Prosecutors Oppose Sam Bankman-Fried’s Request for New Trial

TheNewsCryptoPublished on 2026-03-12Last updated on 2026-03-12

Abstract

Prosecutors have opposed Sam Bankman-Fried's request for a new trial, arguing that he failed to present legitimate new evidence. Bankman-Fried’s motion, filed in February, claimed that testimony from two former FTX officials could have challenged the prosecution's fraud narrative, but prosecutors stated these witnesses were known prior to the trial and their testimony does not qualify as new evidence. They also argued that the testimony would not have altered the trial outcome, citing overwhelming evidence that Bankman-Fried misappropriated billions in customer funds. Additionally, prosecutors dismissed Bankman-Fried's claim that FTX was not bankrupt, noting a severe shortfall in cryptocurrency holdings compared to customer claims.

The prosecutors of the United States requested a judge to decline a request by former FTX CEO Sam Bankman-Fried for a new trial, claiming that the jailed crypto official has not been successful in showing any legitimate new evidence.

The proposal of Bankman-Fried, filed in February by his mother on his behalf, cited new evidence to reopen a case in which a 2023 jury convicted him of fraud and conspiracy associated with the decline of FTX. He is convicted with a 25-year prison sentence.

In the February motion, Bankman-Fried claimed that two ex-FTX officials, Daniel Chapsky and Ryan Salame, could have questioned the narrative of the prosecutor that he cheated FTX customers had they borne witness.

The ex-CEOs argued that both rejected testifying because of the fear of retaliation. As per the Wednesday filing, prosecutors declined that argument, mentioning that the witnesses were completely known to the defence before trial; conveying testimony does not qualify as recently discovered evidence.

The Rejection of the Argument

The decision of the defence not to put the witnesses on his witness list or force their testimony precludes any argument that their post-trial views are recently discovered, the prosecutors stated.

The prosecutors also claimed that even if the testimony were looked at, it would not have changed the result of the case, as there was overwhelming evidence showing that Bankman-Fried shifted the transfer of billions of dollars in customer funds to Alameda.

The motion of Bankman-Fried also continued his prolonged argument that FTX was not bankrupt and that customers could eventually be repaid. The prosecutors rejected that argument, mentioning that FTX has a shortage of the cryptocurrency it promised customers, at one point holding around 105 bitcoin against customer claims nearing 100,000 bitcoin.

They also added that the ultimate recovery of assets via bankruptcy proceedings does not justify the underlying crime.

Highlighted Crypto News Today:

Mastercard has Launched Crypto Partner Program, Connecting Industry Leaders

TagsbankruptcyFTXSam Bankman Fried

Related Questions

QWhat was the main reason prosecutors gave for opposing Sam Bankman-Fried's request for a new trial?

AProsecutors argued that Bankman-Fried failed to present any legitimate new evidence that would warrant a new trial.

QWho filed the February motion for a new trial on behalf of Sam Bankman-Fried?

AThe motion was filed by his mother on his behalf.

QWhich two former FTX officials did Bankman-Fried claim could have challenged the prosecution's narrative if they had testified?

ADaniel Chapsky and Ryan Salame.

QAccording to prosecutors, why would the testimony of these witnesses not have changed the case outcome?

ABecause there was overwhelming evidence showing Bankman-Fried transferred billions of dollars in customer funds to Alameda.

QWhat key evidence did prosecutors cite to refute Bankman-Fried's claim that FTX wasn't bankrupt?

AThey noted FTX held only about 105 bitcoin against customer claims of nearly 100,000 bitcoin.

