Keyfactor has acquired InfoSec Global and CipherInsights to further expand cryptographic posture management and quantum readiness. The acquisitions enable Keyfactor to deliver deep cryptographic asset discovery, real-time risk monitoring, and seamless transition to quantum-safe standards. With these acquisitions, Keyfactor is addressing the critical gap in cryptographic observability, helping organizations take control of their non-human identities and prepare for the next era of secure infrastructure. Key capabilities include AgileSec Analytics for deep cryptographic visibility, AgileSec Agility for managing and updating cryptography without source code changes, and CipherInsights for real-time passive network monitoring of cryptographic risks. Customers will benefit from enhanced capabilities that will empower security teams to take control of their cryptographic landscape including Comprehensive Visibility; Actionable Intelligence; Risk Remediation.
Agentic AI’s role in taking down DanaBot malware-as-a-service through orchestrating predictive threat modeling cuts months of forensic analysis to weeks validates its value for SOC teams
U.S. Department of Justice unsealed a federal indictment in Los Angeles against 16 defendants of DanaBot, a Russia-based malware-as-a-service (MaaS) operation responsible for orchestrating massive fraud schemes, enabling ransomware attacks and inflicting tens of millions of dollars in financial losses to victims. Agentic AI played a central role in dismantling DanaBot, orchestrating predictive threat modeling, real-time telemetry correlation, infrastructure analysis and autonomous anomaly detection. These capabilities reflect years of sustained R&D and engineering investment by leading cybersecurity providers, who have steadily evolved from static rule-based approaches to fully autonomous defense systems. Taking down DanaBot validated agentic AI’s value for Security Operations Centers (SOC) teams by reducing months of manual forensic analysis into a few weeks. All that extra time gave law enforcement the time they needed to identify and dismantle DanaBot’s sprawling digital footprint quickly. DanaBot’s takedown signals a significant shift in the use of agentic AI in SOCs. SOC Analysts are finally getting the tools they need to detect, analyze, and respond to threats autonomously and at scale, attaining the greater balance of power in the war against adversarial AI. Agentic AI directly addresses a long-standing challenge, starting with alert fatigue. Microsoft research reinforces this advantage, integrating gen AI into SOC workflows and reducing incident resolution time by nearly one-third. DanaBot’s dismantling signals a broader shift underway: SOCs are moving from reactive alert-chasing to intelligence-driven execution. At the center of that shift is agentic AI. SOC leaders getting this right aren’t buying into the hype. They’re taking deliberate, architecture-first approaches that are anchored in metrics and, in many cases, risk and business outcomes.
Keyfactor supports quantum-safe security expansion enabling managing and updating cryptography without source code changes, and also real-time passive network monitoring of cryptographic risks; for
Keyfactor has acquired InfoSec Global and CipherInsights to further expand cryptographic posture management and quantum readiness. The acquisitions enable Keyfactor to deliver deep cryptographic asset discovery, real-time risk monitoring, and seamless transition to quantum-safe standards. With these acquisitions, Keyfactor is addressing the critical gap in cryptographic observability, helping organizations take control of their non-human identities and prepare for the next era of secure infrastructure. Key capabilities include AgileSec Analytics for deep cryptographic visibility, AgileSec Agility for managing and updating cryptography without source code changes, and CipherInsights for real-time passive network monitoring of cryptographic risks. Customers will benefit from enhanced capabilities that will empower security teams to take control of their cryptographic landscape including Comprehensive Visibility; Actionable Intelligence; Risk Remediation.
IPQS Email Verification tech enables businesses to accurately identify fraudulent or suspicious emails at scale by using email reputation database to analyze factors such as email age, domain reputation, and historical fraud associations
IPQS launched its IPQS Email Verification Database. This database is the first of its kind, enabling businesses to validate email addresses at scale. It reduces the need for external API calls for every fraud check, and makes it easier to comply with data privacy regulations. The IPQS Email Verification Database enables businesses to identify fraudulent, disposable, or suspicious emails with unparalleled accuracy by tapping into IPQS’s vast repository of email reputation data. By analyzing factors such as email age, domain reputation, and historical fraud associations, companies can significantly enhance fraud detection while improving customer trust. Additionally, businesses can maintain better email hygiene by filtering out invalid or risky email addresses, improving deliverability rates and sender reputation. IPQS provides businesses with the most comprehensive access to granular email risk intelligence. This enables organizations to detect high-risk users, block fraudulent account registrations, and prevent payment fraud at scale. Delivered securely via an API, the database is updated on a daily, weekly, or monthly basis, depending on business requirements: On-Premise Deployment; Lightweight Design; Regulatory Compliance; Unmatched Data Accuracy; Email List Hygiene. With the IPQS Email Verification Database, businesses can tap into the freshest, most comprehensive email risk intelligence, CEO Dennis Weiss said.
