Машинное обучение и ИИ каждый день помогают «Лаборатории Касперского» выявлять около полумиллиона новых киберугроз

The main problem now is the lack of automated tools for detecting deepfakes in real time

Artificial intelligence and machine learning help Kaspersky Lab detect about half a million new cyberthreats daily. This was announced by Mikhail Gerber, Director of the Consumer Business Department of the company, at SPIEF-2025.

Machine learning and artificial intelligence have burst into our lives rapidly and are changing it in all areas... In particular, today we detect up to half a million new malicious objects a day thanks to these technologies, while our specialists are busy with complex and sophisticated threats, which are also abundant.
Mikhail Gerber

Attackers, like cybersecurity professionals, are constantly improving their methods. According to the expert, the main problem is the lack of an automated tool that can detect deepfakes in real time.

Gerber reminded that it is important for mobile device users to be vigilant. You should not communicate with strangers if the purpose of the call is unknown. He also advised not to leave your profile open on social networks. This will help avoid creating deepfakes using your photos.

If you are asked to provide any confidential or personal data, an SMS code, or transfer money, always try to make sure that you are communicating with the person they claim to be.
Mikhail Gerber

It is better to call back the official number of the company that the person allegedly represents through other communication channels, for example, by landline.

Earlier, Mikhail Gerber warned that the number of malicious programs found on fake Android smartphones is growing in Russia. Attackers introduce viruses into devices during flashing and then sell them, including via the Internet.

Read more on the topic:

Sber Discovered More Than 200 Groups of Fraudsters Renting Accounts for Cold Calls

Passing off malicious software as useful programs: Russians warned about fake KeePass

Hackers break into smart devices in homes and force them to "work" for them

Fraudsters most often "hunt" for the elderly, children, and cryptocurrency owners

It became known who telephone scammers most often pretend to be