Systems | Development | Analytics | API | Testing

According to a recent survey by AppDirect, half of IT decision-makers are losing sleep over security. It's no surprise, given that 45% of respondents have experienced a security breach in the last year. The threat of vulnerabilities and cyber security attacks is on the rise, and the impact of an incident can be devastating. Having the right DevSecOps strategy helps, but getting the right toolchain in place is crucial.

Artificial intelligence (AI) is kind of a big deal. And when things are a big deal, they're ripe to be exploited. Fortunately, mounting concerns about AI security and privacy are met by plenty of guidance on best practices from the good folks in the open source world. The OWASP AI Security Project has emerged as a crucial initiative, offering developers clear, actionable guidance on designing, creating, testing, and procuring secure and privacy-preserving AI systems.

Today’s enterprise networks are complex. Potential attackers have a wide variety of access points, particularly in cloud-based or multi-cloud environments. Modern threat hunters have the challenge of wading through vast amounts of data in an effort to separate the signal from the noise. That’s where a security data lake can come into play.

On July 19th, 2024, the world witnessed a large-scale computer outage caused by a faulty update from cybersecurity giant CrowdStrike. This incident, affecting millions of Windows devices globally, serves as a stark reminder of the domino effect that software errors can have. Since then, CrowdStrike and other industry experts have shared their preliminary incident report in which they outline the incident and the steps they will take to prevent future issues like this.

On July 19th, 2024, the world witnessed a large-scale computer outage caused by a faulty update from cybersecurity giant CrowdStrike. This incident, affecting millions of Windows devices globally, serves as a stark reminder of the domino effect that software errors can have. In part one of this series, we discussed the role QA methodologies can play in preventing future outages.

Privacy and security are top priorities for Unravel and our customers. At Unravel, we help organizations better understand and improve the performance, quality, and cost efficiency of their data and AI pipelines. As a data business, we appreciate the scope and implications of privacy and security threats. This data sheet provides details to help information security (InfoSec) teams make informed decisions. Specifically, it includes: For additional details, please reach out to our security experts.

‍ A survey suggests that 61% of companies' compliance teams have identified that keeping abreast of upcoming regulatory changes should be a top strategic priority. This indicates that businesses are not only striving to meet current compliance requirements but are also proactively staying ahead of them. However, maintaining such compliance requirements needs tight security strategies.

From smart homes to wearable devices to connected cars, the Internet of Things (IoT) is bringing about a new era of hyper-connectivity. Experts expect investments in the IoT ecosystem to rise above $1 trillion in 2026 — with no signs of slowing down. Application programming interfaces (APIs) are the backbone of IoT, ensuring scalability and security across billions of connected devices.

Businesses are seeking ways to collect all the data from their digital sources and draw out patterns that can reinterpret human participation with automation. A vanguard in this attempt is the emergence of large language models (LLMs) powered by artificial intelligence (AI).