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Check Point Launches Quantum Firewall R82.10 to Secure AI Adoption in Enterprises

Check Point Software unveils Quantum firewall R82.10, enhancing AI security with 20 new features to protect enterprises from emerging threats in hybrid environments.

Check Point Software has launched a new version of its Quantum firewall software, R82.10, designed to address security risks associated with the rapid adoption of artificial intelligence (AI) in enterprise environments. The latest release introduces 20 new features focusing on network, identity, and AI security, particularly within hybrid environments that encompass data centers, branch offices, and multiple public clouds.

The update comes in response to escalating pressures on security teams as organizations roll out AI tools and large language model projects across their operations. “As organisations embrace AI, security teams are under growing pressure to protect more data, more applications and more distributed environments,” said Nataly Kremer, Chief Product Officer at Check Point Software Technologies. “R82.10 helps enterprises shift to a prevention-first model by unifying management, strengthening Zero Trust and adding protections that support safe, responsible AI adoption and development.”

As many enterprises connect AI services to existing systems and data stores, concerns over data leakage, model abuse, and new types of automated attacks have surged. Check Point’s new software release targets four operational areas: AI adoption, hybrid mesh network security, threat prevention, and platform unification.

The company has introduced functions aimed at tracking and controlling the use of generative AI tools. The software can detect unauthorized AI services in network traffic and provides specific visibility for popular AI tools such as ChatGPT, Claude, and Gemini. Additionally, R82.10 includes monitoring for the model context protocol, which supports AI workflows that integrate various tools and data sources. This feature aims to mitigate the risks associated with unmanaged AI agents accessing sensitive systems, thereby offering security teams increased visibility into employee usage of AI services and data flows.

R82.10 is tailored for organizations managing multiple locations and cloud environments, linking on-premises firewalls with secure access service edge (SASE) services through centralized internet access policies. This unified approach applies consistent rules to traffic from branch offices, remote workers, and cloud workloads, reducing the necessity for separate policy sets in each environment. The release also enhances identity and device posture checks, supporting the implementation of Zero Trust models at scale by validating users and devices before granting access to applications.

Among its new features, Check Point has incorporated phishing protection that operates without requiring HTTPS inspection. This capability allows for the detection of malicious sites and links without decrypting traffic content, making it particularly suitable for environments that must safeguard encrypted traffic for regulatory or privacy reasons. The adaptive intrusion prevention system adjusts alerts based on threat context, which aims to alleviate alarm fatigue in security operations centers. New Threat Prevention Insights highlight configuration weaknesses and posture gaps, enabling security teams to prioritize remediation before attackers can exploit vulnerabilities.

The R82.10 update deepens Check Point’s integration strategy, supporting over 250 third-party integrations. Customers can incorporate endpoint posture data from existing providers into their Quantum firewall policies, which may include device health, operating system status, and security agent information. This data informs identity-based rules, enhancing access controls and facilitating granular Zero Trust enforcement.

Industry analysts have noted that the transformative impact of AI is reshaping network security strategies. “With the efficiency gains promised by AI, security professionals cannot slow down business innovation or risk being excluded,” stated Frank Dickson, Group Vice President of Security & Trust at IDC. “The benefits of innovation do not negate the looming security threat being introduced by AI. Enterprises need to reduce risk, unify controls, and stay ahead of sophisticated malicious actors. Check Point’s approach of embedding AI security into the network stack is an appropriate strategy to quickly improve an organisation’s AI security posture.”

R82.10 is part of Check Point’s broader AI security portfolio, integrating seamlessly with the company’s Infinity Platform and its open integration framework. This platform approach allows organizations to apply consistent policies across on-premises networks, cloud workloads, and remote users. Furthermore, the new firewall release connects with AI security technology from Lakera, a company acquired by Check Point earlier this year. Lakera’s tools are focused on securing AI models during both training and inference phases, thereby extending protection for AI workloads from data ingestion to model output inspection.

Channel partners are expressing strong demand for such integrated security solutions. “Check Point continues to deliver AI security innovations at the exact moment customers need them,” remarked Chris Konrad, Vice President of Global Cyber at World Wide Technology. “Their AI-driven security capabilities help organizations safeguard their businesses from the latest cyber threats while providing enterprise-grade protection for sensitive AI workloads from model training to inference without compromising performance.”

Looking ahead, Check Point plans to further develop its AI security features across both the Quantum and Infinity product lines as customers continue to expand their AI projects within hybrid network environments.

See also
Rachel Torres
Written By

At AIPressa, my work focuses on exploring the paradox of AI in cybersecurity: it's both our best defense and our greatest threat. I've closely followed how AI systems detect vulnerabilities in milliseconds while attackers simultaneously use them to create increasingly sophisticated malware. My approach: explaining technical complexities in an accessible way without losing the urgency of the topic. When I'm not researching the latest AI-driven threats, I'm probably testing security tools or reading about the next attack vector keeping CISOs awake at night.

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