For decades protecting identities meant looking after people. Banks and companies watched for stolen passwords, warning customers when someone used their details, notifying authorities and public breach registries when the worst came to pass.

Today a second problem has arrived: the identities of machines. Every app, software controller, robot and automated system needs its own digital identity to work. In many companies these machine identities outnumber human staff. Security teams face a double burden: they must protect both people and machines from identity theft. The machine side is far more difficult to spot.

People vs Machines

When a criminal steals a person’s identity, the victim usually notices. They might see a strange transaction on their bank statement or get a warning email. But there is a sneakier type of fraud where the criminal builds a fake person from bits of real data mixed with invented details. Because no real person exists, nobody complains. The fake identity quietly builds trust and access over months or years.

Companies have whole teams watching for this against human customers. But few realise the same trick works against machines. A criminal does not need to steal an existing software account. They can simply create a new one that looks like it belongs. They copy the naming style, put it in the right place and give it the same permissions as real machine accounts. Because companies create so many machine identities so quickly, a fake one blends in easily. There is no human owner to notice something is wrong.

Fraud against people and fraud against machines share the same root problem. But the machine version is harder to catch because there is no person to raise the alarm.

How Fake Machine Identities Hide

A fake machine identity looks convincing from day one. It uses the same naming rules as real accounts. It sits in the correct part of the company network. It asks for sensible permissions that other machines already have. To an administrator scrolling through thousands of software accounts, it looks like routine business. Nothing is stolen so no system flags a breach.

The real danger is silence. When a human identity is stolen, the real person might spot a login from an unusual location. When a machine identity is fabricated, nobody exists to notice. As companies add more and more automated systems, one extra fake account is invisible. It simply sits there, gathering access and power.

Human fraud has victims who sound the alarm. Machine fraud has no victims, only silent intruders.

Why AI Makes This Worse

In the past creating a fake machine identity took time and skill. Artificial intelligence is changing that. Modern AI systems can create new identities for themselves and for other AI agents automatically. They do this in the background while doing normal work. The boundary between a real machine identity and a fabricated one is becoming blurry. The speed and scale of AI means fake identities can now be created far faster than any human process could manage.

How Companies Can Fight Back

The answer, stronger governance from the first interaction. Fake identities must not be allowed to blend in, build up access through automatically provisioned groups & allocations, accidental inclusions, migratory permissions or hidden in the forgotten automations of services management applications.

Give every machine a human owner. Every software account needs a named person responsible for it, a clear reason it exists and a reasonable expiry date. When someone owns a machine identity, they can watch for abuse, when a machine watches a machine, it’s looking for the shortest path to process completion. This connects the human world to the machine world.

Rotate passwords and keys automatically. Criminals often hide their own access codes inside existing accounts, some dormant, some reactivated by another service user. If a company changes all machine passwords and keys automatically and frequently, any hidden criminal access quickly becomes useless.

Limit what each identity can do. Every service account should only have the minimum access it needs and only for the time it needs it. If a fake identity is created, it inherits only a tiny window of power instead of permanent access. This limits damage from any identity, real or fake.

Watch behaviour, not just creation. Too many companies check an identity once when it is set up and then trust it forever. The better approach is to watch what each identity actually does over time. Unusual behaviour reveals fake identities that looked perfect on day one.

The Bottom Line

Companies have spent years protecting real identities from criminals, turning a blind-eye to the 100’s of service accounts running their infrastructure. Now they must also find identities that were never real to begin with. Machine identity security means every account has an owner, every password is short lived and every action is watched. Once companies accept that identity fraud threatens both people and machines, they can build defences that cover the whole picture.