SMS remains a widely used and reliable communication channel across industries, from financial services and healthcare to e-commerce and public sector operations.
However, with this scale comes risk. According to a recent industry report, more than 50% of service providers expect SMS fraud to increase in 2025, driven by evolving fraud techniques and vulnerabilities in digital systems.
As businesses continue to rely on A2P messaging for critical communications, the threat landscape is evolving just as rapidly. A recent report indicates that over 50% of service providers expect SMS fraud to increase in 2025, a trend driven in part by the growing sophistication of fraud tactics like SMS pumping.
SMS pumping, also referred to as artificially inflated messaging traffic, is a scheme in which bad actors exploit test or verification processes (often tied to OTP or 2FA systems) to generate large volumes of illegitimate SMS messages. These are often routed through expensive or revenue-sharing destinations, resulting in unexpected charges for the sender, typically a business, financial institution, or digital service provider.
This activity is a form of Artificially Inflated Traffic (AIT) and is increasingly recognized as a key concern in the realm of SMS fraud. While the message content may appear legitimate, the intent behind the traffic is fraudulent, designed solely to trigger charges and profit intermediaries or rogue network operators.
While SMS pumping may resemble normal messaging activity, it is engineered to exploit gaps in A2P delivery systems and monetization models. Below, we explore how this fraud works and why traditional filters often fail to prevent it.
Fraudsters typically target SMS-triggering features in mobile apps and websites, such as:
These workflows often trigger SMS messages with no additional verification, making them easy entry points for fraud.
Using bots or scripts, attackers can send thousands of requests to trigger SMS messages in quick succession. Since the triggers come from legitimate flows, this abuse often bypasses detection by standard fraud filters.
Fraudsters profit by routing these SMS messages through premium-rate or revenue-sharing destinations, particularly in regions with International Revenue Share Fraud (IRSF) exposure. In these cases, a portion of the message fee is returned to the carrier or aggregator involved in the fraud.
This turns normal A2P message delivery into a billing attack, with the enterprise footing the bill for traffic it never intended to send.
Standard telecom and enterprise security measures are often designed to stop spam or phishing, not behavioral volume abuse. SMS pumping often goes unnoticed until billing anomalies or usage spikes surface, by which time significant financial damage may have occurred.
Without real-time fraud intelligence, AI-powered detection, and advanced fraud analytics, identifying the intent behind seemingly legitimate traffic can be a challenge.
AIT-related fraud, including SMS pumping, continues to challenge the integrity of A2P messaging ecosystems. These threats are difficult to detect using conventional monitoring methods and require more than manual reviews or traditional blacklisting, as they often mimic legitimate user activity.
This has prompted a more advanced approach to detection, including IRSF (International Revenue Share Fraud) intelligence, real-time fraud analytics, and AI-based mobile fraud prevention tools.
By continuously analyzing SMS routes and monitoring for revenue-sharing destinations, IRSF detection technology helps identify high-risk channels used in AIT schemes. Route scoring flags suspicious carriers before fraudulent traffic causes damage.
This type of telecom security intelligence is essential for identifying unusual traffic flows, particularly from niche regions or underregulated jurisdictions, where SMS pumping is commonly monetized.
AI-based fraud prevention tools leverage machine learning models to detect behavioral anomalies in real time. These systems can distinguish between legitimate user actions and automated or scripted abuse, even when traffic originates from typical entry points.
AI enables messaging platforms to detect:
This allows businesses to automate threat response while minimizing false positives.
Fraud analytics engines aggregate data across users and regions to identify suspicious trends over time. Unlike static filters, these platforms adapt to emerging attack methods and generate actionable insights. They support:
These insights are critical for both mobile fraud prevention and broader business fraud prevention strategies.
The most effective way to prevent AIT is to stop fraudulent traffic before messages are sent. Real-time fraud intelligence platforms integrate with your SMS delivery pipeline to inspect traffic patterns continuously.
These platforms can:
A proactive strategy to combat Artificially Inflated Traffic (AIT) starts with reliable, accurate, and continuously updated datasets designed to identify fraudulent destinations and behavioral patterns.
Neural Technologies’ IRSF Defense Solution includes:
Frequently Asked Questions (FAQs)