The Bittensor blockchain, which focuses on decentralized artificial intelligence (AI) technology, was abruptly shut down by its developers following a security breach. This precaution was taken after suspicious activities targeting user wallets were detected.
This incident highlights the vulnerabilities inherent in blockchain and cryptocurrency platforms. It also sheds light on the urgent need for stringent security measures.
Bittensor Blockchain Operates in a “Safe Mode”
Earlier today, anomalous transactions led the core development team to halt all network operations. According to the blockchain’s block explorer, Bittensor has not produced new blocks for about six hours. This suspension of activity has notably shaken market confidence, resulting in the token’s sharp price decline.
The value of the TAO token is down by over 17%. It is currently trading around $227.73.
“By way of an update, we have contained the attack and put the chain into safe mode (blocks producing but no transactions are permitted). We’re still mid investigation and are considering all possibilities,” Ala Shaabana, the co-founder of Bittensor, said.
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The blockchain will operate in a safe mode for the next 24 hours, as confirmed by Watchmaker, a moderator on Bittensor’s Discord.
“As we are prioritizing this issue for the rest of this week, we will not be releasing any regular software updates for either Bittensor software or for any chain updates on either mainnet or testnet until we have brought the chain fully back online,” Watchmaker elaborated.
ZachXBT, an on-chain investigator, reported that a theft address now holds over 32,000 TAO tokens, valued at approximately $8 million. Although Bittensor has not officially commented on the hack’s financial impact, the community remains alert and cautious.
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The significant drop in TAO token value has raised concerns among investors and participants who depend on the Bittensor platform for developing, training, and exchanging AI models. Utilizing blockchain technology, Bittensor facilitates a collaborative environment where users contribute computational resources and data crucial for the network’s AI training processes.
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