Search results for "offensive security using python"
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Advanced Python Programming
Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge librariesKey FeaturesBenchmark, profile, and accelerate Python programs using optimization toolsScale applications to multiple processors with concurrent programmingMake applications robust and reusable using effective design patternsBook DescriptionPython's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages.In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level.This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models.The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming.You'll also understand the common problems that cause undesirable behavior in concurrent programs.Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable.By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.What you will learnWrite efficient numerical code with NumPy, pandas, and XarrayUse Cython and Numba to achieve native performanceFind bottlenecks in your Python code using profilersOptimize your machine learning models with JAXImplement multithreaded, multiprocessing, and asynchronous programsSolve common problems in concurrent programming, such as deadlocksTackle architecture challenges with design patternsWho this book is forThis book is for intermediate to experienced Python programmers who are looking to scale up their applications in a systematic and robust manner. Programmers from a range of backgrounds will find this book useful, including software engineers, scientific programmers, and software architects.
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Python Scripting for Computational Science
With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language. All the tools and examples in this book are open source codes. This third edition features lots of new material. It is also released after a comprehensive reorganization of the text. The author has inserted improved examples and tools and updated information, as well as correcting any errors that crept in to the first imprint.
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Blue Team Handbook: Incident Response
As cyberthreats grow and infrastructure evolves, organizations must prioritize effective, dynamic, and adaptable incident response. Based on the original print bestseller, Blue Team Handbook: Incident Response is now available for the first time in a digital format. This trusted and widely used field guide for cybersecurity incident responders, SOC analysts, and defensive security professionals distills incident response essentials into a concise, field-ready format. Author Don Murdoch draws on decades of real-world experience in incident response and cybersecurity operations to provide actionable guidance and sample workflows you can immediately apply in your own work. Whether you're investigating an alert, analyzing suspicious traffic, or strengthening your organization's IR capability, you'll find this updated edition an essential resource for hands-on practitioners. Understand how modern adversaries operate and recognize common indicators of compromise in networksAnalyze network traffic with common tools to identify and investigate suspicious activityExecute structured incident response procedures and follow a clear response planConduct basic forensic analysis on both Windows and Linux systemsUse proven methodologies and tools to carry out effective, dynamic incident response
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Programming with Python
Based on the latest version of the language, this book offers a self-contained, concise and coherent introduction to programming with Python. The book’s primary focus is on realistic case study applications of Python. Each practical example is accompanied by a brief explanation of the problem-terminology and concepts, followed by necessary program development in Python using its constructs, and simulated testing. Given the open and participatory nature of development, Python has a variety of incorporated data structures, which has made it difficult to present it in a coherent manner. Further, some advanced concepts (super, yield, generator, decorator, etc.) are not easy to explain. The book specially addresses these challenges; starting with a minimal subset of the core, it offers users a step-by-step guide to achieving proficiency.
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Head First Python
What will you learn from this book? Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you'll quickly grasp Python's fundamentals by working with built-in data structures and functions. You'll build your very own web app, which--once it's ready for prime time--runs in the cloud. You'll learn how to wrangle data with Python, scrape data from the web, feed data to pandas, and interact with databases. This third edition is a complete learning experience that will help you become a bona fide Python programmer in no time. What's so special about this book? If you've read a Head First book, you know what to expect: a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. With this book, you'll learn Python through a multisensory experience that engages your mind--rather than a text-heavy approach that puts you to sleep.
