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300 Pcs RJ45 Ethernet Connector Cust Cover Network Plug Cover Cap Hat for Cat5e Cat6 Cat7 CAT8 Protector RJ45 Plug Case(Black) in Saudi Arabia

300 Pcs RJ45 Ethernet Connector Cust Cover Network Plug Cover Cap Hat for Cat5e Cat6 Cat7 CAT8 Protector RJ45 Plug Case(Black) Black

SAR 167
Brand
KaiYeA
Weight
0.6 kg
ColorBlack
– 1 +

Special Features

  • Multi-Hazard Network Port Barrier Protection: Fully block moisture and oxidation from invading idle Ethernet interfaces. Keep internal metal contacts clean and intact to avoid unstable signal, disconnection and network lag caused by corrosion
  • Pull-Tab Humanized Disassembly Structure: Independent reserved pull tab on each plug enables quick plugging and unplugging by hand without tools. It will not scratch or tangle nearby cables and adjacent ports during operation
  • Soft Non-Abrasive Fit Structure: Flexible smooth texture closely fits the port inner cavity. It stays firmly inserted during daily equipment operation and movement, without scraping the shell or metal shrapnel of network hardware
  • Standard Universal Interface Matching: Standard shaping fits all mainstream common female network ports. Compatible with switches, routers, patch panels, network adapters and other wired communication equipment of all brands
  • Long-Term Stable Maintenance Accessory: Reusable structure maintains consistent tightness after repeated plugging and pulling. It extends the service life of network equipment and cuts extra maintenance troubles for office, home and data center networks

Description

Lightweight Space-Saving Auxiliary Fitting: Mini lightweight outline occupies no extra space after installation. Neatly shield idle ports to keep server racks and wiring cabinets tidy and orderly.
Material: Plastic
Color: As shown in the picture
Quantity: 300 pieces

Note:
1. The real color of the item may be slightly different from the pictures shown on website caused by many factors such as brightness of your monitor and light brightness.
2. Please allow slight manual measurement deviation for the data.

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