In 2022 InterContinental Hotel Group breach compromised customer names and addresses across Regent, Crown Plaza, and Holiday Inn properties. The attack spread from Starwood's compromised data to IHG's network of over 6,000 hotels in 100+ countries, demonstrating how quickly threats cascade through hospitality ecosystems.

Traditional threat intelligence relies on static indicators and manual analysis, approaches that fail against rapidly evolving attacks targeting hospitality organizations. Cybercriminals now use generative AI to craft convincing business email compromise campaigns at scale, creating threats that bypass signature-based detection entirely.

AI transforms threat intelligence into predictive capability. Systems learn normal operational rhythms of property management systems, point-of-sale terminals, and guest networks, then identify anomalies signaling emerging threats. This behavioral approach proves especially valuable in hospitality environments where legitimate activity varies dramatically by season, occupancy, and operational patterns.

AI-powered threat intelligence transforms hospitality security through behavioral pattern analysis, predictive threat modeling, and automated responses.

Hospitality organizations face attack vectors extending beyond traditional enterprise threats, with payment system fraud representing the largest loss category. Cybercriminals target multiple payment touchpoints across reservation systems, point-of-sale terminals, mobile applications, and third-party booking platforms.

Threat methods have evolved beyond signature-based detection capabilities. Modern attackers use AI to develop attack variants faster than traditional security systems can update databases. They exploit extensive IoT environments common in smart hotels, target property management system integrations, and leverage complex vendor relationships characterizing hospitality operations.

Having said that, here are five steps to implement AI-based threat intelligence in hospitality:

Map specific attack vectors across payment processing, property management systems, and vendor relationships before implementing AI threat intelligence.

Identify the three primary attack vectors represent highest risk, whichincludes:

• Business email compromise, which targets financial transactions through convincing communications appearing to come from vendors or executives.

• Vendor email compromise, which exploits extensive supplier relationships where attackers use legitimate vendor accounts and established communication channels.

• Payment system fraud extends beyond credit card fraud to reservation manipulation, loyalty program abuse, and mobile payment exploitation across multiple touchpoints.

Next, establish security baselines by recognizing seasonal patterns, occupancy-driven traffic variations, and legitimate behavioral patterns of guests and staff. This baseline understanding becomes critical for training AI systems to distinguish operational variations from genuine threats.

Platform selection should prioritize capabilities aligned with hospitality's unique operational requirements and compliance obligations. Your platform must integrate seamlessly with property management systems, point-of-sale infrastructure, and guest network architecture without disrupting operational efficiency.

Essential requirements include PCI DSS compliance, behavioral analysis establishing baselines for property operations, automated threat hunting, pattern recognition adapting to seasonal variations, predictive analytics identifying emerging threats, and full NIST Cybersecurity Framework alignment. The platform should provide capabilities for managing, detecting, responding to, and recovering from ransomware events critical to operations where system availability directly impacts guest services and revenue.

Train AI threat intelligence systems with hospitality-specific operational patterns to ensure accuracy and minimize false positives. Provide data from property management systems, point-of-sale operations, guest network usage, and employee access patterns.

Configure AI to learn normal device connection patterns during check-in and check-out periods, legitimate Wi-Fi usage baselines, and mobile payment interaction patterns varying by property type, guest demographics, and seasonal factors.

Model shift-based access patterns for front desk operations, housekeeping schedules, management oversight, and maintenance activities. Include vendor ecosystem data incorporating normal communication patterns with suppliers, contractors, providers, and booking platforms to detect compromised communications.

Implement tiered automated responses maintaining operational continuity while preventing service disruption. Your response framework should distinguish between threats requiring immediate automated action and those requiring human validation.

Hospitality industry’s automated response system should balance security protection with operational continuity:

• Tier 1 Automated Responses: Address threats with zero guest impact through immediate network rerouting, targeted credential restrictions, and surgical malware isolation that maintains system availability.

• Tier 2 Semi-Automated Responses: Handle minimal-risk threats requiring human validation before action, including property management anomalies, payment irregularities, and suspicious vendor communications that need verification before blocking legitimate business processes.

Business continuity has risen to the top cybersecurity priority in hospitality. Response automation must prevent security incidents from cascading into operational disruptions affecting guest services, reservation systems, or payment processing capabilities.

The response system should provide rich contextual information enabling rapid decision-making, including detailed threat analysis, potential impact on specific operational systems, and recommended response actions with clear business impact assessments.

Continuously adapt AI-driven threat intelligence to remain effective against evolving threat actors and tactics. Hospitality's unique operational patterns demand ongoing refinement of detection algorithms, baseline adjustments for seasonal variations, and integration of new threat intelligence sources.

Implement Continuous Threat Exposure Management as your foundational methodology. This approach prioritizes resilience through ongoing threat assessment and adaptation to increasing regulatory pressures. Continuously evaluate threat exposure across all operational systems from property management platforms to guest-facing applications.

Additionally, incorporate feedback loops from actual security incidents, near-miss events, and operational disruptions. Performance metrics should align with business resilience: guest service disruptions prevented, payment system availability maintained, and compliance audit findings addressed.

Abnormal addresses hospitality's unique security challenges through behavioral analysis distinguishing between legitimate operational communications and sophisticated threats. The platform's adaptive email security uses machine learning and real-time threat intelligence to detect threats before they reach critical operational systems.

Abnormal's vendor email compromise solution provides essential protection against supplier relationship exploitation targeting hotels, restaurants, and travel companies. The system's human behavior AI detects fraud patterns in legitimate-appearing vendor communications, protecting against payment redirection and system access attempts.

Also, the platform integrates seamlessly with existing hospitality technology stacks, providing enhanced protection without disrupting property management systems, reservation platforms, or guest-facing applications.

Choice Hotels, faced sophisticated attacks bypassing two secure email gateways targeting their hospitality culture of helpfulness.

Abnormal's behavioral AI platform delivered immediate protection:

• 97 attacks on an average stopped every day

• 120+ compromised vendor accounts identified

• 36% reduction in SOC response efforts

• Zero successful attacks since deployment

CISO Jason Stead emphasized the broader impact: "Abnormal delivered the fastest POV time-to-value, by far, that I've ever seen. What we're doing now, especially with Abnormal and RH-ISAC, is banding together to uplift the entire industry."

Read more customer stories or schedule a demo with Abnormal to see how behavioral AI can protect your hospitality operations from email-based threats while maintaining seamless guest experiences.