Over the last year, we have continued to witness web shells breaching organizations worldwide, affecting both edge devices and on-premise web applications. Web shells consistently evade standard controls, posing a persistent threat. Today, the Splunk Threat Research Team is excited to announce the final tool in the ShellSweep collection: ShellSweepX.

Howdy folks, it’s your friendly neighborhood transformational detection engineering evangelist Haylee Mills here. Maybe you’ve already been introduced to risk-based alerting, or maybe you’ve seen one of my many talks on the subject: Even if you haven’t, I’m super excited to share a brand new version of my step-by-step guide to success with the risk-based alerting framework!

As the Splunk Industry Advisor to the Australian public sector, I work closely with government organisations and their leaders to understand their goals, objectives and the challenges they face in achieving digital resilience. This blog shares perspectives on how Splunk works with the Australian government to provide a unique approach to solve some of the public sector's toughest challenges.

When it comes to cybersecurity, ransomware is probably one of the first threats you think of. It seems like it’s everywhere — and it is. Ransomware is one of the most notorious cyber threats affecting individuals, businesses, and organizations globally. The frequency and impact of these attacks have surged in recent years, making it crucial to understand their nature and how to protect against them.

In today's rapidly evolving cybersecurity landscape and complex compliance mandates, traditional Security Operations Centres (SOCs) are being transformed by the integration of artificial intelligence (AI) and machine learning (ML). At Splunk, we are no strangers to these technologies.

As outlined in a previous post, OpenTelemetry and Splunk Observability Cloud can provide great visibility when security teams investigate activity in modern environments. In this post, we look at another aspect of this visibility: how you can use traces to see directly into the workings of an application to find a potential threat. Let’s imagine we’re the security analyst, and a message comes across from the Security Operations Center (SOC).

In 2016, a house in Middle, Ohio, went up in flames. The owner of the home, Ross Compton, claimed he was asleep when the fire broke out, waking just in time to hastily pack a suitcase, smash his bedroom window, and make an escape. However, the very technology keeping Compton alive unraveled his alibi and led to his arrest. Compton had a pacemaker, and the police, suspicious of his account, secured a warrant to access its data.

The Splunk team is excited to announce the release of the latest addition to our security product portfolio, Splunk Asset and Risk Intelligence (ARI). The modern digital landscape is a complex mix of devices, users, and a wide array of products and applications, all spread across on-prem, cloud, and hybrid environments.

On the day that Splunk officially became part of Cisco, our leadership outlined key ways we’d come together to support customers to achieve business-critical outcomes, noting: In the short time since then, we’ve already made significant strides, demonstrated by our announcements of: As we continue to build on this momentum, we’re excited to announce the availability of Cisco Talos Incident Response services to Splunk customers.

As a small kid, I remember watching flying monkeys, talking lions, and houses landing on evil witches in the film The Wizard of Oz and thinking how amazing it was. Once the curtain pulled back, exposing the wizard as a smart but ordinary person, I felt slightly let down. The recent explosion of AI, and more specifically, large language models (LLMs), feels similar. On the surface, they look like magic, but behind the curtain, LLMs are just complex systems created by humans.