Securing the Future of A2P Messaging: Why RBM Security is a CPaaS Imperative

RCS Business Messaging (RBM) is poised to revolutionize how brands and consumers connect. Analysts predict massive market growth, but it hinges on one critical factor: security. Unless consumers trust messages received through RBM, they will choose other channels to communicate with brands, and the growth will not happen. To ensure trust, security tools are needed to filter out spam and block falsified sender agents.

The move to RBM and rich media in messaging comes as AI has become generally available as a tool for defenders and offenders. When spammers use AI to exploit rich media, their campaigns become even more intrusive, which requires CPaaS providers to meet the new challenges with similar means. CPaaS providers and aggregators must recognize that securing RBM is not just a best practice; it’s an absolute imperative for maintaining user trust, brand reputation, and the overall viability of the RBM ecosystem.

The Shifting Sands of Responsibility

The move to RBM will significantly shift security responsibility compared to A2P SMS. Unlike SMS, where mobile network operators (MNOs) have greater visibility and control, they will have no line of sight for RBM content. CPaaS providers are now on the front lines, responsible for managing content filtering, adhering to regulations, guiding brands toward compliance, and actively combating emerging threats.

This responsibility is amplified by regulatory scrutiny. Telecom services like SMS, MMS, and RBM fall under the watchful eye of national regulatory authorities (NRAs). These bodies are concerned with maintaining critical infrastructure, ensuring economic stability, and protecting consumers from spam and misinformation. While proprietary messaging services can control their platforms, NRAs hold MNOs (and, by extension, CPaaS providers) accountable for the content transmitted through their networks. Failure to comply can result in severe penalties, including sending restrictions, suspension from network termination, and hefty fines.

The Limits of Sender Verification and Vetting

One security feature RBM adds to aid CPaaS providers in combating spoofing and building trust is sender verification. Verified senders are essential for consumers to trust the sender and the message and for the brand to protect its reputation. However, verification alone isn’t a silver bullet. Clever spammers can still impersonate legitimate brands, creating a false sense of security for recipients.

Moreover, the vetting processes designed to curb unsolicited communications is not foolproof. Content can drift into a non-compliant domain, inappropriate content can be sent by vetted brands, rogue elements can falsify information to get approval or impersonate legitimate brands, and accounts can be hijacked.

A massive challenge for a robust vetting process that can ensure the level of customer knowledge required to keep destructive elements out is the sheer scale of potential RBM senders. With potentially millions of businesses adopting RBM, thoroughly vetting each becomes almost impossible. Spammers can exploit this by creating fake business profiles or falsifying information.

It is essential that CPaaS providers protect the integrity of the vetting process by enforcing compliance and filtering out spam and campaigns that miss the mark for what is appropriate and compliant.

The Offensive Side of AI: Empowering Spammers in RBM

While AI offers tremendous potential for improving user experiences and enhancing security, it also presents new opportunities for malicious actors. Spammers increasingly leverage AI-powered techniques to automate their operations, craft more convincing phishing messages, and evade detection by traditional security systems. This poses a significant threat to the RBM ecosystem, as AI can amplify the scale and sophistication of spam campaigns, making detection and blocking more challenging.

One primary way spammers can use AI is to generate highly personalized and targeted phishing messages. By analyzing user data from various sources, AI can automatically create convincing fake profiles, tailor message content to individual recipients’ interests and preferences, and even mimic the writing style of trusted contacts. This makes it more likely that recipients will fall for the scam and click on malicious links or provide sensitive information.

AI can also be used to evade detection by traditional spam filters. Analyzing the patterns and characteristics of blocked messages helps AI learn to adapt message content and delivery methods to avoid triggering spam filters. This includes techniques such as generating variations of spam messages, using obfuscation techniques to hide malicious content, and distributing spam messages across multiple senders to avoid being blocked.

The Defensive Side of AI: Seeing Through the Bluff

AI can not only generate spam; it can also be used to detect spam and senders of spam. Some examples of how AI can be used to fight back against spam are:

• AI-driven message categorization can understand the purpose and intent of a message, such as whether it is a delivery notification or a spam message, and add it to the appropriate category. This not only helps filter spam but can also be used to ensure compliance. For example, it can flag messages as marketing and then let a rule set decide if it is compliant to deliver a marketing message to a specific recipient at that time.
• Non-compliant image content is a significant risk with rich media messaging, but this can be controlled through AI-powered restricted image detection. It can interpret image content and let a rule set decide whether it is compliant to send to the specific audience.
• OCR is a special case for image detection. Spammers often hide text in images to avoid text-based spam filters. With OCR capabilities, text can be extracted from images and scanned for inappropriate content or malicious URLs.

AI is significantly more agile at detecting spam messages than traditional methods like keyword identification and fingerprinting, as it can analyze patterns and context in a more comprehensive manner. While spammers can rapidly generate countless variations of spam content using AI, conventional methods struggle to keep up with the overwhelming influx of rich media spam. In contrast, AI-powered spam-filtering solutions provide the necessary scale and adaptability to combat these evolving threats effectively.

There are plenty of methods spammers can use to exploit AI and rich media, but there are equally many opportunities to use AI to fight back. In essence, the rise of AI-powered spam requires an equally sophisticated AI-powered defense.

The Imperative of Continuous Improvement and AI

One of the core security problems to solve for RBM is that the rich media and features that make it a better messaging service also create advantageous conditions for misuse. Combined with AI, which can generate personalized and credible media content at scale, this becomes extraordinarily problematic.

For business interest and regulatory compliance, CPaaS providers must integrate messaging firewalls with AI-driven detection and filtering mechanisms to safeguard against sophisticated attacks and ensure the ongoing security and integrity of the RBM ecosystem.

Securing RBM is not just about preventing spam and fraud; it’s about preserving the long-term viability of this promising communication channel. By embracing their responsibilities, investing in robust security measures, and collaborating with industry partners, CPaaS providers can ensure that RBM fulfills its potential as a trusted and valuable tool for brands and consumers alike. The future of A2P messaging depends on it.

Read more in our handbook about RBM security for CPaaS providers: Securing Messaging in the Age of Rich Media and Artificial Intelligence,  or check out Enea’s messaging firewall for CPaaS providers.