Related Reads

It Took Me a Year to See the Hard Truth About Agent Payments

**Title: It Took Me a Year to See the Hard Truth About Agent Payments** Over the past year, I've worked on infrastructure for the Agent economy, engaging with major players like Stripe, Visa, Coinbase, and numerous startups. The findings reveal a stark reality: genuine, widespread demand for Agent-based payments does not yet exist. **Key Observations:** * **Agent-to-Merchant (Shopping):** The user experience for AI shopping often falls short, especially for visual product discovery. While AI excels at understanding needs, conversational interfaces can't yet replace browsing and comparing multiple products visually. Current merchant interest is largely defensive ("Agent Engine Optimization") for a future that hasn't arrived. High-frequency, low-friction purchases (like food delivery) are potential fits, but lack open APIs and face high AI inference costs. Simpler, more affordable, or cross-language interactions for complex UIs are a niche opportunity but require massive consumer distribution to scale. * **Agent-to-API (Developer Tools):** Developer payment needs for APIs (computing, data, models) are already met through subscriptions and prepaid credits. The core challenge is not payment friction but supplier economics: most large SaaS providers prefer enterprise contracts over micropayments for API calls. Protocols like MPP and x402 suit the long-tail of smaller services but cater to a developer market historically reluctant to pay for these tools. Major infrastructure needs at the top of the stack are already being addressed. * **Agent-to-Agent (Machine Commerce):** This is a long-term vision with almost no current transaction volume. While a future with high-speed, high-frequency, multi-party machine-to-machine transactions would require novel infrastructure, it remains theoretical. The market is not here yet. * **Agent-to-Finance:** This is the only category with clear, present demand. Financial professionals and DeFi users already pay for tools, and AI augmentation is a natural evolution. Autonomous AI agents can enable entirely new financial strategies. However, competition is fierce from established, regulated incumbents who can more easily layer AI onto their existing products. **The Core Insight:** Companies, especially giants with long time horizons, are building defensively for a potential future of mass machine commerce. For them, early investment is a low-cost hedge. For startups, the current market reality is different. The primary challenge isn't just moving money between agents (payments). The larger, unsolved problem is **orchestration** – coordinating work between agents and humans, verifying outcomes, and then settling. Payment is just a part of settlement, which is just a part of orchestration. Companies that solve the orchestration problem will subsume payments, not the other way around. After a year of building, we see the real, growing, and underserved market opportunity lies in this broader domain of orchestration.

链捕手1m ago

It Took Me a Year to See the Hard Truth About Agent Payments

链捕手1m ago

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

A researcher discovered a critical "infinite mint" vulnerability in the Zcash cryptocurrency's Orchard protocol using Claude Opus 4.8, leading to a swift fix but also a 50% market drop, erasing billions in value. This incident highlights a new era where powerful, accessible AI models are dramatically lowering the barrier to finding software vulnerabilities. Previously, the security community feared specialized models like Claude Mythos Preview, capable of finding decades-old zero-day exploits. The Zcash case, however, involved a publicly available, general-purpose model. This shift makes advanced security auditing—and attack capabilities—accessible to far more people, not just experts. The mass democratization of vulnerability discovery brings a dual challenge: a flood of low-quality, AI-generated false reports that overwhelm maintainers, and the real, rapid uncovering of deep, dangerous bugs. Open-source projects, often understaffed and unfunded, are particularly vulnerable to this "attention DDoS." The article cites examples like curl shutting down its bug bounty program due to the unsustainable workload. Our perceived digital safety has often been luck, relying on the high cost and effort required to find deeply hidden flaws in complex systems, as seen with historical vulnerabilities like Heartbleed or Baron Samedit. AI changes this cost structure, effectively "mass-producing flashlights" to illuminate every corner of our codebase. While large companies operate extensive security chains involving external white-hat hackers and massive defensive operations, the global cybersecurity workforce faces a severe shortage, especially of experienced personnel capable of analyzing complex threats and coordinating fixes. The core dilemma emerges: AI makes *finding* bugs cheap and scalable, but *fixing* them remains a slow, expensive, and human-intensive process. The article concludes that AI won't destroy the internet but acts as a bright light, revealing that our digital existence is not inherently secure but is precariously maintained by ongoing human effort. The true cost in the AI era may not be discovery, but whether there will be enough people left willing and able to do the hard work of repair.

marsbit34m ago

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

marsbit34m ago

Ethereum Price Prediction: ETH Could Double While Cardano (ADA) and This Newcomer Token Near 500% Rally

As the cryptocurrency market anticipates a potential bull cycle, investor focus is shifting toward projects with high return potential. Ethereum (ETH), currently at approximately $2,014, is highlighted for its long-term value, with predictions suggesting a possible 2x increase to over $4,000. Cardano (ADA), trading around $0.2329, remains a choice for its research-driven development and scalability focus, though some seek higher upside elsewhere. Significant attention is drawn to Little Pepe (LILPEPE), a new Layer 2 Ethereum-compatible token priced at $0.0022 in its presale stage, which has raised over $28.19 million. The project aims to build a dedicated blockchain for meme communities, offering lower costs and faster transactions. Backers speculate a potential 500% gain, driven by strong presale demand, planned ecosystem features like staking and a launchpad, and active community engagement through giveaways. While Ethereum and Cardano are viewed as foundational investments, LILPEPE represents a newer, high-growth opportunity for investors targeting the meme coin sector.

