Hospitality security and IT teams are under huge amounts of pressure to protect guest data, ensure system uptime, and comply with regulations like PCI DSS. Meanwhile, hotels, casinos, cruise lines, and resorts face growing cyber threats, from guests abusing open Wi-Fi networks to attacks targeting point-of-sale (POS) systems. Disconnected systems and manual processes make it easy for security gaps to go unnoticed. A single oversight, like an unmonitored account or an unpatched payment server, can lead to service disruptions, data breaches, and hefty fines under data protection laws. 

Kindo bridges these gaps through the power of intelligent automation. It integrates with your identity providers, property management and payment systems, and network monitoring tools, then applies large language models (LLMs) to analyze and act on real-time data. Kindo is an AI-native platform built from the ground up for technical operations teams. 

In practice, this lets your team offload toil and respond faster, while maintaining full control. Kindo combines orchestration, tool integrations, and deep policy enforcement to help operators respond to incidents, remediate vulnerabilities, harden environments, secure identity and access, and automate end-to-end workflows, exactly what hospitality security engineering demands. 

Below are three workflows we’ll teach you how to automate for hospitality security:

1. Detect and Report Guest Wi-Fi Abuse

Free Wi-Fi is a standard amenity, but an open or poorly segmented guest network can invite trouble. Guests (or attackers posing as guests) might exploit hotel Wi-Fi for malicious activity, effectively masking behind the hotel’s IP address. For example, a guest could download pirated content or host illegal sites, launch phishing campaigns, or even scan for vulnerabilities on the hotel’s internal network. This not only puts other guests and internal systems at risk, but can also land the organization in legal or regulatory trouble if criminal acts are traced back to its network. The infamous Marriott breach showed how long an intruder can linger undetected (in that case, attackers maintained access for four years, compromising over 500 million guest records. Many hospitality operators lack visibility into what’s happening on guest Wi-Fi beyond basic bandwidth metrics. Without active monitoring, abuse can go unnoticed for months, giving attackers a foothold or allowing illicit use that damages the brand.

How the Workflow Works

1. A Kindo workflow with an API action step can be scheduled to periodically pull logs and alerts from your guest network infrastructure. It might use API calls to retrieve connection logs, DNS queries, and traffic summaries from a cloud-managed wireless controller (like Cisco Meraki or Ruckus) or from a firewall separating the guest network. This provides a dataset of recent guest device activities, like IP/MAC addresses, sites or domains accessed, bandwidth usage, and any security events triggered (e.g., intrusion detection alarms).

2. Kindo’s WhiteRabbitNeo LLM analyzes the aggregated Wi-Fi data for signs of misuse or attacks. We prompt the model with known abuse scenarios: “detect large sustained downloads, access to known malicious domains, port scans or sweeps, and attempts to reach internal IP ranges from the guest segment,” for example. Unlike a static filter, the AI can reason about context. It will label each suspected abuse case with a reason: “Device X potentially running BitTorrent (excessive bandwidth to known P2P endpoints)” or “Device Y scanning the internal network.”

3. The final step formats the findings into a clear report. Each row could include the device identifier (IP or MAC, or assigned guest ID), timestamp, and a description of the suspected abuse, along with a severity rating. Kindo uses an LLM to generate brief, plain-language explanations for each incident. For instance, “Guest device 10.1.20.5 triggered 500+ port scan attempts within 5 minutes.” Because it’s structured data, the team can easily sort by severity or filter by date. This report serves as both an actionable list and an audit log of how the guest network is being used.

Value of Automation

By actively monitoring guest Wi-Fi, hotels and resorts can stop minor incidents from becoming major breaches. Automated detection means if a guest is engaging in illicit or dangerous activity, the security team is alerted with evidence, rather than finding out weeks later via an abuse complaint. This not only protects internal systems from spillover attacks, but also helps preserve the property’s reputation and legal compliance. Importantly, automation relieves IT staff from manually sifting through enormous logs; instead, they get a concise report that distills signal from noise (no false alarm spam). Many hotels only realized the need for strict Wi-Fi monitoring after high-profile incidents. With Kindo, even lean teams can enforce a zero-tolerance policy on network abuse 24/7. All suspicious incidents are documented, creating an audit trail that demonstrates due diligence in protecting guests and systems.

