Gate User Reports $1.7 Million Asset Theft, Questions Facial Verification Bypass
User @jheioff claims their Gate verified account was hacked, resulting in the theft of approximately $1.7 million in assets. Despite having set up mobile, Google, and email verification, the user did not receive a verification code and did not provide facial recognition, a photo with ID, or screen recording.
The user refuted Gate's explanations point by point, questioning the authenticity of live verification, unbinding of mobile, and email changes, asserting these actions were not performed by them. Security logs show an internal network IP, and they strongly demand the release of the complete evidence chain, freezing of the addresses involved, and compensation.
Source: Public Information
ABAB AI Insight
Gate has previously responded to similar security incidents, and this user's detailed rebuttal highlights ongoing controversies regarding the transparency of account reset processes and the reliability of facial verification, especially concerning potential AI forgery.
From a capital perspective, the platform's risk control system allows for quick withdrawals after resets, leading to user funds being emptied rather than frozen. Resources are focused on post-incident explanations rather than prevention, motivated by a balance between user experience and risk control costs.
Similar recent complaints from Gate users about asset theft, along with cases of facial verification being bypassed by AI, indicate that exchanges are currently in a transitional phase where security technology is lagging behind attack methods.
This fundamentally relates to technological substitution and regulatory changes: facial and multi-factor verification are questioned for being bypassed, stemming from opaque review processes and advancements in AI tools, which shift pricing power towards platforms. Users' ability to hold platforms accountable relies on public logs and regulatory intervention to rebuild trust.
ABAB News · Cognitive Law
Failure of multi-factor verification leads to a collapse of trust; the transparency of facial review determines the platform's survival.
Victims face challenges in providing evidence; a closed evidence chain from the platform is necessary to mitigate public sentiment.
With the escalation of AI attacks, if exchanges lag in security investment, user assets remain vulnerable.