Schubring Global Solutions

In 2025 and beyond, cloud security must evolve to address new and growing challenges. As organizations increasingly rely on cloud infrastructure, especially for AI-driven workflows and data migration, robust security strategies will be more crucial than ever. ?? Key trends include: ?? Increased Threat Landscape: Sophisticated cyberattacks are pushing the market toward comprehensive, proactive security platforms. ?? SOC Integration: Cloud security and Security Operations Centers (SOCs) will merge, improving coordination and resilience. ?? Data Security in CNAPPs: With more sensitive data in the cloud, solutions will prioritize strong data protection. ?? Unified Application Security: More organizations will consolidate security budgets into unified platforms, offering better threat detection and prevention. ?? Protecting IP in AI-Generated Code: Businesses will focus on securing proprietary content in AI-driven software. ?? Stricter AI Compliance: New regulations will require organizations to enhance security and training for AI data handling. ?? Balancing Security with Innovation: Developers may bypass security for innovation, making it vital for companies to find a balance. ?? AI-Powered Malware: The rise of AI-driven malware will require adaptive defenses to counter new, automated threats. These shifts demand a comprehensive, forward-thinking approach to cloud security. ???? For more insights ?? https://buff.ly/3EqKTMX #CloudSecurity #AI #DataProtection #SOC #CyberSecurity #AICompliance #CloudInfrastructure #ThreatDetection #InnovationVsSecurity #CyberDefense #CloudNative #AIThreats #DataSecurity

As digital innovation accelerates, AI and machine learning are reshaping cybersecurity, but they also bring new threats. Public sector organizations must balance embracing these technologies with defending against evolving risks, all while facing a 500,000-person workforce shortage. AI and automation can act as force multipliers, enhancing speed, accuracy, and efficiency in threat detection and response. By automating routine tasks and using predictive analytics, agencies can shift from reactive to proactive defense. AI helps identify subtle anomalies that humans might miss, reducing the risk of human error, which is a major threat. Federal agencies are increasingly leveraging AI to automate tasks and streamline operations, saving time and improving decision-making. However, they must remain vigilant, ensuring strong cybersecurity foundations while embracing new technologies. For more insights ?? https://buff.ly/40RoRdW #Cybersecurity #AI #MachineLearning #Automation #CyberDefense #ThreatDetection #TechInnovation #PublicSector #AIinCyber #CyberResilience #TechNews #CyberAware #DigitalTransformation

In 2025, technology leaders are focused on adopting agentic AI, with enterprises eager to incorporate the technology. Research on agentic systems has surged, and around 400 vendors now offer new platforms. However, while experts believe businesses will quickly benefit from agents, concerns about security, readiness gaps, and immature foundations remain. Despite challenges, two-thirds of organizations are exploring AI agents, with companies like SharkNinja piloting the technology for customer support, returns, and sales. Vendors like Microsoft, AWS, and Salesforce are pushing AI agents to expand adoption, aiming to replicate the hype seen with generative AI. The outlook for success is mixed, with both optimism and concerns about potential failures. For more insights ?? https://buff.ly/3Q9tcEk #AgenticAI #AIAdoption #GenerativeAI #TechTrends #Innovation #EnterpriseTech #AIinBusiness #AI #Leadership #TechTransformation #TechNews

?? Cybersecurity Term of the Week: Machine Learning (ML) Machine Learning (ML) is a subset of artificial intelligence (AI) that enables computers to learn from data and make decisions without being explicitly programmed. By analyzing large datasets, ML algorithms identify patterns, make predictions, and improve their performance over time. It is widely used in various applications, from predictive analytics and speech recognition to image classification and autonomous vehicles. ML's ability to continuously improve from experience makes it a powerful tool in automation and data-driven decision-making. ?? #MachineLearning #AI #ArtificialIntelligence #DataScience #Tech #Automation #PredictiveAnalytics #DeepLearning #DataDriven #SmartTechnology #Cybersecurity #CyberTerms #algorithms

Social engineering attacks, commonly used by cybercriminals to breach organizations, are becoming more sophisticated with the rise of AI. AI enables more personalized and convincing attacks through tactics like personalized phishing, local and contextual content generation, and realistic deepfakes. The development of agentic AI (autonomous AI agents) further amplifies these risks by allowing AI to adapt and improve its attacks over time. Agentic AI can autonomously gather data, tailor phishing messages, and launch multi-stage or multi-channel campaigns, making attacks more dynamic and harder to detect. Organizations can counter these threats by using AI to detect malicious activities, employing AI-based security training, and preparing employees to recognize and respond to AI-driven social engineering attacks. Security awareness and AI-based tools are key to staying ahead of the evolving cyber threat landscape. For more insights ?? https://lnkd.in/g8WPbkPh #Cybersecurity #AI #SocialEngineering #Phishing #Deepfakes #CyberThreats #AIsecurity #Infosec #SecurityAwareness #TechRisks #CyberDefense #AIThreats #DataProtection #SecurityForces