AI-powered cyberattacks are expected within a year and will emerge from models that are less controlled than OpenAI and Anthropic
Kevin Mandia, one of the most prolific cyber entrepreneurs and investors, predicts the world is only a year away from an AI-agent-enabled cyberattack. Mandia warned that chances are we won’t even know an AI tool was the perpetrator. “Everybody’s going to look at that, wonder how that got done, and it’s probably AI behind it,” he told Axios on the sidelines of the RSA Conference. AI doomsday scenarios have haunted cyber pros for decades, but the introduction of generative AI hypercharged their fears. Some have predicted we’ll see autonomous cyber weapons that can evade security tools in the wild by 2027. Others predict that one day the robots will be fighting robots. Mandia founded famed cybersecurity incident response company Mandiant in the early 2000s. The type of attack Mandia is predicting will likely come from the cyber criminal side of the world, rather than nation-states, he said. Mandia added that the first iteration of any new attack style is typically “a bit sloppy” and that foreign adversaries like China are more likely to take their time before rushing to follow suit. “There is enough R&D happening right now on how to use AI [at legitimate organizations] that the criminal element is doing that R&D as well,” he said. Models from OpenAI, Anthropic and other popular AI companies aren’t likely to be involved in the attack that Mandia is predicting. Those models are “pretty darn good” at blocking such blatant violations of their safety parameters. “It’s going to come from some model that’s somewhere out there that’s less controlled,” he said. Chester Wisniewski, global field CISO at Sophos, told Axios that cyber criminals may already have the capabilities — but many of them don’t have a real incentive to tap into them yet. “Fortunately today, cyber criminals are really lazy, and because we keep leaving our wallets open with large sums of cash in them, they’re happy to just steal the money and move on and not do anything fancy,” Wisniewski said.
JFrog’s software supply chain platform integration with Nvidia to scan all components for vulnerabilities, version them and track them across the entire development lifecycle, along with end-to-end artifact and model management
Software supply chain company JFrog announced a new strategic partnership with Nvidia Corp. to power what the company calls the next era of enterprise AI. Under the partnership, JFrog’s platform will serve as the central software artifact repository and secure model registry within Nvidia’s recently unveiled Enterprise AI Factory. The initiative is designed to help enterprises build, deploy and manage next-generation AI workloads, including agentic and physical AI applications, in a secure and scalable environment. The integration between JFrog and Nvidia will allow users to gain secure and governed visibility into all software components, including ML models and engines. The components can be scanned for vulnerabilities, versioned and tracked across the entire software development lifecycle. Users will also benefit from end-to-end artifact and model management, with the ability to seamlessly pull, upload and host AI models, datasets and containers. The integration includes full support for Nvidia NIMs and other assets optimized for the Enterprise AI Factory architecture. By using JFrog Artifactory, organizations can eliminate the need to access components from external sources, improving both performance and security. The integration includes the ability for the JFrog Platform to run natively on Nvidia’s Grace Blackwell architecture to help reduce latency and process tasks with unparalleled performance, efficiency and scale. Additionally, the integration is expected to support a wide range of AI-enabled enterprise applications, agentic and physical AI workflows, autonomous decision-making and real-time data analysis across various industries, including financial services, healthcare, telecommunications, retail, media and manufacturing.
Platformization taking centre stage in cybersecurity driven by the need to create experience-driven engagement and safeguard complex, distributed environments where data, people and machines all intersect
Platformization is becoming a critical strategy in cybersecurity as organizations shift from fragmented tools to integrated platforms to manage growing threats, complex infrastructure and changing buyer expectations. Vendor consolidation and re-platformization are reshaping the cybersecurity landscape, but expectations often clash with reality on the show floor. As buyers shift toward experience-driven engagement, traditional booth strategies fall short. “I think we’re just consolidating those alphabet soups into specific platforms,” Jackie McGuire, principal analyst, security analytics, operations and strategy at theCUBE Research. said. “The IAM, PAM, all of the identity will become an identity platform. The data security, DSPM, all of that will be a data platform. We are seeing platformization, I just don’t think it’s quite the one login to rule them all that the big vendors would have you believe.” As the security perimeter disappears and digital threats reach into physical infrastructure, the importance of truly integrated platforms continues to rise. Organizations are no longer just defending networks, they’re safeguarding complex, distributed environments where data, people and machines all intersect. The challenge now is not just technical unification, but creating experiences and solutions that align with how modern buyers think, behave and invest, according to John Furrier, co-founder and executive analyst at theCUBE Research. “I call it the re-platformization, because some people are re-platforming, some are actually adopting platforms for the first time because they had best of breed,” he added. “The theme is homogeneous layers where you need data and people, using the Waymo example, where you have so much data and devices or things connected that you need to have data controls. That’s become a big theme.”