TheNewsCrypto55m ago

Ethereum Price Prediction: ETH Could Double While Cardano (ADA) and This Newcomer Token Near 500% Rally

TheNewsCrypto55m ago

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

"Codex Goal Mode: How to Make AI Work Continuously Toward a Specific Goal" OpenAI's Codex "goal mode" (/goal) transforms the AI from a reactive code assistant into a proactive execution agent capable of working autonomously for hours or even days to achieve a defined objective. To maximize its effectiveness, follow these key principles: 1. **Define Clear, Verifiable Exit Criteria:** The goal prompt should be a concise, measurable success condition, not a lengthy specification. Use quantifiable metrics like "reduce build time by 30%" or "achieve 100% test parity." 2. **Provide Initial Guidance and Tools:** Direct Codex toward likely problem areas and specify available tools (e.g., browsers, testing environments) to prevent it from exploring unproductive paths. 3. **Enable Progress Measurement:** Equip Codex with ways to track advancement, such as creating comparison tools for visual tasks or evaluation sets, ensuring it can gauge its own progress. 4. **Use a Realistic Execution Environment:** For tasks like performance optimization, provide access to environments that closely mimic production (e.g., similar configs, databases) to yield valid results. 5. **Be Cautious with Visual Goals:** Avoid vague "pixel-perfect" instructions. Instead, supplement visual references with functional checklists or design system specifications to prevent Codex from obsessing over minor details. 6. **Implement Progress Tracking:** For long-running tasks, have Codex commit code to draft PRs, update progress documents, or send Slack updates to maintain visibility into its work. 7. **Review and Consolidate Results:** Once the goal is met, instruct Codex to review its work, clean up ineffective experimental code, and reflect on what strategies succeeded or failed. Ultimately, using goal mode shifts the developer's role from writing prompts to managing a persistent engineering agent—defining objectives, establishing metrics, configuring environments, and conducting final reviews.

marsbit1h ago

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

marsbit1h ago

From Ethereum to AI's 'CROPS': What Exactly Is This 'Slow Variable' That Vitalik Has Repeatedly Emphasized?

Recently, Vitalik Buterin has frequently emphasized the concept of "CROPS," first outlined in the Ethereum Foundation's March mandate as core principles guiding its focus: Censorship Resistance, Capture Resistance, Open Source, Privacy, and Security. CROPS represents Ethereum's commitment to providing foundational capabilities for user sovereignty—enabling asset ownership, identity expression, and coordination without reliance on centralized platforms or surrendering ultimate control. This framework is gaining new urgency with the rise of AI, particularly AI agents managing digital assets and automating transactions. While AI offers convenience, it risks centralizing user data, intent, and control if dependent on opaque, centralized services. Vitalik argues for "CROPS AI"—AI that is open, privacy-preserving, secure, and capable of local execution to maintain user agency. He highlights convergence between "CROPS Ethereum access layers" and "CROPS AI," such as using zero-knowledge proofs for private remote LLM calls and Ethereum RPC reads, ensuring users can access services without exposing sensitive information. Ultimately, CROPS is not just an abstract ideal but a practical guide for Ethereum's development and AI integration. It addresses the critical long-term question: as digital systems grow more powerful, how can users retain control over their privacy, assets, and autonomy? In an AI-driven era, these principles may define Ethereum's enduring value—prioritizing verifiable, secure, and user-centric design over short-term optimizations like speed and cost alone.

marsbit1h ago

From Ethereum to AI's 'CROPS': What Exactly Is This 'Slow Variable' That Vitalik Has Repeatedly Emphasized?

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

Top Questions

Hot Categoriesright-arrow

Hot Tagsright-arrow