Pokémon TCG [Sun & Moon: Celestial Storm] - Leaf Charge Theme Deck (Sceptile)
SKU: 62819914756

Pokémon TCG [Sun & Moon: Celestial Storm] - Leaf Charge Theme Deck (Sceptile)

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Description

Pokémon TCG [Sun & Moon: Celestial Storm] - Leaf Charge Theme Deck (Sceptile)Prepare to embark on an exhilarating Pokmon catching journey with the Sun & Moon: Celestial Storm Leaf Charge Theme Deck featuring Sceptile. For those aspiring to catch 'em all, seize the opportunity by clicking 'Add to Cart' and ordering today! This theme deck is a vital step toward completing your Pokmon collection, offering a diverse array of creatures to enhance your arsenal. Part of the Celestial Storm expansion within the broader Sun and Moon

Prepare to embark on an exhilarating Pokémon-catching journey with the Sun & Moon: Celestial Storm - Leaf Charge Theme Deck featuring Sceptile. For those aspiring to catch 'em all, seize the opportunity by clicking 'Add to Cart' and ordering today! This theme deck is a vital step toward completing your Pokémon collection, offering a diverse array of creatures to enhance your arsenal.

Part of the Celestial Storm expansion within the broader Sun and Moon series of the Pokémon TCG, the Leaf Charge theme deck boasts Sceptile as its leader Pokémon. With 2 cards featuring this impressive Pokémon, the deck's strategic prowess revolves around grass and lightning-connected Pokémon. Capitalize on the element of surprise as opponents may underestimate your botanical strength, turning their misjudgment into a distinct advantage.

Within the deck's box, uncover a comprehensive set of components essential for thrilling battles. The 60 Pokémon cards, meticulously selected from the grass and lightning types, form the foundation for engaging gameplay. The back of the box provides a detailed card list, ensuring strategic planning before each challenge. Additionally, discover a card checklist, metallic coin, 2-player playmat with a rulesheet, a code card for online play, a deck box, and damage counters—a complete package for an immersive and competitive Pokémon TCG experience. Harness the power of Sceptile and ignite a storm of Grass and Lightning with the Pokémon TCG: Sun & Moon—Celestial Storm Leaf Charge Theme Deck.

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SKU: 62819914756

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4.3 ★★★★★
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Product Reviews
E
eyal Fishman
Grantham, 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
Natrona Heights, 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
Port Orchard, 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
Port Orchard, US
★★★★★ 5
All OK.
Format: Paperback
All OK.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 23, 2024
E
Eugene
Port Orchard, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on October 14, 2024

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