When people ask me about nation-state threats on Election Day, they usually picture the same scene. A hacker in a dark room breaks into a voting machine and quietly flips votes to put a favored candidate in office.

It makes a great movie plot. But after 20 years as a cyberspace operations officer in the Air Force and a long career in federal IT, I’ve seen that influence campaigns usually aim at something softer and easier to reach. They go after the shortcuts we all use to decide what's true, like a blue check mark, a pile of likes, or a video that looks too real to question.

Those shortcuts are a form of implicit trust, and attackers exploit the same weakness inside corporate networks. As voters head to the polls on November 3, the lesson for security leaders is simple.  

Zero Trust works because it swaps assumptions for verification, and that habit is the best defense against nation-state influence, whether it targets a voter’s feed or your network.

Seeing is no longer believing

Not long ago, a photo or video was close to proof. Today, just because I see something with my own eyes doesn’t make it true. AI tools can create a convincing fake image, voice clip, or video in minutes.

Influence campaigns only need content that looks real enough to get shared before anyone checks it. Once it spreads, the damage is done, even if someone debunks it a day later.

Everyone wants an easy button

Most people won’t spend much time researching what they see online. We look for an easy button, some sign that someone else already did the work and we can trust it.

Security teams know this pattern well, because networks ran on easy buttons for years. A device on the corporate network, a valid login, or a familiar IP address meant a system was trusted. Attackers count on that. Once they get a foothold, they use that built-in trust to move from system to system.

Elections face the same risk. In its 2026 election security plan, CISA noted that election systems are often reachable from general business networks, which lets attackers exploit known flaws and move laterally.

Validation you can scale

I’d like to see more AI tools that check a claim against other sources and give it a confidence score. Something like, “I can’t find this anywhere else, and no news outlet has reported it.” That kind of seal confirms the content has been checked and appears legitimate, without taking a side on what it says.  

Human researchers can’t keep up with the flood of content, so this work needs automation.

That’s how Zero Trust works inside a network, too. Every request gets checked based on who’s asking and what they need, every time. Microsegmentation enforces least-privilege access, so even when something slips through, it can only reach what it’s allowed to reach.

Take a beat before you pass it on

For individuals, the best defense is a pause. If something sounds sensational, check it first, and don’t let your own bias lead you down a path. Run a quick search to see if it shows up anywhere else, or ask your favorite AI model to help validate it. You’ll often find something that debunks it right away.

Security teams need the same habit. When an alert, a claim, or a strange request lands on your desk, verify it before you act. And plan for the moments when something gets past you. Breach containment helps keep one bad decision from turning into a much bigger problem.

Implicit trust is a risk you can’t afford to keep

The volume of AI-generated content is growing faster than any person or team can review it. Influence campaigns also don’t end when the polls close.  

Any organization that depends on public confidence, from banks and hospitals to utilities and agencies, is a target every day of the year.

In my career, I’ve learned that adversaries go after whatever we take for granted. Right now, that’s implicit trust in what we see online and in what’s already inside our networks.  

Every month AI makes a fake easier to produce and harder to spot, and every month an organization runs on implicit trust, it hands attackers more room to work.