

Binance founder Changpeng Zhao says fully transparent on-chain transactions expose salaries and business data, blocking real-world adoption of crypto payments.
Summary
Unexplained Chinese bot traffic is colliding with a second, quieter crisis: AI‑driven forgery and identity abuse that even crypto’s most seasoned insiders now struggle to parse.
In a recent Wired article, the author notes that over the last several months of 2025 and into 2026, small publishers, corporates, and even US agencies have watched their analytics fill up with “visitors” from Lanzhou and Singapore—sessions that rarely touch servers, leave no firewall traces, and yet dominate GA4 dashboards. As one analytics firm bluntly summarized it, these are “ghost sessions” generated by bots capable of triggering measurement calls while mimicking basic user behavior. The effect is not just technical noise: inflated sessions distort engagement metrics, ad yield, and campaign performance, especially for niche sites where a few hundred fake visits can flip a trend line.
This fog of synthetic traffic lands at the same time as a deepfake wave that is starting to outpace human intuition. Changpeng “CZ” Zhao recently admitted that an AI‑generated clip in flawless Mandarin was so accurate he “couldn’t distinguish that voice from [his] real voice,” calling the realism “scary” and warning that “even a video call verification will soon be out of the window.” His alarm follows scams where fully AI‑generated meeting participants convinced a Hong Kong finance team to wire roughly 25 million in corporate funds.
Zhao has begun to connect these threats to a deeper structural flaw in today’s internet and in public blockchains themselves. Privacy, he argues, is a “fundamental human right,” yet “current blockchains… provide too much transparency,” especially once KYC data links real‑world identities to on‑chain addresses. He has described the “lack of privacy” as “the missing link holding back crypto payment adoption,” warning that fully transparent ledgers make salaries, vendor flows, and even “ice cream preferences” trivially traceable.
The irony is brutal. On one side, overstated transparency—hyper‑indexed traffic logs, fully public transaction graphs—creates rich attack surfaces for state‑scale scrapers and commercial data brokers. On the other, AI systems now generate fake humans, fake traffic, and fake “proof” at industrial scale, eroding trust in every digital signal, from a GA4 session to a board‑level video call. When analytics can be flooded from servers routed through Singapore while GA4 “thinks” it sees Lanzhou, even basic questions (“Who visited my site?”) become non‑trivial.
Zhao’s answer is not to abandon transparency, but to harden it—pushing for privacy‑preserving tools such as zero‑knowledge proofs, and for verifiable identity rails that can flag deepfaked personas without exposing full financial lives on‑chain. In practice, that means building systems where origin, integrity, and consent can be cryptographically checked, while granular data—whether web sessions or payroll flows—remains shielded by design. The alternative is visible in today’s dashboards: a web that looks “busy,” yet is increasingly unreadable.
These moves comes as digital assets continue to trade as the purest expression of macro risk appetite. Bitcoin (BTC) is hovering around $68,531, with a 24‑hour range between roughly $68,096 and $70,898 on about $39.4B in volume. Ethereum (ETH) changes hands near $2,053, after a 24‑hour move of about 5.5%, with trading volumes above $22.5B and recent lows under $1,910. Solana (SOL) has recently traded in the $200–$220 band, with on‑chain liquidity crossing 1B and bulls eyeing the $236–$252 zone.
For now, bots from “Lanzhou” and face‑swapped executives share a common lesson: in an AI‑saturated market, privacy and transparency are no longer opposites. They are joint prerequisites for any data stream investors can still afford to trust.






