A threat actor, Zestix, is selling stolen corporate data from breaches of ShareFile, Nextcloud, and OwnCloud instances. The data, obtained through info-stealing malware, includes sensitive information from various sectors, posing security and national security risks. Hudson Rock, a cybersecurity company, has identified the breaches and notified the affected platforms.
In 2026, CISOs will prioritize speed, clarity, and accountability in security, as AI accelerates attacks and complicates traditional defenses. Key trends include platform consolidation for resilience, routine zero-day exploitation, autonomous intrusion chains, and the need for advanced identity controls. The emphasis will shift from merely having tools to justifying decisions and ensuring AI's responsible use. Visibility will replace perimeter defenses, and credential-based security will increasingly become irrelevant. CISOs must adapt to these changes to maintain trust and manage risk effectively.
https://www.msspalert.com/news/2026-will-break-long-held-ciso-security-assumptions
CISOs warned to focus on systemic cloud risks amid rising supply-chain attacks predicted for 2026. Security landscape shaped by AI, but risk concentrated in cloud services and shared platforms. Increased attacks expected on major cloud platforms due to rapid adoption and insufficient visibility into security measures. Attackers utilizing AI for more sophisticated and automated intrusions. Organizations lagging in basic security controls, leaving them vulnerable as threats escalate. Defensive preparations urged for future challenges in cloud security.
https://securitybrief.co.uk/story/cisos-warned-cloud-supply-chain-attacks-set-to-surge
Cybersecurity Predictions for 2026 reveal a major shift in threat landscapes due to AI integration in attacks. Key trends include the rise of autonomous AI-driven threats, an increase in phishing and deepfake attacks, and evolving ransomware tactics. Identity security is critical, with credential abuse as a leading breach method, while Zero Trust architecture gains traction. Cloud and supply chain vulnerabilities are significant, leading to heightened regulatory scrutiny. Continuous Threat Exposure Management will emerge as a focal strategy for resilience against these advanced threats, emphasizing proactive defense over reactive measures.
https://cybersecuritynews.com/cybersecurity-predictions-2026/
Generative AI (GenAI) is transforming cybersecurity for both attackers and defenders. While adversaries use it for coding, phishing, and malware, defenders utilize it to analyze threats, enhance response, and detect vulnerabilities. The rapid evolution of GenAI complicates its quantification in the threat landscape. Adversaries leverage it for anti-analysis tactics, while defenders can use it to sift through vast data. Effective GenAI applications arise in vulnerability hunting and enterprise security, although its success relies on knowledgeable humans to guide its use.
https://blog.talosintelligence.com/spy-vs-spy-how-genai-is-powering-defenders-and-attackers/
AI combats payment fraud as criminals utilize it to execute attacks. Traditional defenses falter against AI-driven scams, leading to increased false declines of legitimate transactions. Static rule-based systems fail to adapt to evolving fraud tactics. AI enables real-time transaction analysis, enhancing accuracy and reducing losses by dynamically scoring risks. Companies like Stripe leverage AI for improved fraud prevention, leading to increased revenues and better customer experiences. Investing in AI for fraud prevention is now vital for growth and trust in e-commerce.
https://www.business-reporter.co.uk/technology/fighting-payment-fraud-with-ai
Visa's Fall 2025 Threats Report identifies five major fraud threats: industrialized fraud tactics, a monetization strategy for stolen card data, AI-generated synthetic content, weakened legacy defenses, and vulnerabilities in third-party systems. Fraudsters leverage tech like botnets and AI for efficient, scalable attacks, maintaining a 12-month delay before exploiting stolen data. Traditional fraud detection struggles to keep pace, leading to a trust paradox where consumer data is at risk through third-party channels.
https://www.digitaltransactions.net/visa-identifies-payments-five-biggest-fraud-threats/
