.

Impact / Outcome
Overall phishing detection effectiveness improved by at least 10%, while also accelerating threat identification and enabling earlier disruption of social engineering-driven attacks. This shifts phishing detection from indicators of compromise to a human-centric threat analysis paradigm, strengthening cyber resilience.
Key Metrics
10%+ improvement in phishing detection effectiveness
Locations
Europe, Spain
Sector
Financial services
Year published
04 May 2026
Organization involved
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Banco Santander