Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Cybersecurity researchers are ringing the alarm on new phishing campaigns exploiting Cloudflare Workers, HTML smuggling, and generative AI (GenAI) to target user credentials. These innovative techniques highlight the sophisticated strategies cybercriminals are deploying to bypass security measures and harvest sensitive information.

Have you ever wondered how Artificial Intelligence (AI) could mimic consciousness and autonomously control various tasks? It sounds rather daunting. However, it may not be as intimidating as it seems under the right conditions. Moreover, Would AI perform tasks independently in the same manner as humans? And what implications does this hold for cybersecurity? In the present day, we are observing the rise of self-driving cars that operate with minimal human input.

Anyone remotely wired into technology newsfeeds – or any newsfeeds for that matter – will know that AI (artificial intelligence) is the topic of the moment. In the past 18 months alone, we’ve borne witness to the world’s first AI Safety Summit, a bizarre and highly public leadership drama at one of the world’s top AI companies, and countless prophecies of doom. And yet, even after all that, it seems businesses have largely failed to take meaningful action on AI.

For most organizations, the decision to adopt cloud technologies is a simple one. Cloud apps streamline operations and costs while enabling users to access resources from anywhere and on any device. But migrating to the cloud has also introduced some complexity, which comes with new risks. Instead of everything residing neatly within your corporate perimeter, your data now resides within countless apps and is being handled by users and endpoints that operate outside of your sphere of influence.

Penetration testing is a cornerstone of any mature security program and is a mature and well understood practice supported by robust methodologies, tools, and frameworks. The tactical goals of these engagements typically revolve around identification and exploitation of vulnerabilities in technology, processes, and people to gain initial, elevated, and administrative access to the target environment.

In the rapidly evolving landscape of technology, the fusion of Artificial Intelligence (AI) and cybersecurity is creating both exciting opportunities and formidable challenges. The recent breakfast briefing on the historic HMS Belfast served as a critical forum for industry leaders to explore these issues in depth.

IONIX’s Cloud Cross-View (CCV) uses cloud integrations to broaden the scope of attack surface mapping and coverage beyond traditional methods of monitoring. CCV extends asset analysis to consider aspects that are specific to cloud environments. This complements CSPM and CNAPP solutions by enriching them with broader attack surface data obtained through IONIX’s EASM capabilities.

In our latest report, Snyk surveyed security and software development technologists, from top management to application developers, on how their companies had prepared for and adopted generative AI coding tools. While organizations felt ready and believed AI coding tools and AI-generated code were safe, they failed to undertake some basic steps for secure adoption. And within the ranks, those close to the code have greater doubts about AI safety than those higher up in management.

It’s a familiar post-disaster scene in seemingly every television medical drama. A ferry has crashed, or a train has derailed. Patients flood into the ER, each requiring urgent medical attention. The impossibly attractive medical staff must quickly assess and prioritize patients based on the severity of their injuries and the likelihood of survival. Someone with great hair likely says an inspiring quote and jumps immediately into action.