According to Dune Analytics: Kaito is potentially facing a Centralized Staking Risk, with 23M KAITO potential sell pressure building up

Article Source: TokenPost

According to on-chain data monitoring by Dune Analytics, Kaito is currently in a highly sensitive liquidity window. A significant amount of staked tokens has entered the unstaking cooldown queue, potentially leading to concentrated near-term secondary market inflows. Coupled with subsequent unlocked nodes, the project may face a sustained selling pressure test.

I. Unstaking Risk Quantified: Nearly One-Third of Staked Tokens Exiting

Based on Dune dashboard data:

Approximately 8M KAITO in the unstaking cooldown queue

Total remaining staked amount for the project is around 23.97M

This means that close to 33% of staked tokens have entered the unstaking process and will be released to the market shortly.

This ratio is not commonly seen in similar staking model projects and is often regarded as a "systemic liquidity warning signal."

II. 48-Hour Concentrated Release: Short-Term Liquidity Pressure Highly Concentrated

Further breakdown of the unstaking timeline reveals that this round of unstaking is not naturally dispersed but highly concentrated.

Dune data shows:

Jan 22: Approximately 4.85M KAITO unlocked and withdrawable

Jan 23: Approximately 2.1M KAITO to be unlocked

Total over 48 hours: Around 8M KAITO potentially entering the circulating market

Simultaneously, unstaking requests were predominantly concentrated between Jan 18-21, with daily request counts maintained at 50–70 transactions, demonstrating a clear pattern of collective withdrawal.

This behavioral pattern aligns more with "risk-averse exits" rather than normal position rotation.

III. Potential Chain Reaction: 23M Staked Tokens May Face "Stomping Unstaking"

Of concern is that the current release of 8M KAITO is not the only risk.

Under the staking mechanism, once the secondary market price faces pressure, the remaining 23.97M

KAITO stakers are highly likely to unstake passively, forming a typical negative feedback loop:

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