2. Flag Suspicious Logins on Shared Machines

Hospitality environments often rely on shared workstations and POS terminals like front-desk PCs that are used by all shifts, restaurant register screens, concierge kiosks, etc. This operational reality can lead to password sharing and blurred accountability, especially in high-turnover roles. Unfortunately, it also creates a ripe opportunity for misuse. A malicious insider or someone who stole a password might log into a cash register after hours, and it would look like just another employee session. If staff forget to log out or use weak credentials, an unauthorized person could literally walk up to a logged-in terminal and access sensitive systems or customer data. PCI DSS compliance adds further urgency: the standard requires unique user IDs (requirement 8) and daily review (requirement 10) of access logs for anomalies. If suspicious access isn’t being flagged, the organization not only risks a breach but could also fail its compliance obligations.

How the Workflow Works

1. The workflow begins by pulling authentication logs from all relevant sources. For instance, it can query Active Directory or the hotel’s identity provider (e.g. Microsoft Entra ID/Azure AD or Okta) for recent login events on key machines. It also retrieves local Windows Security Event logs from POS terminals and shared PCs. This yields a timeline of who logged into what device, when, and whether the attempt was successful or failed. We can also integrate contextual data: for example, import employee shift schedules from a workforce management system, or tag each login with the location of the device. By the end of this step, Kindo has a consolidated view of user login activity on systems.

2. Kindo’s WhiteRabbitNeo LLM analyzes the compiled login events to spot anything out of the ordinary. The AI is prompted with the organization’s context and rules: “Front desk agents typically work 8am-6pm; flag logins outside those hours. Each user should only be logged in to one POS at a time; flag if the same account appears on two devices concurrently. Flag more than 5 failed logins for any account in an hour. Flag logins from new devices or locations for a given user.” Because the model understands typical attack patterns and insider behaviors, it can go beyond hard rules. For example, it might notice “User A logged into the Hotel Lobby PC and a back-office server within 2 minutes”. This is impossible without credential sharing. Each suspicious event is identified with a brief explanation. This approach catches subtle anomalies a simple script might miss.

3. The final step is to generate a report of all flagged login anomalies. Each entry lists details such as the username, device or system accessed, timestamp, and the reason it was flagged. Kindo can prioritize these by severity. For example, a successful login by an ex-employee account would be critical, whereas a single after-hours login might be medium. Because the workflow runs continuously, the team is essentially getting an automated watchguard on logins. There’s no need for an analyst to manually pore over Windows event logs or export data from Active Directory. Kindo delivers a concise list of the anomalies to focus on.

Value of Automation

Implementing this workflow means no suspicious login goes unseen. In many hospitality IT setups, login monitoring is ad-hoc or reactive, which attackers know how to exploit. With Kindo, the moment someone’s account is behaving oddly – be it a cybercriminal using stolen credentials or an employee abusing access – the issue is flagged and can be responded to before damage is done. This dramatically shrinks dwell time of attackers and reduces the chance of a minor credential leak turning into a full breach. It provides a reliable, timestamped audit trail that the security team is monitoring all access to systems in the cardholder data environment. PCI DSS explicitly recommends using automated mechanisms for log review. This is exactly what Kindo delivers. For engineers, this automation frees up countless hours that would otherwise be spent writing ad-hoc scripts or manually checking logs across dozens of machines (an error-prone process at best).

