dames sportful srk top mouwloze jersey zwart
SKU: 94348893176

dames sportful srk top mouwloze jersey zwart

Sale price$58.49 Regular price$64.99
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Description

dames sportful srk top mouwloze jersey zwartHet Sportful SRK W Top shirt is een mouwloos fietsshirt voor dames, speciaal ontworpen voor de warmste zomerdagen. Of je nu onder de brandende zon bergpassen beklimt, ontspannen fietstochten maakt of zomerse gravelritten doet: dit shirt biedt absolute bewegingsvrijheid en maximale ventilatie. Dit shirt uit de veelzijdige SRK collectie combineert de onmisbare functies van een echt fietsshirt (zoals achterzakken en een ritssluiting) met de lichtheid van

Het Sportful SRK W Top-shirt is een mouwloos fietsshirt voor dames, speciaal ontworpen voor de warmste zomerdagen. Of je nu onder de brandende zon bergpassen beklimt, ontspannen fietstochten maakt of zomerse gravelritten doet: dit shirt biedt absolute bewegingsvrijheid en maximale ventilatie.

Dit shirt uit de veelzijdige SRK-collectie combineert de onmisbare functies van een echt fietsshirt (zoals achterzakken en een ritssluiting) met de lichtheid van een sport-tanktop. Het is gemaakt van een ultraluchtdoorlatende technische stof die zweet onmiddellijk afvoert om je lichaam koel te houden, terwijl het tegelijkertijd bruine strepen op je armen beperkt.

 

Zakken de achterzakken niet in omdat het shirt mouwloos is? Sportful heeft een elastische steunband in de taille verwerkt, gecombineerd met een stevige stofstructuur aan de achterkant. Je spullen (energierepen, telefoon, sleutels) blijven goed tegen je lichaam aanliggen en het shirt kruipt niet omhoog, zelfs niet als je voorovergebogen over het stuur fietst.

Heeft dit shirt een ingebouwde sportbeha? Nee, dit model is ontworpen als een lichtgewicht mouwloos shirt en heeft geen ingebouwde beha. Dit geeft je de volledige vrijheid om je gebruikelijke sportbeha eronder te kiezen en te dragen, afhankelijk van de mate van ondersteuning die je persoonlijk nodig hebt.

Hoe valt de SRK Top qua maat? In lijn met de filosofie van de SRK-collectie heeft dit shirt een Regular Fit-pasvorm (nauwsluitend maar comfortabel). Het volgt de lijnen van het lichaam zonder het compressie-effect van race-shirts. Je kunt je gebruikelijke maat kiezen voor een comfortabele pasvorm die geschikt is voor lange zomerse tochten.

 

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SKU: 94348893176

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4.3 ★★★★★
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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
Lake Worth, 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
San Leandro, 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
Waukegan, US
★★★★★ 5
All OK.
Format: Paperback
All OK.
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Reviewed in the United States on August 23, 2024
E
Eugene
Chelsea, 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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