Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

As a small kid, I remember watching flying monkeys, talking lions, and houses landing on evil witches in the film The Wizard of Oz and thinking how amazing it was. Once the curtain pulled back, exposing the wizard as a smart but ordinary person, I felt slightly let down. The recent explosion of AI, and more specifically, large language models (LLMs), feels similar. On the surface, they look like magic, but behind the curtain, LLMs are just complex systems created by humans.

Artificial intelligence has taken over almost every aspect of our everyday lives. In cybersecurity, generative AI models with natural language processing are commonly being used to predict, detect, and respond to threats. But AI security assistants, although an upgrade from traditional machine learning, only provide very basic queries and summarization, which is insufficient to fully comprehend modern cloud attacks. As part of an ongoing effort to improve the cloud detection and response (CDR) experience,

The Cyber Security Agency of Singapore (CSA) has warned that threat actors are increasingly using AI to enhance phishing and other social engineering attacks, Channel News Asia reports. The CSA’s report found that cybercriminals are selling tools that automate these attacks, allowing unskilled threat actors to launch sophisticated attacks.

Cloud storage is a versatile and competitive market, so making a decision about choosing the best cloud storage services can seem intimidating. Fortunately, best cloud storage for personal use offers many features and services to securely store personal files, backups, sync, and protect your privacy online.

The explosion of AI has ignited both excitement and apprehension across various industries. While AI is undeniably having a positive impact on engineering and customer service teams, cybersecurity and IT practitioners remain cautious. Concerns about data privacy, the inflexibility of disparate tools, and the sensitive nature of many mission-critical workflows—which, more often than not, require some level of human oversight—fuel a deep mistrust of LLMs by these teams.

As noted in the 2024 Gartner Market Guide for API Protection“API security governance is an emerging capability. It allows the administrator of the tool to define and enforce security policies. Unlike posture management, this is a top-down enforcement. It also allows for compliance reports for specific regulations to be generated automatically.” This capability is becoming increasingly important as organizations face a constantly evolving threat landscape.

The API security landscape is changing rapidly, and cybercriminals are becoming increasingly sophisticated. According to the Salt Labs State of API Security Report 2024, API security incidents have more than doubled in the past 12 months, while API usage is rapidly increasing. Organizations are finding it challenging to keep up with the threats associated with expanding API ecosystems and fully understand their complex behavioral attributes.

In today’s rapidly evolving cloud landscape, organizations are grappling with the intricate challenge of striking a delicate balance between ensuring robust cybersecurity measures and facilitating seamless operational efficiency. As cloud adoption continues to surge, the traditional approach of granting standing privileges to users has become an increasingly significant security vulnerability.