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    Home»Development»Learn how to build security into AI

    Learn how to build security into AI

    July 16, 2025

    Artificial Intelligence is changing how we build software, but it also introduces brand new security risks. If you’re a developer or security professional stepping into the world of AI, how do you make sure your applications are safe?

    We’ve just published a new course on the freeCodeCamp YouTube channel that will teach you how to build security into AI. The course was created by security expert Robert Herbig.

    Here’s a quick look at what you’ll learn:

    • AI vs. Traditional App Security: Understand why securing an AI model isn’t the same as securing a standard web app.

    • Threat Modeling for AI: Learn how to identify potential weaknesses in your AI systems, from poisoned training data to supply chain attacks.

    • Input & Output Risks: Dive into specific attack vectors like prompt injection and adversarial examples, and learn how to prevent sensitive data leaks.

    As Robert says, “Security must be a foundational layer in AI development, not an afterthought.”

    Watch the full course now on the freeCodeCamp YouTube channel (1-hour watch).

    Source: freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More 

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    Description : Kyverno is a policy engine designed for cloud native platform engineering teams. Prior to versions 1.13.5 and 1.14.0, it may happen that policy rules using namespace selector(s) in their match statements are mistakenly not applied during admission review request processing due to a missing error propagation in function `GetNamespaceSelectorsFromNamespaceLister` in `pkg/utils/engine/labels.go`. As a consequence, security-critical mutations and validations are bypassed, potentially allowing attackers with K8s API access to perform malicious operations. This issue has been patched in versions 1.13.5 and 1.14.0.

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