
Adaptive Security is OpenAI’s investment for AI cyber threats. The company was founded in 2024 by serial entrepreneurs Brian Long and Andrew Jones. Adaptive has raised $50M+ from investors like OpenAI, a16z and executives at Google Cloud, Fidelity, Plaid, Shopify, and other leading companies.
Adaptive protects customers from AI-powered cyber threats like deepfakes, vishing, smishing, and email spear phishing with its next-generation security awareness training and AI phishing simulation platform.
With Adaptive, security teams can prepare employees for advanced threats with incredible, highly customized training content that is personalized for employee role and access levels, features open-source intelligence about their company, and includes amazing deepfakes of their own executives.
Customers can measure the success of their training program over time with AI-powered phishing simulations. Hyper-realistic deepfake, voice, SMS, and email phishing tests assess risk levels across all threat vectors. Adaptive simulations are powered by an AI open-source intelligence engine that gives clients visibility into how their company's digital footprint can be leveraged by cybercriminals.
Today, Adaptive’s customers include leading global organizations like Figma, The Dallas Mavericks, BMC Software, and Stone Point Capital. The company has a world class NPS score of 94, among the highest in cybersecurity.
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Bitdefender Small Business Security provides robust, enterprise-level cyber-defense tailored for smaller companies, ensuring protection across various platforms including Windows, macOS, iOS, and Android. With a centralized management system that is user-friendly, it allows organizations lacking dedicated IT personnel to efficiently implement and oversee their security measures from a single interface. The solution features a multi-layered approach to endpoint protection, incorporating machine learning, behavioral analysis, real-time monitoring, process termination, and rollback capabilities to safeguard against both known and emerging threats. Additionally, it includes ransomware prevention and remediation strategies that detect unusual encryption activities and facilitate file recovery from backups. Users are also protected against fileless attacks, with measures like memory and back-injection interference as well as script blocking. The software further enhances security by preventing phishing and fraud through the blocking of malicious websites and alerting users accordingly, while offering advanced exploit protection with real-time shields for common applications such as browsers, Office software, and Adobe Reader, thus ensuring all-encompassing endpoint security. This comprehensive suite of features makes it an ideal choice for small businesses seeking to fortify their cybersecurity defenses.
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Diopter
Diopter AI serves as a cutting-edge platform designed to detect deepfakes and impersonation in real-time during live video and voice communications. This solution empowers organizations to confirm the identities of individuals they engage with by identifying synthetic faces, replicated voices, virtual camera manipulations, and dubious social-engineering behaviors, particularly in situations deemed high-risk.
Various departments such as security, human resources, finance, and customer support utilize Diopter to mitigate threats like executive impersonation, help-desk fraud, unauthorized approvals, counterfeit candidate interviews, and sophisticated social engineering tactics enabled by AI. Unlike traditional methods that focus on post-event analysis, Diopter is tailored for teams that require assurance during live digital interactions to maintain security and trust. Overall, it represents a proactive approach to safeguarding against emerging threats in digital communication.
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IDLive Face
The adoption of facial recognition technology for authentication purposes is rapidly growing, particularly on mobile platforms. However, the combination of readily available images on social media and the advancements in both digital and print image quality has created vulnerabilities in biometric systems that can be exploited by malicious actors to deceive facial recognition software. These deceptive tactics, referred to as presentation attacks, encompass various methods such as using printed photographs, cutout masks, video replays, and 3D masks. Implementing liveness detection enhances security and improves the ability to identify fraudulent attempts. ID R&D's passive face liveness offers a notable advantage as it is not only secure but also user-friendly. Unlike other solutions that require additional steps and can be time-consuming, IDLive Face operates seamlessly, remaining unnoticed by users who are unaware that the liveness check is taking place. Moreover, the software does not provide any hints to potential fraudsters on how to bypass it. As a result of its intuitive design, passive liveness significantly minimizes user confusion, leading to lower abandonment rates and reduced need for human oversight. This streamlined approach ultimately contributes to a more efficient and secure user experience.
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