The France Verif platform draws our attention to the rise, considered “worrying”, of the identity theft of town halls, a technique increasingly used by cybercriminals.
More and more town halls are seeing their digital identity being usurped. This is the observation made by France Verif, the web and mobile platform that detects online fraud and scams and protects cyberbuyers. The service has released a special edition of its monthly cyber scam barometer, in which it alerts us to an upsurge in town hall identity theft.
Cybercriminals exploit the (big) shortcomings of French town halls
The upcoming presidential election obliges many French people, these days, to approach their town hall in order to obtain or update their voter card, following a move, for example.
France Verif underlines it well, and rightly: many French town halls are still very behind in terms of computer security, sometimes due to a lack of human or financial resources, or quite simply a lack of will. It is therefore often easy for cybercriminals to hit the bull’s eye and trick employees or representatives of town halls to steal their digital identity.
Subsequently, hackers have as many opportunities to seize valuable information on citizens, who are tricked by the SIM swap technique, a technique favored by crooks, who manage to circumvent certain security systems, for example verification codes or identification SMS, by establishing another SIM card in the name of the victim in order to empty the bank account of the latter, with unstoppable ease.
The founders of France Verif have infiltrated the world of cyber crooks
The founders of France Verif, who spent a year infiltrating cyber crooks to understand their tools, methodologies and resources, were surprised by the diversity of frauds and their speed of propagation, lamenting that current solutions do not allow all the detect.
Together, they brought together engineers from Polytechnique, the Corps des Mines and the Pierre and Marie Curie Institute, to design an alloy of various artificial intelligences and excavation robots. A team of 43 people managed to filter, for a year and a half, some 500,000 e-commerce sites and gather the data necessary for the proper learning of AI.
Six changes of process were necessary, and seven data analysts are still scrutinizing the new types of scams emerging on the Web every day.
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