Kaspersky Lab, a leading developer of secure content and threat management solutions, has announced its partnership with TeamF1, the leader in embedded networking and security software solutions for wired and wireless applications.

The technology agreement with TeamF1 enables networking OEMs targeting secure devices for home and business networking to offer superior gateway anti-malware protection to their users.
This partnership expands the array of options available to OEMs by offering functionality to match threats against the latest Kaspersky Lab signatures database in gateway or routers, as well as optionally integrating Kaspersky Lab’s anti-malware engine into TeamF1’s SecureF1rst family of gateway solutions.
With increasing demand for anti-malware checks at the point of Internet access for home and SMB networks, today’s Internet gateway devices need to offer continuous protection from diverse types of malware – from viruses, Trojans, spyware and crimeware to malicious adware and key loggers – as an important part of their unified threat management strategy.
OEMs benefit from TeamF1’s technology that leverages Kaspersky Lab’s latest malware signatures database and detection engine to stop malware in real-time as it attempts to enter the network.
“End-point protection, while an important part of security, is no longer sufficient for today’s constantly besieged networks. Network users need solid anti-malware protection at the gateway to be able to combat dangerous malware,” says Mukesh Lulla, president of TeamF1.
“Kaspersky Lab’s highly-regarded technologies and frequently updated signatures enable our SecureF1rst platform to offer the kind of ironclad security that today’s networks demand.”
"TeamF1, with its leading security platform, forms the base of many leading SMB networking security devices in the market," says Stephane Le Hir, Kaspersky Lab’s VP of technology alliances.
“This partnership will help OEMs served by TeamF1 to offer best-in-class devices to the market driven by our award-winning malware detection features.”