downalisa
SKU: 23482592250

downalisa

$24.25 $26.95
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No.2 Bestseller on asantecanada.ca >

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Description

downalisaThe Gildan 5000 heavy cotton tee is a dependable classic made for everyday wear and custom printing. Its 100% cotton fabric is tightly knit to give designs sharper detail and long lasting color. The seamless body eliminates side seams for a smoother fit, while reinforced shoulders keep the shirt in shape through repeated washes. Durable, comfortable, and print friendly, the Gildan 5000 is a trusted staple for personalized apparel. Disclaimer: Due to

The Gildan 5000 heavy cotton tee is a dependable classic made for everyday wear and custom printing. Its 100% cotton fabric is tightly knit to give designs sharper detail and long-lasting color. The seamless body eliminates side seams for a smoother fit, while reinforced shoulders keep the shirt in shape through repeated washes. Durable, comfortable, and print-friendly, the Gildan 5000 is a trusted staple for personalized apparel.

Disclaimer:
- Due to the fabric properties, the White color variant may appear off-white rather than bright white.


.: The Gildan 5000 is made with medium fabric (5.3 oz/yd² / 180 g/m²) consisting of 100% cotton, offering year-round comfort with lasting durability.
.: The classic fit of this shirt ensures a comfy, relaxed wear while the crew neckline adds that neat, timeless look that can blend into any occasion, casual or semi-formal.
.: The tear-away label means a scratch-free experience with no irritation or discomfort whatsoever.
.: Made using 100% US cotton that is ethically grown and harvested. Gildan is also a proud member of the US Cotton Trust Protocol ensuring ethical and sustainable means of production. This blank tee is certified by Oeko-Tex for safety and quality assurance.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
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Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 23482592250

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4.9 ★★★★★
Based on 696 reviews
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Product Reviews
E
eyal Fishman
Birmingham, 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
Dallas, 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
Los Angeles, 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
Charlottesville, US
★★★★★ 5
All OK.
Format: Paperback
All OK.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 23, 2024
E
Eugene
Houston, 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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