Credit monitoring is a service that tracks any changes made to your credit reports that could be signs of fraud or identity theft. It is helpful to be alerted in real time to any new accounts being opened in your name, changes to your credit or missed payments. Continue reading to learn what credit monitoring does, if it’s worth it and how to protect yourself from becoming a victim of fraud and identity theft.

You can tell if your computer has a virus by looking for warning signs, such as slower performance speed, increased pop-ups, frequent crashes or freezes, reduced battery life and unfamiliar files. A computer virus is a type of malware that requires user interaction to infect your computer. Computer viruses can disguise themselves as email attachments in phishing scams, illegitimate files, altered code or pirated software.

In this digital age, enterprises in all industries are creating and accumulating an astronomical amount of sensitive data to store and exchange. Given a prevalence of highly sensitive data, preventing it from getting into the wrong hands or avoiding data loss by accident has become a top priority. While on surface data loss vs data leak can look harmless, it can lead to financial losses, reputational damages, and even trigger litigation.

The traditional methods of detecting and mitigating cyberattacks will no longer be adequate as these attacks become sophisticated and frequent. These days, risk-based alerting and network detection and response (NDR) are regarded as essential tools for safeguarding enterprises. By avoiding false positives or low-priority warnings, risk-based alerting allows security teams to concentrate on the high-risk threats, saving time and resources.

Discover key takeaways from SOSS Fusion 2024, where security experts gathered to learn from one another about improving our world, AI, and the future of open-source security.

By James Rees, MD, Razorthorn Security In today’s complex cybersecurity landscape, Governance, Risk and Compliance (GRC) tools have become essential for organisations managing intricate security ecosystems. These tools are designed to centralise information, streamline processes and offer crucial insights into an organisation’s risk posture. However, as cybersecurity expert Jack Jones revealed when he joined me on a recent podcast, the reality often falls short of these ambitious claims.

False positives in API security are a serious problem, often resulting in wasted results and time, missing real threats, alert fatigue, and operational disruption. Fortunately, however, emerging technologies like machine learning (ML) can help organizations minimize false positives and streamline the protection of their APIs. Let's examine how.

There are several tactics that threat actors can use to access cloud environments, services, and data. A common example is lateral movement, which involves techniques that enable a threat actor to pivot from one host to the next within an environment. This type of activity often uses other tactics, such as initial access and privilege escalation, as part of a larger attack flow.