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K&N Universal Rubber Filter-Round Tapered 6in Flange ID x 9in Base OD x 6.625in Top OD x 7.5in HK&N Black Universal Air Filters are made from Dryflow oil free synthetic media. These low restriction clamp on air filters are designed and manufactured for a wide variety of applications. When dirty they can be easily washed using K&N synthetic air filter cleaner. This Part Fits: Year Make Model Submodel 2007 2010 Chevrolet Silverado 2500 HD LT 2007 2010 Chevrolet Silverado 2500 HD LTZ 2007 2010 Chevrolet Silverado 2500 HD WT 2007 Chevrolet Silverado
K&N Black Universal Air Filters are made from Dryflow oil-free synthetic media. These low restriction clamp-on air filters are designed and manufactured for a wide variety of applications. When dirty they can be easily washed using K&N synthetic air filter cleaner.This Part Fits:
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| 2007-2010 | Chevrolet | Silverado 2500 HD | LT |
| 2007-2010 | Chevrolet | Silverado 2500 HD | LTZ |
| 2007-2010 | Chevrolet | Silverado 2500 HD | WT |
| 2007 | Chevrolet | Silverado 2500 HD Classic | LS |
| 2007 | Chevrolet | Silverado 2500 HD Classic | LT |
| 2007 | Chevrolet | Silverado 2500 HD Classic | WT |
| 2007 | Chevrolet | Silverado 3500 Classic | LS |
| 2007 | Chevrolet | Silverado 3500 Classic | LT |
| 2007 | Chevrolet | Silverado 3500 Classic | WT |
| 2007-2010 | Chevrolet | Silverado 3500 HD | LT |
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| 2013-2016 | Ford | F-350 Super Duty | Platinum |
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| 2011-2016 | Ford | F-350 Super Duty | XLT |
| 2007-2010 | GMC | Sierra 2500 HD | SLE |
| 2007-2010 | GMC | Sierra 2500 HD | SLT |
| 2007-2010 | GMC | Sierra 2500 HD | WT |
| 2007 | GMC | Sierra 2500 HD Classic | SL |
| 2007 | GMC | Sierra 2500 HD Classic | SLE |
| 2007 | GMC | Sierra 2500 HD Classic | SLT |
| 2007 | GMC | Sierra 2500 HD Classic | WT |
| 2007-2010 | GMC | Sierra 3500 HD | SLE |
| 2007-2010 | GMC | Sierra 3500 HD | SLT |
| 2007-2010 | GMC | Sierra 3500 HD | WT |
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Based on 5 reviews
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5
A good book for Cyber Professionals
Format: Paperback
A very good book, I absolutely love how it gives security professionals much needed AI security insights.
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Reviewed in the United States on January 16, 2026
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5
In-depth and highly technical!
Format: Paperback
"Adversarial AI Attacks, Mitigations, and Defense Strategies" by John Sotiropoulos is a must-have resource for cybersecurity professionals navigating the complexities of AI security.
This book is an incredibly in-depth guide that tackles the intricate details of defending AI systems from adversarial attacks. Itβs highly technical, making it an excellent choice for those with a solid background in cybersecurity, machine learning, and system administration. Sotiropoulos doesnβt shy away from the details, providing comprehensive code examples, system admin settings, and scripts that are invaluable for practical implementation.
One of the standout aspects of this book is its coverage of both predictive and generative AI. This dual focus ensures that readers are well-equipped to handle security challenges across different AI applications. Whether you're dealing with machine learning models in a predictive context or exploring the relatively newer field of generative AI, this book has you covered.
If youβre looking for a technical, hands-on approach to securing AI systems, this book is an essential addition to your library.
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Reviewed in the United States on August 12, 2024
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4
Good and thorough!
Format: Paperback
I was amazed to see a thick book arriving in the package and spent quite some time reading this. The book is so hands-on. I build agentic systems at work and going through these concepts felt good. My only complaint is that the code snippets are not up to date for which I had to edit my code several times.
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Reviewed in the United States on May 9, 2026
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5
Amazing book
Format: Paperback
Excelent product
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Reviewed in the United States on November 4, 2025
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5
solid read with walk through
Format: Paperback
There is limited material on this topic and I am about 4 chapters in and I have enjoyed the walkthrough on setting up a lab as the background... will update as I continue through the book.
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Reviewed in the United States on October 18, 2024