3. Catch and Fix PCI Compliance Issues Automatically

Handling credit card data is central to hospitality, from hotel bookings to restaurant charges, so PCI DSS compliance is not optional. Non-compliance can lead to fines ranging from $5,000 to $100,000 per month, especially if a data breach occurs while standards aren’t met. Beyond fines, a failure to secure card data can result in lawsuits, loss of the ability to process cards, and irreparable reputation damage. Unfortunately, maintaining PCI compliance is easier said than done. The standard comprises 12 major requirements and nearly 400 test procedures, covering everything from network segmentation and encryption to password policies and audit logs. In a hotel or casino environment, this means a huge range of systems (ie. PMS databases, POS terminals, booking websites, on-prem servers, third-party integrations) all need to be configured and maintained according to strict rules. It only takes one forgotten setting or lapse to put the organization out of compliance (and at risk). To truly be secure, properties need to actively find and fix PCI issues as soon as they arise, not just during annual audits.

How the Workflow Works

1. This workflow regularly collects the latest information about systems in the cardholder data environment (CDE). It uses an API action step to fetch results from vulnerability scanners and configuration management tools. For example, if the organization uses Qualys or Nessus, the workflow pulls the latest scan report for all servers that store or process credit card info. These reports include detected vulnerabilities, missing patches, open ports, and compliance checks. In addition, the workflow can query system APIs or run scripts for specific configuration data (e.g. checking Windows policy settings on POS machines, pulling firewall rule sets to verify network segmentation, or querying anti-virus consoles for the status of endpoint protection).

2. Now Kindo’s flagship LLM, WhiteRabbitNeo, steps in to analyze the collected data against PCI DSS controls. The AI has context on PCI standards, and it examines each finding or configuration item. Essentially, it asks: “Does this represent a PCI violation or risk?”. For instance, if the vulnerability scan shows a severity flaw on a payments database that’s been open for 60 days, the model flags that as non-compliant (PCI requirement 6 - timely patch management) and high priority. If it finds that a database or S3 bucket containing credit card data isn’t encrypted, that’s a violation of PCI requirement 3 (protect stored cardholder data). A default admin account still enabled? Violation of PCI requirement 2 (secure configurations). Because the LLM is knowledgeable about real-world threats and compliance, it can also assess risk. The output of this step is essentially an AI-curated list of compliance issues, each mapped to the relevant PCI control and with an explanation.

3. After identification, the workflow generates a report. This report itemizes each compliance issue that was identified, and notes the outcome: “Issue: POS terminal Register-3 missing antivirus or “Issue: Unpatched vulnerability CVE-2025-1234 on Webserver”. In essence, it’s an audit trail of problems identified. This report can be stored centrally and even forwarded to compliance officers or IT management regularly. It demonstrates continuous compliance effort: every week there’s a document of exactly what was checked and how any deviation could be addressed. This is incredibly useful for PCI preparation. Come audit time, you can produce evidence of an ongoing PCI maintenance process, not just a one-time audit scramble.

Value of Automation

Automating PCI compliance checks yields huge benefits for hospitality engineering teams. First and foremost, it lowers the risk of a breach. Issues like unpatched systems or default credentials are some of the most common pathways attackers use. By closing these gaps promptly, you harden your defenses and cut off easy attack vectors. Secondly, this workflow saves enormous manual effort and reduces human error. Traditionally, maintaining PCI compliance means running periodic scans, compiling spreadsheets of findings, chasing different teams to implement fixes, and hoping nothing falls through the cracks. It’s a labor-intensive process that might involve hundreds of line items. With Kindo, most of that toil is offloaded to an intelligent agent.

Ready to Automate Your Hospitality Security Workflows?

Kindo gives security and IT teams the power to automate workflows across identity, network, and infrastructure, using LLMs that understand your environment and act intelligently. Whether you're hunting threats, tightening access, or proving compliance, Kindo helps you move faster and with more confidence.

By leveraging an AI platform that’s built for security operations,with a proprietary LLM that understands adversaries and agentic execution to handle tasks, you can secure your hospitality business against threats while reducing overhead.

Take the next step towards resilient, AI-driven security.

See Kindo in action. Book a demo or start building your first workflow today. Your guests, your staff, and your business will thank you for it.