In Q4 2024, Cisco Talos reported a significant rise in cyber threats. Web shells were deployed in 35% of incidents, up from 10% in the previous quarter. Public-facing applications were exploited for initial access in 40% of cases, marking a shift from previous quarters when valid accounts were the primary entry method. Remote access tools were used in all ransomware cases, with Splashtop appearing in 75% of them. ?? Additionally, there was an increase in password-spraying attacks, with one organization reporting 13 million attempts in 24 hours. Researchers noted these shifts in tactics and tools used by threat groups, driven by new vulnerabilities and automated attacks. ??? For more insights ?? https://buff.ly/3EsF3KZ #CyberSecurity #WebShells #Ransomware #PasswordSpraying #ThreatHunting #CiscoTalos #DataBreach #CyberThreats #RemoteAccess #PublicApps #Malware #InfoSec #CyberAttack

?? Cybersecurity Term of the Week: Defense-in-Depth Defense-in-Depth is a cybersecurity strategy that employs multiple layers of security controls to protect information and systems. Rather than relying on a single security measure, this approach involves a combination of preventive, detective, and corrective measures across various levels, such as network, application, and endpoint security. By using overlapping defenses, Defense-in-Depth ensures that if one layer is bypassed, others are in place to mitigate the risk, providing a stronger, more resilient defense against potential threats. ??? #Cybersecurity #DefenseInDepth #InfoSecurity #NetworkSecurity #Security #CyberDefense #DataProtection #IT #CyberThreats #CyberResilience #CyberTerms

Cyber Threat Intelligence (CTI) is vital for protecting digital infrastructures, with Indicators of Compromise (IOCs) being key to detecting cyber threats. However, generic IOCs often overwhelm security teams with noise and lack context, making them less effective. Custom IOCs, tailored to an organization’s specific risks, offer more value. They improve threat detection by reducing false positives, provide relevant, timely intelligence, and enhance supply chain and regulatory compliance. Custom IOCs are essential for adapting to evolving threats and safeguarding critical assets, making them a necessity in modern cybersecurity defense. For more insights ?? https://lnkd.in/eP9eDWDA #CyberThreatIntelligence #CTI #CyberSecurity #ThreatDetection #CustomIOCs #IOCs #InfoSec #Malware #CyberDefense #DataProtection #CyberAwareness #ThreatHunting #SecurityCompliance #SupplyChain #SecurityForces

AI is rapidly evolving social engineering attacks, making them more realistic and scalable. Traditional methods like silicone masks and fraudulent phone calls are being replaced by deepfakes and voice cloning. ?? For example, attackers used a deepfake CFO in Hong Kong to steal $25 million, and voice cloning was used to impersonate a daughter in a ransom scheme. Phishing attacks have also become more sophisticated, with AI enabling attackers to send highly personalized, realistic emails at scale. This reduces costs and increases effectiveness. To combat these AI-driven threats, cybersecurity leaders must adapt defenses, focusing on simulated social engineering training to better prepare employees. Traditional awareness methods are no longer enough in the face of these advanced, human-targeted tactics. For more insights ?? https://buff.ly/4hKS3dm #Cybersecurity #AI #SocialEngineering #Deepfakes #VoiceCloning #Phishing #Vishing #DataBreach #SecurityAwareness #CyberDefense #ThreatIntelligence #SimulatedAttacks #TechSecurity

?? Researchers at Reversing Labs discovered two malicious machine learning (ML) models on Hugging Face that exploited a new malware distribution method using Pickle file serialization. Despite containing malicious code, these models were not flagged as unsafe by Hugging Face’s Picklescan security tool. The models bypassed detection by using 7z compression instead of the traditional ZIP format, preventing standard security scans. The malicious models appeared to be proof-of-concept rather than fully operational threats. The incident exposed flaws in Picklescan, which relies on basic blacklists and struggles to detect threats in broken Pickle files. Hugging Face promptly removed the models and updated Picklescan to address these vulnerabilities. For more insights ?? https://buff.ly/3WSybge #MachineLearning #CyberSecurity #AI #HuggingFace #Malware #PickleFiles #SecurityFlaw #TechNews #DataSecurity #MaliciousCode #ReversingLabs #AIThreats