Security/Hacker

NEAR Governance Forum Proposes Reducing Token Issuance Rate from 2.5% to 1.6% Over 24 Months

Odaily News: A new proposal has been submitted on the NEAR governance forum by Sal Ternullo, CEO of Svrn AI, recommending that the NEAR token issuance rate be reduced from 2.5% to 1.6% over 24 months, with a long-term push toward a fixed total supply. The proposal is currently open for discussion among validators, House of Stake representatives, and the broader NEAR community.The NEAR team stated that the NEAR Intents incident did not involve any vulnerability in NEAR Protocol or the native NEAR token. The network continued producing blocks and processing transactions without downtime during the period.

NEAR Community Proposal Proposes Reducing Maximum Annual Token Issuance Rate, Clarifies Security Incident Does Not Involve Native Token Vulnerabilities

NEAR Protocol announced on the X platform that Sal Ternullo, CEO of NEAR Treasury Company SVRN, has introduced a new proposal on the NEAR Governance Forum to reduce NEAR's annual maximum token issuance rate from 2.5% to 1.6% over a 24-month period, and lower the staking yield from the current approximately 5.4% to around 3.5%. The proposal is currently soliciting feedback from validators, House of Stake delegates, and NEAR community members, with a complete plan expected to be published next week for voting. Following the earlier NEAR Intents security incident, NEAR Protocol further clarified that the blockchain network is operating normally. The incident was not caused by any vulnerabilities in NEAR Protocol or its native NEAR token. The NEAR Protocol network continues to produce blocks and process transactions without experiencing downtime.

Zhou Hongyi urges the cybersecurity industry to rapidly establish a framework for AI vulnerability discovery, automated defense, and agent security.

According to a report by the Securities Times, at the 4th Cyberspace Security (Tianjin) Forum, Zhou Hongyi, founder of the 360 Group, delivered a keynote presentation, stating that AI has reshaped the cyber attack and defense landscape, rendering traditional solutions unsustainable. It is essential to build a new automated cyber defense and offense system centered on "governing models with models," leveraging AI capabilities to mitigate AI risks, ensure the inherent security of large models, the reliability of generated content, and the trustworthiness of output results; and to implement full lifecycle management of AI agents, establishing control mechanisms that are auditable, subject to intervention, and capable of being blocked.