The article explains how online privacy is compromised by the aggregation of personal data through common identifiers used across multiple services, enabling data brokers to build comprehensive profiles without breaches or hacks. It highlights the exacerbation of this issue by AI's ability to correlate disparate data points. The proposed countermeasure is compartmentalization through multiple digital personas, each with unique identifiers, to prevent correlation and contain damage from breaches or spam. MySudo, developed by Anonyome Labs, implements this approach by allowing users to create up to nine separate personas, each with its own phone number, email, payment card, communication handle, and browser. This structural privacy model reduces the value of any single identity and does not rely on changes in internet-wide data practices.

The impact described is the erosion of individual privacy due to data brokers' ability to link online activities via shared identifiers, leading to profiling, spam, price discrimination, identity theft, and loss of control over digital identity. AI technologies have intensified this by improving data correlation. The use of single identifiers increases exposure to breaches and subsequent misuse of personal data. Compartmentalization limits these impacts by isolating identities, reducing the risk that a breach or data sale affects the user's entire digital profile.

This is not a vulnerability with a patch but a privacy risk mitigated by adopting compartmentalization strategies. The vendor (Anonyome Labs) offers MySudo, a tool that enables users to create multiple digital personas with separate identifiers to reduce correlation and exposure. Users are encouraged to use distinct emails, phone numbers, payment methods, and browsers per persona to contain damage from breaches or data broker profiling. No official patch or fix applies as this is a privacy practice and product solution rather than a software vulnerability.