Livia | Elegante en veelzijdige badmode
SKU: 802842494

Livia | Elegante en veelzijdige badmode

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Description

Livia | Elegante en veelzijdige badmodeElegante en comfortabele badmode Ontdek het perfecte badpak voor vrouwen die stijl en comfort willen combineren. Dit eendelige badpak is ontworpen om de vrouwelijke figuur te accentueren, met een rok die elegante bedekking biedt en een vleugje vrouwelijkheid toevoegt. Ideaal voor dagen aan het strand of in het zwembad, dit badpak is een must have voor elke zomer. 4 REDENEN WAAROM JE HET BADPAK LIVIA NODIG HEBT Stijl: Elegant ontwerp dat je figuur

Elegante en comfortabele badmode

Ontdek het perfecte badpak voor vrouwen die stijl en comfort willen combineren. Dit eendelige badpak is ontworpen om de vrouwelijke figuur te accentueren, met een rok die elegante bedekking biedt en een vleugje vrouwelijkheid toevoegt. Ideaal voor dagen aan het strand of in het zwembad, dit badpak is een must-have voor elke zomer.

4 REDENEN WAAROM JE HET BADPAK LIVIA NODIG HEBT

  • Stijl: Elegant ontwerp dat je figuur accentueert.
  • Comfort: Zachte en ademende stoffen voor een uitstekende pasvorm.
  • Veelzijdigheid: Geschikt voor verschillende gelegenheden, van strand tot zwembad.
  • Bedekking: De rok biedt extra bedekking zonder afbreuk te doen aan de vrouwelijkheid.

Specificaties

  • Materialen: Hoogwaardige en ademende stoffen.
  • Beschikbare kleuren: Diverse elegante kleuren.
  • Maten: Beschikbaar in verschillende maten om aan elk lichaam aan te passen.
  • Verzorgingsinstructies: Handwassen en in de schaduw drogen.

Maattabel :

Alpha Maten Borstomtrek (cm/in) Tailleomtrek (cm/in) Gewicht (Kg/lbs)
XS - S 78-88 cm / 31-35 in 63-76 cm / 25-30 in 48-60 Kg / 105-132 lbs
M 88-99 cm / 35-39 in 68-83 cm / 31-35 in 58-70 Kg / 124-154 lbs
L 99-106 cm / 39-42 in 91-101 cm / 36-40 in 68-80 Kg / 149-176 lbs
XL 106-116 cm / 42-46 in 101-109 cm / 40-43 in 78-90 Kg / 171-198 lbs
2XL 116-127 cm / 46-50 in 109-119 cm / 43-47 in 88-100 Kg / 194-220 lbs
3XL 127-143 cm / 50-53 in 119-129 cm / 47-51 in 95-105 Kg / 209-231 lbs

📌 Houd rekening met een tolerantie van (+ of -) 1/2 punt in de metingen en kies bij twijfel een maat groter.

📞 Heb je hulp nodig? Neem gerust contact met ons op!

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Exchange/Return Notes
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SKU: 802842494

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E
eyal Fishman
Fort Morgan, 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
Phoenix, 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
Belleville, 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
Fort Morgan, US
★★★★★ 5
All OK.
Format: Paperback
All OK.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 23, 2024
E
Eugene
Fort Morgan, 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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