Palo Alto Networks has announced the rollout of its latest Secure AI by Design product portfolio, aiming to secure organizations’ GenAI usage and development of enterprise AI applications by providing visibility, control, and protection specific to AI, addressing new risks and threats. As businesses increasingly integrate AI, the portfolio enables them to confidently build and use AI-powered apps, while also prioritizing the integrity of AI security frameworks from development to deployment.
Why: The need for securing AI applications has become increasingly important as businesses continue to integrate AI and LLMs into their operations. With employees adopting AI applications at a rapid pace and organizations across various industries gaining a competitive edge through AI-powered applications, the Secure AI by Design portfolio aims to securely enable AI deployments. While the promises of AI are significant, it’s essential to acknowledge the associated risks with equal emphasis in order to realize its full potential. Bad actors are using AI to ramp up the scale of attacks, so it is important that organizations are proactive in their defense.
How: Organizations will be equipped to create a secure AI ecosystem that prioritizes the integrity of AI security frameworks from development to deployment. Businesses can fully harness the potential of AI without compromising security through the following use cases:
- Securely enable GenAI applications: With the growing trend of employees using GenAI apps for business purposes, AI Access Security enables organizations to use AI tools with confidence. It gives security teams full visibility, application and data access controls, and continuous data risk monitoring.
- Fortify AI supply chain: Businesses must be aware and rectify against possible risks. With Prisma Cloud AI Security Posture Management (AI-SPM), organizations can secure their AI ecosystem by identifying vulnerabilities and misconfigurations in models, applications and resources. It improves compliance and minimizes data exposure, thus improving the integrity of your AI security framework.
- Protect enterprise AI applications: It is critical for organizations to see every component of their AI app ecosystem— including AI applications, models, inference and training datasets. AI Runtime Security is designed to help solve this, and protect against evolving zero-day and AI-specific threats, such as data leakage from AI models and applications, and safeguard models from misuse and attacks.