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AI Security Engineering
Design, Build, and Secure Dependable AI Systems Across the Enterprise Lifecycle AI is rapidly becoming part of core enterprise systems but most security programs were not designed for systems that are probabilistic, adaptive, and increasingly autonomous. AI Security Engineering provides a foundational, engineering-first playbook for designing, operating, and scaling secure AI systems across the enterprise lifecycle. Written by Ashish Rajan, a CISO advising Fortune 500 organizations on AI security, this book focuses on security for AI systems not AI used as a security tool. It examines how AI changes traditional security assumptions and how organizations must adapt their architectures, pipelines, governance models, and operating practices to manage AI risk effectively in production environments. Rather than focusing on tools or point solutions, AI Security Engineering applies security engineering principles to modern AI systems. It covers AI threat models, secure AI pipelines, runtime detection and incident response, governance and compliance at scale, and the emerging challenges of agentic and multi-model systems. Readers are guided through how to evolve existing security programs to support AI-enabled applications without slowing delivery or becoming the “department of no”. This book shows how to: Design and operate secure AI systems across their full lifecycle from architecture and delivery to operations and scaleDefend production AI applications against adversarial, emergent, and agent-driven threatsEmbed governance and risk controls into AI pipelines using engineering-first approachesOperate AI security in dynamic environments, including third-party and agentic systemsBalance regulatory compliance, system performance, and engineering velocity CISOs seeking strategic clarity for AI security investments, security architects designing resilient systems, and engineers responsible for operating AI in production will find this book a durable reference for building dependable AI systems at enterprise scale.
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Deceptive Intelligence
This book explores the transformative impact of artificial intelligence on social engineering and testing, offering a timely and necessary guide for navigating one of the most pressing challenges in modern cybersecurity. AI is not only revolutionizing how attackers exploit vulnerabilities but also how defenders test and strengthen their systems. With over 80% of data breaches attributed to human error or social engineering, and phishing responsible for 36% of successful cyberattacks, the stakes for organizations are higher than ever. The rise of AI tools capable of automating these attacks has introduced new complexities, making it critical for organizations to adopt advanced strategies to test their resilience. The book's core mission is to equip cybersecurity professionals with the tools, knowledge, and frameworks to counter these AI-driven threats ethically and effectively. Readers will discover how to simulate sophisticated AI-enabled attacks, from deepfake impersonations to multi-channel phishing campaigns, all while respecting ethical boundaries. Practical applications are emphasized, such as leveraging open-source tools to mimic real-world attack scenarios and using AI to analyze human vulnerabilities. It also provides actionable guidance on building defenses and training programs that reflect the rapidly evolving threat landscape. As AI tools like ChatGPT, deepfake generators, and voice synthesis platforms become increasingly accessible, their misuse in crafting malicious campaigns is accelerating. Research shows that 83% of organizations experienced a successful phishing attack in 2022, while incidents involving deepfakes rose 300% compared to the previous year. Meanwhile, the widespread availability of personal information on social media has created fertile ground for AI-driven reconnaissance, making targeted social engineering easier and more effective than ever. This book directly addresses these challenges, showing how to test against these threats before attackers can exploit them. What makes this book essential is its focus on preparing organizations for the future of security testing. It goes beyond describing threats by offering a blueprint for integrating AI into their existing workflows, enabling defenders to think like attackers and stay one step ahead. From actionable case studies to ethical frameworks, it provides a comprehensive resource for testing and improving defenses in environments where the line between human and machine deception grows increasingly blurred. This is not just a book about threats--it's a call to action for organizations to evolve their approach to security and embrace AI's potential to strengthen their defenses. What You Will learn: How AI reshapes social engineering and testing, acquiring the knowledge to simulate advanced threats such as AI-generated phishing, deepfakes, and automated reconnaissance.How to develop skills to implement open-source AI tools for crafting ethical attack simulations, te
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Introduction to Python and Computer Programming
This book introduces Python programming language and fundamental concepts in algorithms and computing. Its target audience includes students and engineers with little or no background in programming, who need to master a practical programming language and learn the basic thinking in computer science/programming. The main contents come from lecture notes for engineering students from all disciplines, and has received high ratings. Its materials and ordering have been adjusted repeatedly according to classroom reception. Compared to alternative textbooks in the market, this book introduces the underlying Python implementation of number, string, list, tuple, dict, function, class, instance and module objects in a consistent and easy-to-understand way, making assignment, function definition, function call, mutability and binding environments understandable inside-out. By giving the abstraction of implementation mechanisms, this book builds a solid understanding of the Python programming language.
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Python for Bioinformatics
In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language.This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics, but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases, the Anaconda Python distribution, graphical libraries like Bokeh, and the use of Github for collaborative development.
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