That is the ugly truth. AI does not magically create elite hackers. It lowers the bar. And lowering the bar in cybercrime is dangerous because the internet already runs on trust shortcuts.

A simple mental model I keep using

Think of AI like a power tool. A hammer can build a house or smash a window. The tool itself is neutral, but the scale changes everything. A scammer with AI is like a kid who suddenly got a factory instead of a screwdriver. They can test, iterate, and attack way faster than a human ever could by hand.

That means our defenses cannot stay manual and static. If your security process still depends on one tired reviewer spotting a suspicious email or one basic regex catching bad input, yeah, that is not enough anymore.

What I think teams should actually do

I am not interested in security advice that sounds good in slides and dies in production. So here is the practical stuff I would care about if I were shipping a product today:

• Use phishing resistant MFA where possible, especially for admin and support accounts.

• Treat password reset and account recovery like high risk attack surfaces, because they are.

• Add stricter rate limits and behavior checks around signup, login, and OTP requests.

• Review your UX copy and make sure it is not easy to spoof in emails, previews, or fake support flows.

• Log the right signals so anomaly detection has something useful to work with, not just noise.

A tiny detection idea you can borrow

If you are building a product with messaging, inboxes, invites, or external links, start by scoring suspicious behavior instead of trying to block everything upfront. A simple approach could look like this:

type RiskEvent = {
  ipRisk: number
  accountAgeDays: number
  failedLoginsLastHour: number
  linkClicksLast10Min: number
  passwordResetRequestsLastDay: number
  unusualGeoChange: boolean
}

function scoreRisk(event: RiskEvent) {
  let score = 0

  score += event.ipRisk * 3
  score += event.accountAgeDays < 3 ? 2 : 0
  score += event.failedLoginsLastHour * 2
  score += event.linkClicksLast10Min > 20 ? 3 : 0
  score += event.passwordResetRequestsLastDay > 2 ? 4 : 0
  score += event.unusualGeoChange ? 5 : 0

  return score
}

const risk = scoreRisk({
  ipRisk: 7,
  accountAgeDays: 1,
  failedLoginsLastHour: 4,
  linkClicksLast10Min: 26,
  passwordResetRequestsLastDay: 3,
  unusualGeoChange: true,
})

if (risk >= 15) {
  console.log("step up auth, slow down actions, and flag for review")
}

This is not magic. It is just a better posture. You do not need perfect certainty. You need enough signal to make abuse expensive.

What the defender side gets right

The hopeful part is that AI is also helping security teams move faster. Vulnerability discovery, fuzzing, triage, log analysis, threat hunting. All of that becomes more scalable if we use the tools well. That Mozilla and Anthropic result about finding hundreds of zero days is a pretty loud reminder that the same tech can expose weaknesses before attackers do.

And that is where I get optimistic. Not naive, just optimistic. Because every time an attack class gets easier, defenders also get access to better automation. The long game is not humans versus AI. It is humans plus AI versus humans plus AI.

The real question

Are we building products that assume trust, or products that verify by default? That is the fork in the road. If the future is full of agentic tools, automated fraud, and synthetic persuasion, then the apps we ship need to be much less gullible than they are today.

I want to live in a world where AI helps us secure the internet faster than criminals can abuse it. Maybe that sounds idealistic, but I do think this is one of those moments where infrastructure decisions matter a lot. A lot a lot.

So yeah, my takeaway is simple. AI is not just changing how we build software. It is changing how software gets attacked. And if we get serious now about identity, telemetry, abuse detection, and better UX around trust, we can still stay ahead of the curve instead of getting dragged behind it.

If you are working on a product right now, ask yourself one thing: where would an attacker use convincing language, scale, or automation to fool your users or your systems? That answer is probably where your next security fix should go.