Glean to integrate Palo Alto Network’s security platform to enable secure deployment of enterprise AI agents at scale through runtime security; offers unified data governance across the 100+ connected SaaS applications with SASE-native controls and real-time visibility
Glean, the Work AI platform, announced a strategic technology partnership with Palo Alto Networks to further secure and accelerate the use of AI agents in the enterprise. With new integrations to Palo Alto Networks Prisma AIRS and Prisma Access Browser and AI Access, Glean customers gain enhanced visibility and control over how AI agents operate and interact with sensitive enterprise data – enabling rapid innovation without sacrificing trust, security, or compliance. Glean is purpose-built to solve the challenges of deploying AI at scale in the enterprise. From day one, it was architected with enterprise-grade security at its core: enforcing source-level permissions, isolating customer data, and integrating tightly with identity systems. That foundation has since evolved to include proactive guardrails for agent behavior, continuous governance scanning, and an open ecosystem of security partners. Palo Alto Networks Prisma AIRS is the world’s most comprehensive AI security platform that is designed to protect the entire enterprise AI ecosystem, providing Model Scanning, Posture Management, AI Red Teaming, Runtime Security, and Agent Security. The new integration of Prisma AIRS with Glean’s platform will offer: Secure AI adoption at scale with Runtime Security; Confident cloud data governance Posture Management; Zero-compromise security.
Akamai creates firewall purpose built for unique AI threats unauthorized queries, adversarial inputs, and large-scale data-scraping attempts
Akamai Technologies announced Firewall for AI, a new solution that provides multilayered protection for AI applications against unauthorized queries, adversarial inputs, and large-scale data-scraping attempts. Combined with other new enhancements such as API LLM Discovery, Akamai Firewall for AI provides customers with a holistic set of AI-driven capabilities. AI models contain valuable proprietary knowledge and sensitive datasets, making them prime targets for attackers. Akamai Firewall for AI addresses this as a purpose-built security solution designed to protect AI-powered applications, LLMs, and AI-driven APIs from emerging cyberthreats. By securing inbound AI queries and outbound AI responses, the firewall closes security gaps that generative AI technologies introduce. Key features of Firewall for AI include: Multilayered protection: Blocks adversarial inputs, unauthorized queries, and large-scale data scraping to prevent model manipulation and data exfiltration. Real-time AI threat detection: Uses adaptive security rules to dynamically respond to evolving AI-based attacks, including prompt injection and model exploitation. Compliance and data protection: Helps ensure AI-generated outputs remain safe and align with regulatory and industry standards. Flexible deployment options: Deploys via Akamai edge, REST API, or reverse proxy, enabling seamless integration into existing security frameworks. Proactive risk mitigation: Filters AI outputs to prevent toxic content, hallucinations, and unauthorized data leaks.
Virtana’s full-stack observability platform integrates natively with NVIDIA GPU platforms to offer in-depth insights into AI environments by continuously collecting telemetry
Virtana announced the launch of Virtana AI Factory Observability (AIFO), a powerful new capability that extends Virtana’s full-stack observability platform to the unique demands of AI infrastructure. With deep, real-time insights into everything from GPU utilization and training bottlenecks to power consumption and cost drivers, AIFO enables enterprises to turn complex, compute-intensive AI environments into scalable, efficient, and accountable operations. This launch strengthens Virtana’s position as the industry’s broadest and deepest observability platform, spanning AI, infrastructure, and applications across hybrid and multi-cloud environments. Virtana’s AI Factory Observability (AIFO) helps enterprises treat AI infrastructure with the same level of visibility, discipline, and accountability as traditional IT. As an official NVIDIA partner, Virtana integrates natively with NVIDIA GPU platforms to deliver in-depth telemetry, including memory utilization, thermal behavior, and power metrics, providing precise, vendor-validated insight into the most performance-critical components of the AI Factory. This deep integration delivers accurate, actionable intelligence at enterprise scale. Virtana AI Factory Observability (AIFO) is purpose-built to meet the demands of AI operations. It continuously collects telemetry across GPUs, CPUs, memory, network, and storage and then correlates that data with training and inference pipelines to provide clear and actionable insights. Core capabilities include: GPU Performance Monitoring; Distributed Training Visibility; Infrastructure-to-AI Mapping; Power and Cost Analytics; Root Cause Analysis. AIFO is already delivering measurable results in production AI environments across multiple industries. Operational outcomes include: 40% reduction in idle GPU time, improving resource utilization and reducing infrastructure costs; 60% faster mean time to resolution (MTTR) for AI-related incidents; 50% decrease in false alerts, reducing operational noise and accelerating response; 15% improvement in power efficiency, supporting sustainability goals.