Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

It has been a week since we announced Forward Predict at our Innovation Day broadcast, and I'm still taking it in. Since the inception of networking, the industry has been working without a safety net, making changes in the production network without knowing their impact beforehand. The result has been outages and security breaches. This wasn’t a lack of diligence, it was because there was no way to know, with certainty, what a change would do to the production network before it was pushed.

Network security is operationally complex. It involves constant triage, approvals, and monitoring, spread across a range of tools, teams, and environments. Traditionally, this requires teams to do a significant amount of time-consuming, repetitive, and draining manual work, resulting in a longer MTTR and leaving many practitioners overwhelmed and burnt out. The problem isn’t in the tools they use – it’s in the work that happens between tools.

Underlying the US–China AI race, there’s arguably a more sinister arms race—the race to identify zero-day threats. Frontier AI algorithms, such as Anthropic Mythos (here) and China’s Qihoo 360 (here), are compressing the zero-day discovery cycle. But how those discoveries are gathered and shared among cooperating entities is giving China significant defensive and offensive advantages.

Recently, JUMPSEC’s DART (Detection and Response Team) detected a phishing email targeting a client environment. The email, written in Thai and containing a MediaFire download link, was identified as suspicious by an incident responder and we kicked off an investigation. Since then, we have established infrastructure to track the threat actor, analysed the novel payload in detail, and identified several IoCs below.