Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Managing the risks of AI development tools is crucial for organizations looking to responsibly and effectively leverage this technology’s potential. AI offers transformative capabilities, particularly in coding assistance, where tools can speed up development and reduce manual workloads. However, these benefits can come with risks, such as security vulnerabilities and compliance challenges, that cannot be overlooked.

As organizations continue to evolve their DevSecOps programs by adopting comprehensive testing and monitoring, the next step is to take action on the insights uncovered. This means remediating security issues as early as possible and responding to security alerts and incidents in a timely manner. However, many security and development teams find that triaging the findings of every tool and managing remediation efforts is time-consuming and costly.

Managing PostgreSQL access is a pain for engineering teams. Setting up users, roles, and keeping track of permissions slows down engineers. Security risks may emerge in the form of shared admin accounts or missteps in user setup or authorization workflows. Check out this screenshot from a Reddit thread discussing this problem.

Generative AI is changing industries by making automation, creativity, and decision-making more powerful. But it also comes with security risks. AI models can be tricked into revealing information, generating harmful content, or spreading false data. To keep AI safe and trustworthy, experts use GenAI Red Teaming. This method is a structured way to test AI systems for weaknesses before they cause harm.

On 7 February 2025, it was reported that the UK government had demanded that Apple allow access to encrypted user data worldwide. Under current security policies, only the account holder can access the stored data in Apple’s cloud services, meaning the technology organisation itself cannot view it.

Every day, security teams are expected to manage risks in cloud environments that they don’t fully control, can’t always see, and that are constantly changing. Cloud-native assets—such as container workloads, autoscaling groups, and serverless functions—are highly dynamic, appearing, disappearing, and evolving in response to demand and functionality changes.

Managing Common Vulnerabilities and Exposures (CVEs) is one of the most daunting challenges for Chief Information Security Officers (CISOs) today. In 2024 alone, over 40,000 CVEs were issued by the National Institute of Standards and Technology (NIST), forcing security teams to sift through an overwhelming volume of threats. With hybrid, multi-cloud networks expanding in complexity, manually identifying, prioritizing, and remediating vulnerabilities have become an unsustainable burden.

Did you know that there are approximately 12.52 million credit card users in Australia, along with 43.77 million actively issued debit cards? These figures reflect PCI DSS compliance in Australia’s heavy reliance on digital payments and card-based transactions for everyday purchases and online commerce. However, with this widespread adoption comes an equally significant risk which is the growing threat of data breaches and payment fraud.

Clone phishing is another scam that threatens our online security and data. Throughout this article, we will analyze what clone phishing is with real-world examples. In doing so, you can help identify this kind of scam and keep your personal and business information safe.

It’s safe to say that remote work is here to stay, and hybrid arrangements seem to be getting a boost in 2025. While flexible work models are highly desirable for employees, they create new cybersecurity challenges for businesses. Remote work has quickly become the norm, causing businesses to rethink security protocols. Implementing security measures outside of a centralized office requires a robust strategy—so how can you effectively mitigate risk while still ensuring operational efficiency?