Artificial Intelligence (AI) systems are becoming the crown jewels of many companies.
From digital maps to website chatbots, products that incorporate AI are revolutionizing the customer experience, streamlining operations, and creating vast new revenue opportunities. At the same time, internal AI systems for creating, collecting, organizing, analyzing, and utilizing data are helping companies drive innovation, automate routine tasks, and gain competitive advantages. AI is quickly becoming central to everything companies do, internally and externally. In fact, 80% of executives surveyed believe automation can be applied to any business decision. As AI becomes increasingly valuable, however, it also becomes a prime target for cyber attacks.
With the risk and reward of AI both skyrocketing, securing these critical assets must be a top priority. The future of your business may depend on it.
The AI Security Threat Landscape: More Complex Than You Think
You might assume that traditional cybersecurity measures are sufficient to protect AI systems—but it’s a bigger battle than it appears.
While AI-specific threats like data poisoning, model extraction, and adversarial attacks can compromise the integrity and functionality of AI models, these aren't the only concerns. The broader security landscape surrounding AI systems is generally more complex and often overlooked.
The vulnerabilities extend far beyond the AI models themselves:
Many AI systems are accessed via APIs, which can be vulnerable to various attacks like injections, authentication bypass, or denial of service.
Compromising the tools or libraries used in AI development can give attackers a foothold in your systems.
Employees with access to AI systems are potential targets for phishing or other social engineering tactics.
Cloud infrastructure that many AI systems rely could be misconfigured; disgruntled employees or contractors with privileged access could intentionally sabotage or exfiltrate AI assets.
This complex threat landscape requires a comprehensive and specialized approach to AI security that goes beyond traditional cybersecurity measures to address the unique challenges posed by AI systems and their surrounding infrastructure.
Bottom Line: If you’re going to adopt AI, you must update cybersecurity as well. Otherwise, the risks far outweigh the rewards.
Best Practices to Completely Protect Your Technology
Protecting your AI systems requires a comprehensive security approach. While the AI models your systems are built on, like Llama or GPT-4, come out of the box with model protection, your proprietary AI technology is only as strong as your surrounding security infrastructure. Following these best practices will ensure that your entire IT infrastructure is robust enough to protect your AI systems:
24/7 Monitoring and Threat Detection: Continuously monitor your AI systems and supporting infrastructure to identify and respond to any threats promptly.
AI-Specific Vulnerability Assessments: Consistently evaluate your AI models, training pipelines, and deployment environments to pinpoint and address potential weaknesses.
Validate Cloud Infrastructure: Conduct a thorough assessment of cloud environments hosting AI workloads to ensure proper configuration, access controls, and compliance with security best practices.
Secure DevOps Integration: Rigorously implement security best practices throughout the AI development lifecycle, from data collection to model deployment.
Access Control and Identity Management: Utilize robust systems to ensure that only authorized personnel can access sensitive AI assets and data.
Partnering for a Secure AI Future
While AI systems themselves are valuable targets, the surrounding infrastructure presents an even more critical security challenge. As AI becomes increasingly central to business operations, it's crucial to recognize that protecting your AI assets goes far beyond securing the models themselves.
At NopalCyber, we take a holistic approach to AI security. Our process isn't just about safeguarding AI models; it's about fortifying the entire infrastructure that supports and interacts with your AI systems. We specialize in identifying and addressing vulnerabilities across the entire attack surface, providing comprehensive protection that extends well beyond AI models.
Our team of experts is equipped to help you navigate this complex landscape, offering tailored solutions that address the unique security challenges posed by your specific AI ecosystem. From MXDR and cloud security to implementing robust access controls and conducting regular vulnerability assessments, we ensure that every aspect of your AI infrastructure is protected.
Don't let overlooked vulnerabilities in your AI infrastructure leave your IT open to attack. Secure these critical assets to secure your revenue and growth. Partner with NopalCyber to build a safe, resilient AI ecosystem that not only protects your valuable assets but also drives your business forward.
Contact us to explore what AI security looks like at your company.
