The Developer's Playbook for Large Language Model Security: Building Secure AI Applications episode artwork

EPISODE · Sep 23, 2025 · 51 MIN

The Developer's Playbook for Large Language Model Security: Building Secure AI Applications

from CyberSecurity Summary · host CyberSecurity Summary

Offers an in-depth look at security concerns surrounding Large Language Models (LLMs), drawing heavily from "The Developer’s Playbook for Large Language Model Security" by Steve Wilson. It presents endorsements highlighting the book's importance for AI developers and security professionals due to the novel risks LLMs introduce. The text outlines various vulnerabilities like prompt injection, sensitive data leakage, and denial-of-wallet attacks, often illustrated with real-world examples such as Microsoft's Tay chatbot incident and the Equifax breach. Additionally, it provides mitigation strategies including zero-trust architectures, robust output filtering, and the use of tools like ML-BOMs for supply chain security. The sources emphasize the rapid evolution of AI capabilities driven by advancements in hardware and open-source models, underscoring the critical need for developers to adopt comprehensive security practices and responsible AI development frameworks like RAISE.You can listen and download our episodes for free on more than 10 different platforms:https://linktr.ee/cyber_security_summaryGet the Book now from Amazon:https://www.amazon.com/Developers-Playbook-Large-Language-Security/dp/109816220X?&linkCode=ll1&tag=cvthunderx-20&linkId=30863b7e73b652e38740dd8f97e5064d&language=en_US&ref_=as_li_ss_tlDiscover our free courses in tech and cybersecurity, Start learning today:https://linktr.ee/cybercode_academy

Offers an in-depth look at security concerns surrounding Large Language Models (LLMs), drawing heavily from "The Developer’s Playbook for Large Language Model Security" by Steve Wilson. It presents endorsements highlighting the book's importance for AI developers and security professionals due to the novel risks LLMs introduce. The text outlines various vulnerabilities like prompt injection, sensitive data leakage, and denial-of-wallet attacks, often illustrated with real-world examples such as Microsoft's Tay chatbot incident and the Equifax breach. Additionally, it provides mitigation strategies including zero-trust architectures, robust output filtering, and the use of tools like ML-BOMs for supply chain security. The sources emphasize the rapid evolution of AI capabilities driven by advancements in hardware and open-source models, underscoring the critical need for developers to adopt comprehensive security practices and responsible AI development frameworks like RAISE.You can listen and download our episodes for free on more than 10 different platforms:https://linktr.ee/cyber_security_summaryGet the Book now from Amazon:https://www.amazon.com/Developers-Playbook-Large-Language-Security/dp/109816220X?&linkCode=ll1&tag=cvthunderx-20&linkId=30863b7e73b652e38740dd8f97e5064d&language=en_US&ref_=as_li_ss_tlDiscover our free courses in tech and cybersecurity, Start learning today:https://linktr.ee/cybercode_academy

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The Developer's Playbook for Large Language Model Security: Building Secure AI Applications

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This episode is 51 minutes long.

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This episode was published on September 23, 2025.

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Offers an in-depth look at security concerns surrounding Large Language Models (LLMs), drawing heavily from "The Developer’s Playbook for Large Language Model Security" by Steve Wilson. It presents endorsements highlighting the book's importance for...

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