Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

On June 2, 2026, President Trump signed Executive Order 14409, "Promoting Advanced Artificial Intelligence Innovation and Security." The framing is innovation first. But for federal network and security teams, the practical reality is a short, specific timeline to harden government systems, with AI now active on both sides of the cybersecurity equation. The deadlines are not aspirational.

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.

Over the last decade, while working with Fortune 500 enterprises and some of the most secure government networks on the planet, I’ve consistently heard the same question: “Can your software tell me what will happen if I push this change?”

CVE-2025-53521 was first disclosed by F5 in October 2025 as part of their quarterly security advisory cycle. At that point, it was classified as a denial-of-service vulnerability with a CVSS v4 score of 8.7. Many security teams logged it and moved on, reasonably treating it as a lower-priority item in an already full patch queue.

Walking the halls of Moscone Center last week, the energy was high, but the conversation had a notably different edge than last year. In 2025, everyone was asking, "What can AI do?" This year, "How can we trust it?" As the theme "The Power of Community" echoed across the keynotes, one thing became clear: a community is only as strong as its foundation. For network and cybersecurity professionals to truly operate as one, we must move beyond fragmented data to a single, trusted source of truth.

Network engineers have long understood redundancy. Redundant power, redundant links, redundant clusters. The reasoning is simple: any single component that can fail, will. But AI introduces a category of failure that most infrastructure teams have not yet built defenses against. Unlike hardware, AI models can become unavailable for reasons entirely outside your organization's control.

Every organization has invested in endpoint detection, identity, and cloud security, yet breaches continue to occur. You’ve secured the individual points but lack the context of how those points connect; you haven't secured the paths attackers navigate. Security teams are running more tools than ever: EDR on every endpoint, MFA for every identity, CSPM on every cloud tenant, and SIEMs ingesting terabytes of logs.