
SOCRadar boosts MSSP support with free AI training, new tools
SOCRadar has announced an expansion of its Managed Security Service Provider (MSSP) programme designed to support partners in scaling operations, automating threat workflows, and improving service delivery.
As part of the enhanced programme, SOCRadar will provide free AI Agent and Automation Training to its partners. This training aims to educate MSSPs on the use of AI agents and generative AI (GenAI) technologies to streamline security operations centre (SOC), threat intelligence, and vulnerability management processes.
The training is described as platform-agnostic, equipping MSSP partners with hands-on experience to build their own AI-powered workflows, irrespective of the specific tools they currently deploy.
Alongside the introduction of free training, SOCRadar has implemented several enhancements to its MSSP programme, including multi-tenant licensing, threat intelligence use cases designed specifically for MSSPs, a Multi-Tenant Management Console, and configurable External Threat Assessment Reports.
"Our enhanced MSSP program enables partners to scale smartly and serve clients more effectively. By combining AI Agents with our extended threat intelligence capabilities, MSSPs can double their operational efficiency—automating routine workflows, accelerating incident response, and delivering tailored intelligence without adding headcount. We believe AI Agents and GenAI will be foundational to the future of MSSPs, and we're committed to helping our partners lead that transformation," Huzeyfe Onal, Chief Executive Officer of SOCRadar, said.
According to SOCRadar, its AI agents are intelligent automation components embedded within the company's Extended Threat Intelligence (XTI) platform. These agents utilise Large Language Models (LLMs) and automation scripts with the ability to execute complex, multi-stage cybersecurity workflows.
Unlike traditional scripts or static rules, SOCRadar's AI agents can analyse contextual information, make decisions based on data, and take actions across multiple IT systems. This approach is intended to reduce the manual workload for analysts, while increasing both the speed and accuracy of threat detection and response.
MSSPs can create what SOCRadar refers to as "smart workflows" by establishing specific goals and operational boundaries for each AI agent. The agents then apply planning, reasoning, and learning methods to support tasks such as identifying threats, enriching data, correlating alerts, or prioritising vulnerabilities for remediation.
The company listed several key benefits of its framework for MSSPs, including the automation of threat intelligence, SOC, and vulnerability management tasks; reduction in analyst workload while accelerating detection and response times; improvement in decision accuracy with a reduction in false positives; enablement of continuous monitoring across multiple clients without increasing staffing; and the potential to increase both scalability and profitability whilst preserving service quality.
SOCRadar reports that it serves over 800 customers in 70 countries. Its Extended Threat Intelligence Platform makes use of artificial intelligence and machine learning for threat detection and to deliver actionable intelligence against cyber threats. The suite of offerings includes Cyber Threat Intelligence, External Attack Surface Management, Brand Protection, Dark Web Monitoring, and Supply Chain Threat Intelligence.
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Techday NZ
3 days ago
- Techday NZ
SOCRadar boosts MSSP support with free AI training, new tools
SOCRadar has announced an expansion of its Managed Security Service Provider (MSSP) programme designed to support partners in scaling operations, automating threat workflows, and improving service delivery. As part of the enhanced programme, SOCRadar will provide free AI Agent and Automation Training to its partners. This training aims to educate MSSPs on the use of AI agents and generative AI (GenAI) technologies to streamline security operations centre (SOC), threat intelligence, and vulnerability management processes. The training is described as platform-agnostic, equipping MSSP partners with hands-on experience to build their own AI-powered workflows, irrespective of the specific tools they currently deploy. Alongside the introduction of free training, SOCRadar has implemented several enhancements to its MSSP programme, including multi-tenant licensing, threat intelligence use cases designed specifically for MSSPs, a Multi-Tenant Management Console, and configurable External Threat Assessment Reports. "Our enhanced MSSP program enables partners to scale smartly and serve clients more effectively. By combining AI Agents with our extended threat intelligence capabilities, MSSPs can double their operational efficiency—automating routine workflows, accelerating incident response, and delivering tailored intelligence without adding headcount. We believe AI Agents and GenAI will be foundational to the future of MSSPs, and we're committed to helping our partners lead that transformation," Huzeyfe Onal, Chief Executive Officer of SOCRadar, said. According to SOCRadar, its AI agents are intelligent automation components embedded within the company's Extended Threat Intelligence (XTI) platform. These agents utilise Large Language Models (LLMs) and automation scripts with the ability to execute complex, multi-stage cybersecurity workflows. Unlike traditional scripts or static rules, SOCRadar's AI agents can analyse contextual information, make decisions based on data, and take actions across multiple IT systems. This approach is intended to reduce the manual workload for analysts, while increasing both the speed and accuracy of threat detection and response. MSSPs can create what SOCRadar refers to as "smart workflows" by establishing specific goals and operational boundaries for each AI agent. The agents then apply planning, reasoning, and learning methods to support tasks such as identifying threats, enriching data, correlating alerts, or prioritising vulnerabilities for remediation. The company listed several key benefits of its framework for MSSPs, including the automation of threat intelligence, SOC, and vulnerability management tasks; reduction in analyst workload while accelerating detection and response times; improvement in decision accuracy with a reduction in false positives; enablement of continuous monitoring across multiple clients without increasing staffing; and the potential to increase both scalability and profitability whilst preserving service quality. SOCRadar reports that it serves over 800 customers in 70 countries. Its Extended Threat Intelligence Platform makes use of artificial intelligence and machine learning for threat detection and to deliver actionable intelligence against cyber threats. The suite of offerings includes Cyber Threat Intelligence, External Attack Surface Management, Brand Protection, Dark Web Monitoring, and Supply Chain Threat Intelligence.


