Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Exploring AI for Vulnerability Investigation and Prioritisation

The sheer volume of cybersecurity vulnerabilities is overwhelming. In 2024, there were 39,998 CVEs — an average of 109.28 per day! This constant stream of new threats makes it increasingly difficult for security teams to keep up. Large Language Models (LLMs) offer a possible solution, helping automate vulnerability investigation and prioritisation, allowing teams to more efficiently assess and respond to emerging risks. Do you even have time to skim over 109 CVEs a day?

Insider Risk with Nightfall DLP: Episode 2 - Managing Shadow AI

Earlier this year, security researchers found more than 1 million records, including user data and API keys, in an exposed DeepSeek database. This massive exposure event tells us that data exfiltration risk and AI proliferation are forever linked together: as AI tools grow in popularity and complexity, exfiltration risk rises in kind.

AI Agents and API Security: The Hidden Risks Lurking in Your Business Logic

Modern organizations are becoming increasingly reliant on agentic AI, and for good reason: AI agents can dramatically improve efficiency and automate mission-critical functions like customer support, sales, operations, and even security. However, this deep integration into business processes introduces risks that, without proper API security, can compromise sensitive data and decision-making.

Leveraging map-reduce and LLMs for enhanced cybersecurity network detection

In my security research role at Corelight, I often have to go through large, complex data sets to detect subtle anomalies and threats. It reminds me of a famous quote by Abraham Lincoln: Give me six hours to chop down a tree and I will spend the first four sharpening the axe. For me, that means investing time up front to build tools that allow a large language model (LLM) to do the heavy lifting on key tasks, namely those that teams of analysts would have handled in the past.

Gee-Wiz! What a $30B Acquisition Means for Cloud Security and AI

The cloud security landscape changed overnight. With Google’s $30B+ acquisition of Wiz, CISOs, security leaders, and multi-cloud teams are left asking: �������� �������������� ��������? What does this acquisition mean for you? How does it impact the pace of innovation, cloud partnerships, and security stacks? What is the future of cloud security, the impact of AI, and where the industry is headed?

Why Principle of Least Privilege Matters More Than Ever in a World of Backdoored Large Language Models (LLMs)

The concept of “principle of least privilege” has been around for a long time. In fact, it is older than me; there are papers from the 70s that discuss it: “Every program and every user of the system should operate using the least set of privileges necessary to complete the job.” (The protection of information in computer systems, Saltzer and Schroeder, 1974).