SKU: 34673721347
lorcana set 9 starter decks

lorcana set 9 starter decks Disney Lorcana Archazia's Island Starter Deck An Inventive Pair Ruby /

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Description

lorcana set 9 starter decks Disney Lorcana Archazia's Island Starter Deck An Inventive Pair Ruby /Explore the enchanting world of Lorcana in this extraordinary trading card game. Discover stunning original artwork that beautifully captures the essence of beloved Disney characters. Dive into a welcoming gameplay experience designed for casual players and newcomers, but also offers strategic depth to satisfy competitive pros. Disney Lorcana can be played by 2 or more players ages 8 and up and takes about 10 minutes per player. Embark on an epic

  • Explore the enchanting world of Lorcana in this extraordinary trading card game. Discover stunning original artwork that beautifully captures the essence of beloved Disney characters.
  • Dive into a welcoming gameplay experience designed for casual players and newcomers, but also offers strategic depth to satisfy competitive pros. Disney Lorcana can be played by 2 or more players ages 8 and up and takes about 10 minutes per player.
  • Embark on an epic journey to build your ultimate deck, collect rare cards, and challenge fellow Disney enthusiasts.
Each starter deck includes:
- 60 cards, including 2 foil cards
- 11 damage counters
- 1 paper playmat
- 1 paper tracker token
- 1 quickstart rulebook
- 1 bonus booster pack of 12 random cards


Disney Lorcana Single-Player Decks include everything you need to start playing against another player. Through these decks, you'll get a taste of the rich story and varied characters of Disney Lorcana.

There are two Single-Player Decks available for Disney Lorcana: Archazia’s Island. Each deck has 60 cards and features two ink colors with distinct play styles. If you’re new to trading card games, or if you want to experience the game with a deck designed and tested by the creators of Disney Lorcana, this is a good place to start.

Victory can be part of your tale with this deck in hand (or paw). Together, Belle – Mechanic Extraordinaire and Beast – Frustrated Designer tinker around with items, tools, and even discarded scrap to engineer a winning strategy. It's what you get when a pretty ingenious mind meets one beast of a brain.
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SKU: 34673721347

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E
eyal Fishman
Waukegan, US
★★★★★ 5
outstanding and highly informative book
Format: Paperback
MAoS - Malware Analysis on Steroids: Fighting Malware to the Death - Real-World Threats and Reverse Engineering Tactics by Uriel Kosayev is an outstanding and highly informative book. This is the second book I’ve read from him, after Antivirus Bypass Techniques, and once again I found the content to be extremely practical, well-structured, and insightful. Uriel has a way of explaining complex malware analysis and reverse engineering concepts in a way that is both approachable and deeply technical. The real-world tactics and examples make it not just a book you read once, but a reference you’ll return to often. Without a doubt, another excellent resource—I’m giving it 5 stars.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on September 10, 2025
A
Verified Purchase
Arthur Donkers
Omaha, US
★★★★★ 4
good
Format: Paperback
Good practical content, quality of images could be improved
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on October 13, 2025
Z
Zachi
Carnegie, US
★★★★★ 5
Essential for Malware Hunters
Format: Hardcover
MAoS - Malware Analysis on Steroids is a clear, practical, and engaging guide to real-world malware threats. It blends hands-on reverse engineering tactics with modern case studies, making it both highly technical and easy to follow. Whether you’re new to malware analysis or a seasoned security pro, this book sharpens your skills and mindset for the fight against today’s threats.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on September 20, 2025
C
Verified Purchase
Cliente Amazon
Lexington, US
★★★★★ 5
All OK.
Format: Paperback
All OK.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 23, 2024
E
Eugene
Grantham, US
★★★★★ 5
Great book on Android malware reverse engineering and detection!
Format: Paperback
This book offers a holistic approach for learning how to deal with malware targeting Android platform. I find this book to be equally interesting to read for both people with little experience in the domain of malware analysis as quick-start guide as well as for experienced reverse engineers who would want to translate their knowledge from malware analysis in other platforms to Android. This book is definitely worth the time reading it. The first half of the book is a great source of information on reverse engineering Android malware. Chapters on categories of Android Malware and examples of the malware in the wild set up the necessary context for the readers and help to better understand why Android malware focuses on certain infection/monetization techniques. It also bring context in the evolution of mitigation and hardening in Android platform. Chapters on static and dynamic analysis are very practical and engaging to read which I probably enjoyed the most in the book. They teach readers how to do reverse engineering of Android malware -- covers tooling, methodologies, hints to look for in the code or binary artifacts when doing reverse engineering. The second half of the book is dedicated to using machine learning techniques for detecting malware. It starts with a concise yet self-contained necessary theoretical background. In my point of view the authors hit a very good balance for making material accurate and comprehensive yet easy to read and follow along for people without extensive background in the field (which is not a trivial thing for math texts). As it is probably impossible to fit all the necessary theoretical material in a single (or even couple of chapters) they text offers references to sources which cover certain topics in-depth -- for those readers who would like to dive deeper in machine learning. Finally, the book wraps with application of the discussed machine learning techniques to certain malware families.
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Reviewed in the United States on October 14, 2024

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