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BTC Miner Inflows to Binance Hit Lowest Levels Since June 2023 Amid Reduced Selling Pressure

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Brian Armstrong's Bold Prediction: AI Agents Will Soon Dominate Global Financial

TLDR:

  • BTC miner inflows to Binance have dropped to their lowest monthly average since June 5, 2023.
  • The U.S. ice storm forced miners to sell BTC to cover fixed costs despite reduced operations.
    Combined miner inflows across all exchanges currently stand at approximately 4,381 BTC monthly.
  • Miners are estimated to hold 1.8 million BTC in reserve, making their behavior critical to watch.

BTC miner inflows to Binance have dropped to historically low levels in recent weeks. This follows a sharp spike recorded during the ice storm that struck the United States in late January and early February.

The monthly average now stands at approximately 4,316 BTC. Across all exchanges, the combined figure reaches 4,381 BTC. Analysts view this shift as a reduction in structural selling pressure from the mining cohort.

Ice Storm Forces U.S. Mining Pools to Liquidate BTC Holdings

Several large U.S.-based mining pools slowed down or halted operations during the storm. The extreme weather disrupted normal mining activity across affected regions.

However, fixed costs such as electricity, infrastructure, and operational expenses remained constant. This financial pressure pushed some miners to sell BTC in order to maintain liquidity.

On-chain analyst Darkfost noted the sharp rise in miner inflows during that period. The data showed a clear correlation between the weather event and increased BTC distribution to exchanges.

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Miners facing reduced output still needed to cover ongoing operational costs. Selling into the market became the most practical solution for many affected operations.

The spike in inflows was a temporary reaction to an external shock. Once weather conditions normalized, mining activity gradually resumed across the United States.

With operations back online, the need to liquidate BTC eased considerably. The data confirms the increase was event-driven rather than structural.

This pattern is not uncommon when miners face unexpected downtime. External disruptions can quickly shift miner behavior from accumulation toward distribution.

When income drops but costs remain fixed, selling becomes the most immediate option available. The ice storm served as a clear example of how operational risk translates directly into market activity.

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Miner Reserves and Reduced Selling Pressure Point to Market Stability

Since the storm subsided, BTC miner inflows have reversed sharply to the downside. The current monthly average of 4,316 BTC marks the lowest reading since June 5, 2023.

This decline points to miners retaining more BTC rather than routing it toward exchanges. Lower exchange inflows typically reflect reduced selling intent from this cohort.

According to Darkfost’s analysis, miners currently hold an estimated 1.8 million BTC in reserves. This represents a large supply pool that could enter the market under shifting conditions.

Any move to increase distribution from these reserves could generate considerable selling pressure. Monitoring miner behavior therefore remains a critical component of broader market analysis.

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At present, the data suggests miners are in a conservative distribution phase. The reduction in exchange inflows across both Binance and the wider market supports this reading.

Miner-driven selling pressure appears relatively contained at this stage. This backdrop can support near-term price stability for BTC.

The trend requires continued monitoring as market conditions evolve. If BTC prices decline sharply, miners may resume higher distribution to manage cash flow.

Conversely, rising prices could encourage further holding. Miner inflow data remains one of the more reliable on-chain indicators for gauging supply-side pressure.

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Crypto World

AI Routers Can Steal Credentials and Crypto

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AI Routers Can Steal Credentials and Crypto

University of California researchers have discovered that some third-party AI large language model (LLM) routers can pose security vulnerabilities that can lead to crypto theft. 

A paper measuring malicious intermediary attacks on the LLM supply chain, published on Thursday by the researchers, revealed four attack vectors, including malicious code injection and extraction of credentials

“26 LLM routers are secretly injecting malicious tool calls and stealing creds,” said the paper’s co-author, Chaofan Shou, on X.

LLM agents increasingly route requests through third-party API intermediaries or routers that aggregate access to providers like OpenAI, Anthropic and Google. However, these routers terminate Internet TLS (Transport Layer Security) connections and have full plaintext access to every message. 

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This means that developers using AI coding agents such as Claude Code to work on smart contracts or wallets could be passing private keys, seed phrases and sensitive data through router infrastructure that has not been screened or secured.

Multi-hop LLM router supply chain. Source: arXiv.org

ETH stolen from a decoy crypto wallet 

The researchers tested 28 paid routers and 400 free routers collected from public communities. 

Their findings were startling, with nine routers actively injecting malicious code, two deploying adaptive evasion triggers, 17 accessing researcher-owned Amazon Web Services credentials, and one draining Ether (ETH) from a researcher-owned private key.

Related: Anthropic limits access to AI model over cyberattack concerns

The researchers prefunded Ethereum wallet “decoy keys” with nominal balances and reported that the value lost in the experiment was below $50, but no further details such as the transaction hash were provided. 

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The authors also ran two “poisoning studies” showing that even benign routers become dangerous once they reuse leaked credentials through weak relays.

Hard to tell whether routers are malicious

The researchers said it was not easy to detect when a router was malicious.  

“The boundary between ‘credential handling’ and ‘credential theft’ is invisible to the client because routers already read secrets in plaintext as part of normal forwarding.” 

Another unsettling find was what the researchers called “YOLO mode.” This is a setting in many AI agent frameworks where the agent executes commands automatically without asking the user to confirm each one.

Previously legitimate routers can be silently weaponized without the operator even knowing, while free routers may be stealing credentials while offering cheap API access as the lure, the researchers found.

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“LLM API routers sit on a critical trust boundary that the ecosystem currently treats as transparent transport.” 

The researchers recommended that developers using AI agents to code should bolster client-side defenses, suggesting never letting private keys or seed phrases transit an AI agent session.

The long-term fix is for AI companies to cryptographically sign their responses so the instructions an agent executes can be mathematically verified as coming from the actual model. 

Magazine: Nobody knows if quantum secure cryptography will even work