Techday NZ
30-05-2025
- Techday NZ
APJ region accelerates AI adoption as Dell rolls out new innovations
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CEO Jae Won Kim described how Elice faced soaring costs when trying to provide deep learning environments for students and businesses. "We had to reduce GPU cloud fees by more than 90%," he said. The solution was a portable modular data centre powered by Dell servers, now used for everything from AI digital textbooks for five million students to sovereign AI workloads that comply with government requirements. "There's very limited data centre capacity in Korea for high-density AI workloads," Kim explained. "The modular data centre lets us host hundreds of GPUs, with liquid cooling for the latest chips. It's not just about education anymore – we're talking about a hybrid solution that could be deployed in Japan, Australia or anywhere data centre construction lags demand." Marrs praised the partnership, saying, "You really thought big, and you went and made it happen." Kim's advice for others: "AI is not going away. It's better to start early. If you're worried about investment, modular is the best way to start small and start fast." Innovation and ecosystem challenges Dell's announcements at the conference included a raft of new infrastructure solutions designed to cut energy costs, boost data centre efficiency and accelerate AI deployments of any size. The company's latest cooling technology can reduce energy costs by up to 60%, while new servers with AMD and NVIDIA chips promise up to 35 times greater AI inferencing performance than previous generations. Yet, challenges remain. "The biggest hurdles are people and ecosystem," Marrs acknowledged. "We need to educate the next generation of AI talent and work with governments to create the right regulatory and compliance frameworks." Kelly added, "Access to data centre space, power and cooling is going to be crucial. Requirements are moving so fast that what seemed high density a year ago now looks standard." 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Techday NZ
22-05-2025
- Techday NZ
Organisations boost AI security as data threats & risks evolve
Thales has released its 2025 Data Threat Report, showing that nearly 70% of surveyed organisations view the rapid development of artificial intelligence, particularly generative AI, as their primary security concern related to the technology's adoption. The survey, conducted by S&P Global Market Intelligence 451 Research, captured the opinions of more than 3,000 IT and security professionals across 20 countries and 15 industries, providing insight into current and emerging data security threats faced by businesses worldwide. The report indicates that three key concerns consistently emerged regarding artificial intelligence: the pace of development (cited as the leading risk by nearly seven in ten respondents), followed by questions over AI's integrity (64%), and its trustworthiness (57%). Spending on generative AI security has seen a marked increase since previous years. Seventy-three percent of respondents said their organisations were now investing in AI-specific security tools, with funding sourced either from new or existing budgets. Security for generative AI has risen to become the second highest security spending priority after cloud security. Eric Hanselman, Chief Analyst at S&P Global Market Intelligence 451 Research, described the pressures companies are facing. "The fast-evolving GenAI landscape is pressuring enterprises to move quickly, sometimes at the cost of caution, as they race to stay ahead of the adoption curve," he said. "Many enterprises are deploying GenAI faster than they can fully understand their application architectures, compounded by the rapid spread of SaaS tools embedding GenAI capabilities, adding layers of complexity and risk." The report highlights that organisations are adapting different strategies to address AI-related security challenges. Over two-thirds have obtained security tools directly from their cloud providers, while three in five are relying on established security vendors, and nearly half are working with startups specialising in this area. Adoption of generative AI is already well underway in many firms, with a third of surveyed organisations indicating that the technology is either being integrated into their operations or is actively transforming them. As agentic AI applications develop – those capable of decision-making or acting on data – the importance of ensuring data quality and security grows further. The risk environment for organisations, however, remains complex. Malicious software, or malware, continues to be reported as the most persistent attack vector since 2021. This year, phishing rose to become the second most common type of attack, while ransomware dropped to third place. 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"Even with clear timelines for transitioning to PQC algorithms, the pace of encryption change has been slower than expected due to a mix of legacy systems, complexity, and the challenge of balancing innovation with security." The results of the 2025 Data Threat Report indicate that while there have been improvements in the overall security posture of organisations, further efforts will be required to fully address the risks and operational demands posed by emerging technologies such as generative AI and quantum computing.