Ripple presses SEC to lock in XRP’s post-lawsuit status

ambcryptoPublished on 2026-01-12Last updated on 2026-01-12

Abstract

Ripple has formally requested the SEC's Crypto Task Force to adopt a legal framework that would exempt tokens like XRP from securities law once the original fundraising obligations end. The company argues that securities regulations should only apply during the initial sale where a direct legal relationship exists between issuer and buyer, not to secondary market trading. This approach aims to prevent what Ripple calls the "zombie promise" problem, where outdated issuer statements bind later buyers. Instead, mature crypto markets should be governed by commodity-style rules. The proposal aligns with Ripple's ongoing legal defense against the SEC's claim that XRP is a security. The timing is significant as U.S. crypto regulation evolves, with Congress preparing new legislation and the SEC shifting toward formal rulemaking. If adopted, this framework could permanently exclude XRP and similar tokens from SEC securities oversight.

Ripple has formally asked the US Securities and Exchange Commission’s Crypto Task Force to adopt a legal framework that would allow tokens such as XRP to fall outside securities law once an issuer’s original fundraising obligations have ended.

In a 9 January letter to the SEC, Ripple argued that crypto regulation should follow “the lifespan of the obligation”, not permanently attach securities status to a token simply because it was once sold in a capital-raising transaction.

The request comes as Congress prepares to finalize market-structure legislation and the SEC, under Chair Paul Atkins, begins rewriting its crypto rulebook through its new Crypto Task Force.

The legal framework Ripple is pushing

At the center of Ripple’s submission is a bright-line distinction between a securities transaction and the asset that trades afterwards.

Ripple argues that securities law should only apply where there is privity — a direct legal relationship between the issuer and buyer in a primary sale that creates enforceable rights and obligations.

Once that relationship ends, the token should no longer be subject to securities jurisdiction.

Ripple warned that treating every issuer sale as a permanent capital raise leads to what it calls the “zombie promise” problem, where decades-old statements are deemed legally binding on secondary-market buyers who never saw them.

In mature markets, such as crypto exchanges, Ripple argues that commodity-style rules, rather than securities law, should govern trading.

This is because buyers are relying on liquidity, price discovery, and utility rather than issuer promises.

Why this matters for XRP

Ripple’s position directly reflects its multi-year legal battle with the SEC over whether XRP is a security.

The SEC’s original lawsuit was based on the idea that Ripple’s sales of XRP created an ongoing investment contract.

Ripple is now arguing that even if XRP was once distributed through securities-like transactions, the token itself should not carry permanent securities status once those promises expire.

Under Ripple’s framework, XRP would be regulated only when Ripple itself is making enforceable commitments, not when the token trades between third parties on exchanges.

That would embed Ripple’s courtroom defense into federal policy.

Why the timing matters

The US crypto regulatory system is shifting rapidly. Congress has already passed the GENIUS Act on stablecoins and is preparing comprehensive market-structure legislation for early 2026.

Meanwhile, the SEC has launched Project Crypto to transition from an enforcement-first approach to formal rulemaking.

Ripple is positioning XRP inside that new framework before the rules are finalized.


Final Thoughts

  • Ripple is seeking a legal standard that would permit crypto tokens to be traded as non-securities once the original fundraising obligations have been fulfilled.
  • The framework could permanently remove XRP and many similar tokens from SEC securities jurisdiction.

Related Questions

QWhat is Ripple formally requesting from the SEC's Crypto Task Force?

ARipple is formally requesting the SEC's Crypto Task Force to adopt a legal framework that would allow tokens like XRP to fall outside securities law once an issuer's original fundraising obligations have ended.

QWhat is the core argument Ripple makes in its submission to the SEC?

ARipple's core argument is that securities law should only apply where there is a direct legal relationship (privity) between the issuer and buyer in a primary sale. Once that relationship ends, the token should no longer be subject to securities jurisdiction.

QWhat problem does Ripple warn about regarding 'zombie promises'?

ARipple warns that treating every issuer sale as a permanent capital raise leads to the 'zombie promise' problem, where decades-old statements are deemed legally binding on secondary-market buyers who never saw them.

QHow does Ripple's proposed framework specifically benefit XRP?

AUnder Ripple's framework, XRP would be regulated as a security only when Ripple itself is making enforceable commitments, not when the token trades between third parties on exchanges. This would embed its courtroom defense into federal policy.

QWhy is the timing of Ripple's request significant?

AThe timing is significant because the US crypto regulatory system is shifting rapidly with new legislation and the SEC's transition to formal rulemaking. Ripple is positioning XRP inside this new regulatory framework before the rules are finalized.

Related Reads

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit1h ago

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit1h ago

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit1h ago

Token Inefficient, Economy Tokenless

marsbit1h ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit1h ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit1h ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit1h ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit1h ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbit1h ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbit1h ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of S (S) are presented below.

活动图片