7 hours. That’s how long, on average, a developer takes to remediate a security issue in their code. Vulnerability detection is improving rapidly and scaling, but remediating security risks is still a tedious, time-consuming process that takes developers away from their core work. And now, with AI-generated code introducing vulnerabilities at greater speed and volume than ever before, remediation is taking even more time.

Continuous vulnerability management is not just a best practice—it's a necessity. With so many open-source dependencies to choose from (almost 3 million on the npm registry!), it’s no wonder supply chain security incidents are the focus of malicious actors. Let’s not forget the rise of ChatGPT, LLM chatbots, and AI-assisted code generation.

Can you imagine a world without passwords? There’s nothing more annoying than trying to access an account you haven’t used in a while, only to find out you’ve forgotten your password. As we need to verify our identities for almost everything, it is pretty easy to forget passwords to old accounts. This means you have to waste time remembering usernames, secret answers to questions, verifying, and creating and saving a new password.

The growing reliance on generative AI is transforming industries across the globe. From automating tasks to improving decision-making, the potential of these systems is vast. However, with this progress comes significant risks. Generative AI can be unpredictable, creating new vulnerabilities that expose organizations to data privacy breaches, compliance failures, and other security issues. So, how can companies harness the power of AI while ensuring they remain protected?

The Cyberint Europe Threat Landscape 2024-2025 report sheds light on the increasingly complex and evolving cyber threat environment affecting organizations across Europe and the UK. Leveraging data from Cyberint—which monitors threats like phishing, malware, and supply chain vulnerabilities—the report highlights a surge in malicious activities driven by global conflicts, technological shifts, and the growing use of generative AI in cybercrime.

In the wake of Cisco’s recent data breach involving exposed API tokens - amongst other sensitive information - the cybersecurity community is reminded once again of the significant risks associated with unsecured APIs. Though Cisco has asserted that the damage was limited to a public-facing environment, such breaches demand a more cautious evaluation. Exposing sensitive information like API tokens, credentials, and even source code can have broader security implications than initially apparent.

From power grids and water systems to transport networks and healthcare facilities, critical infrastructure has become a key target for cyber attacks in recent years, such as US utilities suffering a 70% year-on-year increase in cyber attacks this year. The reason for targeting critical infrastructure is clear: they often use outdated software and the attacks have an outsized disruptive impact.

With an average of more than 5 data breaches globally a day, it’s clear companies need a way to prevent data loss. This is where a data loss prevention policy comes into play. A data loss prevention policy serves as a crucial safeguard against unauthorized access, data breaches, and compliance violations. This comprehensive framework outlines strategies and procedures to identify, monitor, and protect valuable data assets across an organization’s network, endpoints, and cloud environments.

Authentication is the process that verifies the user's identity to control access to resources, prevent unauthorized users from gaining access to the system, and record user activities (to hold them accountable for their activities). It is used to authenticate users who log on to a server, ensure that software comes from a reputable source, and ensure that the person sending the message is who he says he is.

The increasing reliance on open-source software coupled with the accelerated pace of software development has created a growing need for support of deprecated packages. The significant majority of open-source software packages are not actively maintained, meaning vulnerabilities are not patched, thereby leaving systems open to attack. Malicious actors often target deprecated open-source packages for this very reason.