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$0.60 or $31 Next for XRP?

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XRP Bull Buys the Dip as Ripple's Price Gets Obliterated by 22% in Just 1 Day


Where is XRP heading next? Here are some of the recent predictions and analyses.

Ripple’s cross-border token has often been the object of some wild price predictions, many of which might sound absurd at the time being. However, its infamous volatility has proved that it can produce massive gains (or drop violently) in the span of just weeks and months.

In this article, we will review some of the latest bull and bear cases, one of which was even called precision and not ‘hopium.’

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XRP’s Bull Predictions

We will begin with the more ‘modest’ forecast coming from perma-XRP bull John Squire. In a recent post, he outlined some rumors that Ripple’s US national bank license is set for approval. Without providing any further details on the matter, he added that such a “major step for crypto adoption and institutional finance” can instantly send the underlying token to $5.

EGRAG CRYPTO, an analyst also known for their pro-XRP calls, relied on technical analysis to determine the asset’s next targets. They indicated that the long-term XRP chart shows a 814% surge during the first Elliott Wave, which transpired between 2015 and 2018. The subsequent corrective wave 2 took the asset south by over 70% to under $0.12 during the 2020-2022 bear market.

The analyst believes XRP is approaching the third wave, but it still needs to confirm it by reclaiming the wave 1 high of over $3.40 with a strong “weekly close and momentum expansion.” Until that happens, the asset is “still corrective.”

If it does, though, the sky would be the limit for the cross-border token, with EGRAG indicating a massive price target of somewhere between $15 and $31 during wave 3.

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Or, Below $1?

In the opposite corner stands Ali Martinez, who, instead of going with the hype and predicting some mind-blowing bull targets, outlined XRP’s most significant support levels in case another correction is to take place. The token has plunged by over 60% since its July 2025 all-time high, and currently struggles to remain above $1.40.

He noted that Ripple’s token could find some support “along the triangle’s hypotenuse between $0.90 and $0.60” if it loses the coveted $1.00 defense level. Recall that XRP dipped to $1.11 on February 6 when the entire market collapsed, but has remained above that line since then.

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Axiom Crypto Exposed: ZachXBT Alleges $400k Insider Trading

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Axiom Crypto Exposed: ZachXBT Alleges $400k Insider Trading

ZachXBT just uncovered what looks like a coordinated insider trading ring at Axiom crypto. According to his findings, senior employees used internal data tools to front-run user trades for more than 10 months, allegedly pocketing over $400,000 in the process. The method involved privileged back-end access that allowed staff to track and mirror high-value wallets before the broader market reacted.

This points to deeper governance failures at a platform generating roughly $390 million in annual revenue. Non-technical staff reportedly had unrestricted access to live user identifiers, exposing a serious breakdown in internal controls.

Key Takeaways

  • The Actor: Senior business development staff with unrestricted admin access to live user databases.
  • The Method: Cross-referencing internal UIDs with on-chain data to identify and front-run KOL wallets.
  • The Failure: A YC-backed unicorn generating $390M revenue operating with zero role-based access controls.

How the Insider Trading Scheme Operated Inside Axiom Crypto

The scheme was simple and effective. Investigators say employees used internal admin dashboards meant for support and compliance to pull private user data. By linking User IDs to on-chain wallets, they could identify high-profile traders and institutions behind supposedly anonymous addresses.

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From there, the play was straightforward. Monitor activity, then trade ahead of it. Buy before a large wallet pushed price. Sell before a whale exits. It was front-running their own users.

The activity reportedly lasted at least 10 months. The troubling part is that business development staff had the same level of system access as technical security teams. That breakdown in internal controls created the information asymmetry that made the scheme possible.

Discover: The best crypto to diversify your portfolio with

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$390M Revenue vs. Zero Access Controls: What Is Axiom Team Response?

Axiom generated $390 million in revenue and scaled rapidly, but the investigation shows its internal controls lagged far behind its growth.

The platform reportedly lacked basic role-based access controls. Business development staff had broad visibility into user identifiers and trading data, creating a “God mode” environment. Proper least-privilege systems and audit logs likely would have flagged the activity early. Instead, it allegedly went unnoticed for nearly a year.

The case highlights a common startup flaw: growth and volume are prioritized, while governance is deferred. That works at a small scale. At billions in volume, it becomes a liability.

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Axiom has confirmed a full internal audit. But the reputational damage is significant, and regulators may view the alleged $400,000 in insider profits as potential fraud.

Discover: The best new crypto in the world

The post Axiom Crypto Exposed: ZachXBT Alleges $400k Insider Trading appeared first on Cryptonews.

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Pantera, Franklin Join Sentient Arena AI Agent Testing Initiative

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Pantera, Franklin Join Sentient Arena AI Agent Testing Initiative

Pantera Capital and Franklin Templeton’s digital assets units have joined the first cohort of Arena, a new testing environment from open-source AI lab Sentient that is designed to evaluate how AI agents perform in enterprise-style workflows.

In a Friday announcement shared with Cointelegraph, Sentient positioned Arena as a production-style benchmarking platform rather than a static model test. Instead of scoring agents on fixed datasets alone, it runs them through standardized tasks modeled on enterprise conditions, including long documents, incomplete information and conflicting sources. 

“In this initial phase, participation refers to supporting the Arena program and developer cohort,” Oleg Golev, product lead at Sentient Labs, told Cointelegraph.

He said partners are helping shape what “production-ready reasoning” looks like for document-heavy tasks such as analysis, compliance and operations. The companies are not announcing capital commitments tied to the initiative. 

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Related: Jack Dorsey’s Block to cut 4,000 jobs in AI-driven restructuring

The launch comes as enterprises accelerate the deployment of AI agents into research and operational workflows, even as governance frameworks lag. 

According to the Celonis 2026 Process Optimization Report, published Feb. 4, 85% of surveyed senior business leaders aim to become “agentic enterprises” within three years, while only 19% currently use multi-agent systems.

The 2026 Process Optimization Report. Source: Celonis

Production-style evaluation, not static scoring

Golev described Arena as a shared platform where developers submit AI agents to standardized tasks and compare results under consistent testing conditions.

The platform tracks failure categories such as hallucination, missing evidence, incorrect citations and reasoning gaps, allowing developers to diagnose recurring issues.

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Arena plans to publish comparative performance metrics through a public leaderboard and release postmortems summarizing common failure modes and fixes.

Infrastructure partners, including OpenRouter and Fireworks, are supplying inference compute for the initial cohort, while other partners support tooling and workshops.

Related: High-yield bond surge signals rising risk, demand in BTC mining, AI infrastructure

Governance layer amid rising AI autonomy

The initiative emerges as financial and crypto companies experiment with giving AI systems greater economic autonomy.

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On Wednesday, MoonPay launched infrastructure enabling AI agents to create wallets and execute stablecoin transactions.

On Thursday, Stripe executives warned that blockchains may need significant scaling improvements if AI-driven commerce expands.