Adaptive Security was founded in 2024 by seasoned entrepreneurs Brian Long and Andrew Jones. Since inception, the company has raised over $50 million from top-tier investors including OpenAI, Andreessen Horowitz, and executives from Google Cloud, Fidelity, Plaid, Shopify, and other industry leaders.
Adaptive defends organizations against sophisticated, AI-driven cyber threats such as deepfakes, vishing, smishing, and spear phishing. Its next-generation security awareness training and AI phishing simulation platform enables security teams to deliver ultra-personalized training that adapts to each employee’s role, access level, and exposure. This training leverages real-time open-source intelligence (OSINT) and features highly convincing deepfake content—including synthetic media of a company’s own executives—to mirror real-world attack vectors.
Through AI-powered simulations, customers can continuously assess and improve organizational resilience. Hyper-realistic phishing tests across voice, SMS, email, and video channels evaluate risk across every major vector. These simulations are fueled by Adaptive’s AI OSINT engine, giving teams deep visibility into how attackers might exploit their digital footprint.
Today, Adaptive serves global leaders like Figma, The Dallas Mavericks, BMC Software, and Stone Point Capital. With an industry-leading Net Promoter Score of 94, Adaptive is redefining excellence in cybersecurity.
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SOCRadar Extended Threat Intelligence is an all-encompassing platform built to proactively identify and evaluate cyber threats, offering actionable insights that are contextually relevant. As organizations strive for improved visibility into their publicly available assets and the vulnerabilities linked to them, relying only on External Attack Surface Management (EASM) solutions proves insufficient for effectively managing cyber risks; these technologies should be integrated within a broader enterprise vulnerability management strategy. Businesses are increasingly focused on safeguarding their digital assets from every conceivable risk factor. The traditional emphasis on monitoring social media and the dark web is no longer adequate, as threat actors continually adapt and innovate their attack strategies. Thus, comprehensive monitoring across various environments, including cloud storage and the dark web, is vital for empowering security teams to respond effectively. Furthermore, a robust approach to Digital Risk Protection necessitates the inclusion of services such as site takedown and automated remediation processes. By adopting this multifaceted approach, organizations can significantly enhance their resilience in the face of an ever-evolving cyber threat landscape, ensuring they can respond proactively to emerging risks. This continuous adaptation is crucial for maintaining a strong security posture in today's digital environment.
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Mindgard
Mindgard stands at the forefront of cybersecurity for artificial intelligence, focusing on the protection of AI and machine learning models, including large language models and generative AI, for both proprietary and external applications. Founded in 2022 and drawing on the academic expertise of Lancaster University, Mindgard has swiftly emerged as a significant force in addressing the intricate vulnerabilities that come with AI technologies. Our primary offering, Mindgard AI Security Labs, exemplifies our commitment to innovation by automating the processes of AI security evaluation and threat identification, effectively uncovering adversarial risks that conventional approaches often overlook.
With the backing of the most extensive AI threat library available commercially, our platform empowers businesses to safeguard their AI resources throughout their entire lifecycle. Mindgard is designed to seamlessly integrate with existing security frameworks, allowing Security Operations Centers (SOCs) to efficiently implement AI and machine learning solutions while effectively managing the unique vulnerabilities and risks associated with these technologies. In this way, we ensure that organizations can not only respond to threats but also anticipate them, fostering a more secure environment for their AI initiatives.
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Protecto
The rapid growth of enterprise data, often dispersed across various systems, has made the management of privacy, data security, and governance increasingly challenging. Organizations face considerable threats, such as data breaches, lawsuits related to privacy violations, and hefty fines. Identifying data privacy vulnerabilities within a company can take several months and typically requires the collaboration of a dedicated team of data engineers. The urgency created by data breaches and stringent privacy regulations compels businesses to gain a deeper insight into data access and usage. The complexity of enterprise data exacerbates these challenges, and even with extensive efforts to pinpoint privacy risks, teams may struggle to find effective solutions to mitigate them in a timely manner. As the landscape of data governance evolves, the need for innovative approaches becomes paramount.
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