ISBN: 9798196154553 - prompt injection defense with python: protect llm apps, rag pipelines, ai agents, and tool-calling workflows from real-world prompt attacks (6 risultati)

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  • Lingua: Inglese

    Editore: Independently Published Mai 2026, 2026

    9798196154553

    Serie: Libro 4 di 4 - AI & Law Series

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Condizione: Nuovo

    EUR 64,57

    EUR 35,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Taschenbuch. Condizione: Neu. Neuware - Protect your AI systems from prompt injection attacks before they reach production. Most developers are building LLM apps, RAG pipelines, and AI agents without a real security layer. This book shows you how to fix that with practical Python projects you can build, test, deploy, and turn into paid services. Prompt Injection Defense with Python is a hands-on guide for developers, AI engineers, freelancers, and technical founders who want to secure modern LLM applications using Python 3.11, FastAPI, ChromaDB, SQLite, and Docker. Inside, you will build practical AI security projects such as: - Prompt Firewall API - a FastAPI middleware that detects risky prompts, blocks malicious inputs, and assigns threat scores.- Secure RAG Pipeline - document ingestion with malicious content detection, retrieval validation, and safer context handling.- Agent Approval Gateway - a permission and audit system for AI agents that call sensitive tools and APIs.- Prompt Injection Scanner - a testing library with attack payloads and JSON vulnerability reports.- Security Dashboard - a lightweight monitoring system for attacks, logs, metrics, and incidents using SQLite.This book focuses on real implementation, not theory. You will learn how to design defensive layers around LLM applications, audit vulnerable workflows, monitor suspicious behavior, and create reusable tools that can become portfolio projects, consulting offers, or MicroSaaS products. You will also learn how to package your skills into paid AI security services, including LLM app audits, RAG security reviews, agent risk assessments, and subscription-based security tooling. If you want to build safer AI applications and turn LLM security into a practical business opportunity, this book gives you the projects, architecture, and code patterns to start.…

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798196154553

    Serie: Libro 4 di 4 - AI & Law Series

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    Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    Condizione: Nuovo

    EUR 45,60

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    PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798196154553

    Serie: Libro 4 di 4 - AI & Law Series

    • Brossura
    • Print on Demand

    Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK

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    Condizione: Nuovo

    EUR 42,32

    EUR 4,97 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: Più di 20 disponibili

    PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798196154553

    Serie: Libro 4 di 4 - AI & Law Series

    • Brossura
    • Print on Demand

    Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

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    Condizione: Nuovo

    EUR 67,81

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    Quantità: 1 disponibile

    Paperback. Condizione: new. Paperback. Protect your AI systems from prompt injection attacks before they reach production. Most developers are building LLM apps, RAG pipelines, and AI agents without a real security layer. This book shows you how to fix that with practical Python projects you can build, test, deploy, and turn into paid services. Prompt Injection Defense with Python is a hands-on guide for developers, AI engineers, freelancers, and technical founders who want to secure modern LLM applications using Python 3.11, FastAPI, ChromaDB, SQLite, and Docker. Inside, you will build practical AI security projects such as: Prompt Firewall API - a FastAPI middleware that detects risky prompts, blocks malicious inputs, and assigns threat scores.Secure RAG Pipeline - document ingestion with malicious content detection, retrieval validation, and safer context handling.Agent Approval Gateway - a permission and audit system for AI agents that call sensitive tools and APIs.Prompt Injection Scanner - a testing library with attack payloads and JSON vulnerability reports.Security Dashboard - a lightweight monitoring system for attacks, logs, metrics, and incidents using SQLite.This book focuses on real implementation, not theory. You will learn how to design defensive layers around LLM applications, audit vulnerable workflows, monitor suspicious behavior, and create reusable tools that can become portfolio projects, consulting offers, or MicroSaaS products. You will also learn how to package your skills into paid AI security services, including LLM app audits, RAG security reviews, agent risk assessments, and subscription-based security tooling. If you want to build safer AI applications and turn LLM security into a practical business opportunity, this book gives you the projects, architecture, and code patterns to start. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Lingua: Inglese

    Editore: Independently published, 2026

    9798196154553

    Serie: Libro 4 di 4 - AI & Law Series

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    • Print on Demand

    Da: California Books, Miami, FL, U.S.A.California Books

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    Condizione: Nuovo

    EUR 67,11

    EUR 2,68 spedizione 
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    Quantità: Più di 20 disponibili

    Condizione: New. Print on Demand.

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798196154553

    Serie: Libro 4 di 4 - AI & Law Series

    • Brossura
    • Print on Demand

    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    Condizione: Nuovo

    EUR 47,33

    EUR 44,18 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 1 disponibile

    Paperback. Condizione: new. Paperback. Protect your AI systems from prompt injection attacks before they reach production. Most developers are building LLM apps, RAG pipelines, and AI agents without a real security layer. This book shows you how to fix that with practical Python projects you can build, test, deploy, and turn into paid services. Prompt Injection Defense with Python is a hands-on guide for developers, AI engineers, freelancers, and technical founders who want to secure modern LLM applications using Python 3.11, FastAPI, ChromaDB, SQLite, and Docker. Inside, you will build practical AI security projects such as: Prompt Firewall API - a FastAPI middleware that detects risky prompts, blocks malicious inputs, and assigns threat scores.Secure RAG Pipeline - document ingestion with malicious content detection, retrieval validation, and safer context handling.Agent Approval Gateway - a permission and audit system for AI agents that call sensitive tools and APIs.Prompt Injection Scanner - a testing library with attack payloads and JSON vulnerability reports.Security Dashboard - a lightweight monitoring system for attacks, logs, metrics, and incidents using SQLite.This book focuses on real implementation, not theory. You will learn how to design defensive layers around LLM applications, audit vulnerable workflows, monitor suspicious behavior, and create reusable tools that can become portfolio projects, consulting offers, or MicroSaaS products. You will also learn how to package your skills into paid AI security services, including LLM app audits, RAG security reviews, agent risk assessments, and subscription-based security tooling. If you want to build safer AI applications and turn LLM security into a practical business opportunity, this book gives you the projects, architecture, and code patterns to start. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…