X Bans InfoFi Projects, KAITO Plummets 20% — Is This the End?

X’s decision to clamp down on so-called InfoFi applications has sent fresh shockwaves through the crypto market, dragging several tokens sharply lower and forcing a rethink across a niche that had grown tightly intertwined with the social media platform.

The immediate market reaction was led by KAITO, the token linked to the Kaito platform, which slid roughly 20% in a single day as investors digested what many saw as a structural threat rather than a short-term policy tweak.

X Cracks Down on Rewarded Posting, Shaking InfoFi Projects

The shift began with a public statement from Nikita Bier, X’s head of product, who said the company was revising its developer API rules to block applications that reward users for posting on the platform.

Bier said that these incentives had fueled a surge in low-quality replies, automated posts, and what he described as “AI slop,” degrading the overall user experience.

X confirmed that API access had already been revoked for affected apps, with Bier adding that developers whose accounts were terminated could seek help transitioning their businesses to other platforms such as Threads or Bluesky.

The announcement landed hard in crypto circles because many InfoFi projects are built around harvesting, analyzing, and monetizing X data.

Platforms like Kaito aggregate posts from large crypto accounts to identify trending narratives and then reward users, often in tokens, for producing content or engagement. That model left them exposed to any restriction on API access or posting incentives.

While X has not declared an outright ban on InfoFi as a category, the practical effect of cutting off rewarded posting has been to disrupt the core mechanics of several projects overnight.

Market data reflected that shock as KAITO token fell from around $0.70 to about $0.57 within hours, down roughly 17% to 20% on the day, while trading volume jumped nearly 87% to more than $121 million, suggesting forced repositioning rather than thin liquidity.

The token now trades more than 80% below its all-time high of $2.88.

Cookie DAO’s COOKIE token followed a similar path, dropping more than 20% in 24 hours to roughly $0.038, with volume also rising, a sign that holders were reassessing exposure as uncertainty spread.

Kaito, Cookie, Xeet Rethink structure After X Policy Shift

Behind the price action lies a deeper debate about whether InfoFi’s incentive structures were sustainable.

Critics had long argued that paying users to post encouraged attention farming and automated content, an accusation that gained credibility as timelines filled with repetitive, AI-generated replies.

Following the announcement, Kaito founder Yu Hu said the company would sunset its “Yaps” and open incentive leaderboards, replacing them with Kaito Studio, a more selective, tier-based marketing platform designed to work across X, YouTube, TikTok, and other channels.

Hu framed the shift as an alignment with both X’s policies and brands’ growing preference for targeted campaigns over mass distribution.

Other platforms echoed that reassessment, with Cookie announcing it was shutting down its Snaps creator campaigns after discussions with X, citing the need to protect the integrity of its data products and remain compliant with platform rules.

Xeet, another project caught in the change, said all campaigns had been paused while it evaluated next steps and worked through outstanding payouts.

In each case, teams stressed that their broader analytics or data businesses would continue, but the rewarded-posting layer was no longer viable in its previous form.

The episode has shown how dependent large parts of crypto’s social layer remain on a single Web2 platform.

X’s use of automated moderation tools and AI-driven detection has turned it into a powerful gatekeeper, capable of reshaping entire business models with policy updates.

It has also intensified discussion about alternatives, including decentralized social networks and multi-platform strategies, as builders seek to reduce single-point risk.