The promise of AI is clear: tools such as OpenAI, Anthropic, and Google’s AI models are revolutionizing how businesses handle everything from customer service to data analysis. But with great power comes great responsibility, and along with that responsibility, a whole host of new risks. One of the most dangerous and rapidly evolving attack vectors against AI models today is prompt injection—an attack where malicious inputs are used to manipulate AI behavior.
When you think of securing your AI, it’s tempting to rely on the AI provider to take care of it for you. However, there are several reasons why depending solely on AI providers to solve vulnerabilities, such as prompt injection, may not be enough. Here’s why having a dedicated AI security layer is critical.
1. AI Providers Focus on Broad Use Cases, Not Your Specific Needs
Anthropic, Google, and OpenAI design AI models to serve a massive variety of use cases, from chatbots to language translation and more. This means their primary goal is to create models that are general-purpose and widely applicable across industries. While they certainly make efforts to improve the security of their models, these improvements are often designed to address broad, common issues.
For example, while OpenAI might focus on blocking commonly exploited vulnerabilities, they’re not specifically tailoring their security for the nuances of your industry, your workflows, or your unique data sensitivity requirements. If you’re in healthcare, finance, or any industry with strict compliance and security standards, you’ll need granular controls that go beyond what the AI provider offers.
2. Security Fixes from Providers Can Be Slow
Even though major AI providers are constantly improving security, their release cycles and update schedules are often slow. Fixes are typically reactive, meaning they may address vulnerabilities only after they’ve been exploited in the wild or flagged by researchers. If you’re relying solely on AI providers to patch these vulnerabilities, you could be left exposed for extended periods while waiting for an update.
3. No Unified Security Across Multiple Providers
It’s increasingly common for businesses to use multiple AI models from different providers, often for different purposes. For example, you might use Google’s AI for analytics, OpenAI’s GPT for natural language processing, and Anthropic’s AI for ethical decision-making. Each of these models could have different security vulnerabilities and different timelines for addressing them.
4. Lack of Custom Control and Transparency
When you rely on AI providers for security, you often rely on black-box models. You don’t have full visibility into how they handle security, manage data, or respond to specific prompt injection scenarios. This lack of transparency makes it difficult to audit or build confidence in the security of your AI deployment.
5. Customizability for Your Business Needs
AI providers offer generic security solutions that don’t always allow for customization. For example, if you want to redirect technical queries to internal models or block specific behaviors like job searching, most AI providers won’t offer that flexibility.
6. Future-Proofing Your AI Security
As AI continues to evolve, so will attack vectors like prompt injection. AI providers will certainly work to address emerging risks, but they have a large, general user base to serve. Their security priorities may not always align with your specific use cases or industry regulations.
Conclusion
Relying solely on AI providers for security leaves your business vulnerable to specific risks, including prompt injection attacks. While providers focus on broad use cases, your organization needs tailored protections to address unique workflows, compliance standards, and evolving threats. Implementing a dedicated AI security layer ensures greater control, faster response times, and the flexibility to adapt to future challenges—empowering you to safeguard your AI investments effectively.
Trevor Welsh is the VP of Products at WitnessAI and a seasoned executive in the AI and cybersecurity sectors. With over two decades of experience in product leadership and innovation, Trevor has been instrumental in shaping cutting-edge security solutions for some of the most critical areas in technology, including cloud security and edge computing. Trevor is a prolific inventor with over 35 patents and pending patents, underscoring his deep expertise in risk management, data loss protection, and large-scale AI-driven security solutions.
The opinions expressed in this post belong to the individual contributors and do not necessarily reflect the views of Information Security Buzz.