What is Seat Spinning? The AI-Driven Bot Attack Sabotaging Airline Revenue

Takeaways

• Seat spinning is automated seat holding that disrupts real availability.

• It distorts pricing, demand signals, and customer experience.

• CAPTCHA does not stop it because bots avoid the checkpoint.

• Detection must focus on booking behavior and purchase intent.

• STCLab identified clear automated patterns that never reach payment.

• Precise blocking protects revenue while avoiding customer friction.

Searching for airline tickets during school breaks or national holidays often leads to a strange experience.
Seats appear available but disappear during payment.
Sold out flights suddenly show open seats again hours later.
Prices move up and down repeatedly within short time of period.

This pattern has become too common to dismiss as simple user congestion.
Across the travel industry, this behavior is now recognized as a structured phenomenon known as seat spinning.

What Is Seat Spinning

Seat spinning is a sophisticated bot attack where automated scripts hold airline seats in a "pending" state without ever completing the purchase. By exploiting the 15-to-20-minute checkout window, bots keep seats off the market, creating artificial scarcity that forces airline algorithms to raise prices for real customers.

If you’ve ever tried to book a flight, seen "only 2 seats left," and then watched the price jump 30% after a page refresh, you might have been a victim of seat spinning.

As of 2026, seat spinning has become one of the most disruptive bot activities in the travel industry. But what exactly is it, and how does it affect your wallet?

Why Seat Spinning Is More Harmful for Airlines

Airline reservation systems are structurally sensitive environments.

• Seats are limited inventory

• Pricing changes in real time based on demand and search patterns

• The reservation flow involves multiple stages before payment

In this environment, seat spinning does more than create traffic.
It interferes with the very mechanisms airlines use to decide demand, availability, and pricing.
This makes the issue relevant not only for security teams but also for commercial, revenue management, digital, and distribution teams.

Why Traditional Security Fails: The "CAPTCHA Myth"

Many airlines rely on CAPTCHA as a primary defense, but in the context of seat spinning, it is largely ineffective.

• Structural Evasion: Bots initiate seat spinning before the payment or login stages where CAPTCHAs are typically triggered.

• Behavioral Mimicry: Advanced bots simulate human-like search and fare calculation phases, avoiding the high-friction checkpoints.

• Friction Paradox: Increasing CAPTCHA intensity often frustrates genuine travelers while automated scripts simply pivot to a different part of the reservation flow.

Key Insight: CAPTCHA determines if a user looks human, but it cannot determine if a user has purchase intent.

The Data Behind Seat Spinning

STCLab applied its BotManager analytics to airline reservation traffic and identified clear patterns.
Approximately 30% of booking related traffic showed automated behavior.

These bots repeatedly accessed:

• seat search

• fare calculation

• reservation entry

But almost none of these flows continued to the payment stage.
In other words, they occupied seats but did not generate revenue.

This pattern aligns with Imperva’s How Bots Affect Airlines report:

• 59% of Travel Site Visits: Attributed to bots globally.

• 43% Bad Bot Rate: Airline-specific traffic significantly exceeds the cross-industry average for malicious bot activity.

• Asia Pacific airlines suffer more due to long no cost hold windows

• seat spinning activity intensifies as departure dates approach

The effect is visible.
Flights appear full even when many seats were never purchased.
When the hold window expires, seats suddenly reappear, often too late for optimal pricing or customer confidence.

How Seat Spinning Affects Airlines

Revenue Loss

Bots hold seats for extended periods, preventing real customers from purchasing them.
As a result, airlines lose the opportunity to sell these seats at the right time and at the right price.

Customer Experience Issues

Passengers see flights marked as full or overpriced.
This reduces trust when availability fluctuates within hours.

Operational Distortion

"Look-to-book" ratios spike, giving revenue management teams false demand signals and skewed data.

Left unattended, seat spinning degrades both business performance and customer perception.

Moving Beyond Blocking: A Behavioral Bot Mitigation Strategy

Seat spinning cannot be solved by simple blocks or traditional security tools.
Effective mitigation requires analyzing behavior across the entire booking flow instead of looking at individual requests.

1. Intent-Based Detection

Instead of blocking IPs, STCLab BotManager analyzes the entire session. It identifies repetitive seat-search loops and fare recalculations that deviate from genuine browsing patterns.

2. Monitoring the "Hold and Release" Cycle

Effective mitigation requires tracking how often a specific entity (or group of IPs) holds a seat without progressing to payment. Identifying these patterns allows airlines to release "spun" seats back into the inventory in real-time.

3. Virtual Waiting Rooms & Inflow Control

By combining bot detection with a virtual waiting mechanism, airlines can control traffic bursts during high-demand periods (like holiday sales), ensuring that real humans are prioritized over automated scripts.

STCLab Airline Bot Mitigation Case Study

STCLab analyzed real airline booking domains and found that 29.65% of traffic was bot generated, even though only a small portion of IPs looked suspicious. These automated flows repeatedly:

• Checked seat availability
• Recalculated fares
• Entered the booking flow without progressing
• Repeated the cycle at high speed

Traditional tools like CAPTCHA or simple IP blocking could not stop these patterns.

How BotManager Helped

STCLab’s BotManager detects bots based on booking behavior, not only network signals.
This allowed airlines to identify:

• Seat search and fare calculation loops
• Automation timing patterns
• Excessive or repeated URL sequences
• Multi ID usage from a single source

By blocking only the non purchasing automated flows, airlines reduced unnecessary load by about 30% while protecting real customers.

Conclusion

When airline seats repeatedly disappear and reappear, the cause may not be ordinary congestion.
Automated reservation flows that hold seats without purchasing them can create significant distortion in availability, pricing, and customer experience.

Understanding seat spinning reveals:

• why CAPTCHA does not solve the problem

• why purchase intent matters more than human verification

• why booking flows must be analyzed stage by stage

This article is an introduction to that perspective.
As automated activity grows across the global travel industry, airlines need more precise tools that protect both revenue and passenger experience.