A crypto whale liquidated their entire CRV position after holding it for 3 years, incurring a loss of $4.1 million.

According to SlowMist, North Korea-linked threat actor TraderTraitor (also known as UNC4899 and Jade Sleet) has launched a new attack, recently infiltrating an Indian IT services firm with no ties to the crypto industry. The attacker posted fake job listings on GitHub, using "technical interview assignments" as bait to phish DevOps and crypto engineers. After victims download the project, a malicious .terraform.lock.hcl file points to a Terraform Provider domain controlled by the attacker. Running `terraform init` triggers the download and execution of the malicious Provider module. The attack deploys Rust/ARM64 backdoors FLATROOF and ROOFDECK on victims’ macOS devices; these two malware families were previously used in LayerZero attacks. They can steal credentials and sensitive data, execute shell commands, collect and exfiltrate files, and gain access to cloud services and code repositories. SlowMist warns that TraderTraitor’s latest targets are no longer limited to the crypto sector—the attacker may now be focusing on developers’ access to cloud and API services including AWS, GCP, OVH, and OpenStack. Enterprises should exercise caution when handling unfamiliar Terraform Providers and code repositories from recruiters, and avoid using personal or work devices to run unvetted interview projects.

Beating AI Express (Insight): Luo Fuli, head of Xiaomi’s MiMo project, further explained the current round of reinforcement learning after the release of MiMo-V2.6. She noted that she previously worked on DeepSeek R1, and in her view, the research innovations and engineering challenges behind MiMo-V2.6 exceed those of R1. She also clarified why MiMo uses both MixRL and MOPD: MixRL trains verifiable tasks such as code, general agents, vision, and cybersecurity all within a single round of reinforcement learning. MOPD, meanwhile, handles long, hard-to-verify, or subjectively rewarded tasks by training them separately first, then integrating their capabilities back into the main model. Tasks like games and 3D take too long to run at once and are difficult to auto-assess for correctness. If grouped with code and other tasks in the same RL round, they would significantly slow down training. As a result, MiMo trains these tasks separately and integrates their capabilities into the main model via MOPD.

Uniswap team member niko published a post stating that after Robinhood Chain’s recent large-scale innovation boosted market performance, other blockchains started replicating its ecosystem projects. Meanwhile, some KOLs and venture capital institutions have repeatedly claimed Robinhood Chain is declining, directing users to similar projects on other chains. Niko pointed out that contrary to these claims, Robinhood Chain’s daily trading volume still exceeds $1 billion, and its stock token trading scale is growing rapidly. He believes the bearish narrative surrounding Robinhood Chain’s ecosystem is clearly at odds with actual on-chain data.

Insight Beating AI News Flash: An exclusive report from *Investment Journal* reveals that Yan Wentao officially joined DeepSeek on Monday and reported for duty, becoming the firm’s first Chief Financial Officer (CFO). Born in 1991, Yan graduated from Fudan University and joined Hillhouse Venture Capital in 2020. He has previously been involved in projects including MiniMax, Zhipu AI, and ByteDance. His appointment comes as DeepSeek intensively advances capital operations: the company is finalizing its Series B financing, planning to raise 50 billion yuan at a pre-money valuation of 500 billion yuan. Meanwhile, DeepSeek has hired CITIC Securities to prepare for a potential IPO on the STAR Market.

According to on-chain data, Hyperliquid burned 42,300 HYPE tokens over the past 24 hours, valued at roughly $4 million, marking an over 88% month-over-month rise. In the past seven days, the platform burned 226,500 HYPE tokens, pushing its cumulative total burn to 47,397,098 HYPE, which accounts for 4.74% of the token’s total supply.

Beating AI News Flash: Meta’s personal AI agent Muse, launched just two weeks ago, has been discovered with a local zero-day vulnerability by security researcher Patrick Wardle. Attackers only need to run a piece of code on a Mac under the current user’s identity to modify a hidden Muse setting, redirecting voice requests to their own server. This code does not require extra macOS permissions. Post-exploitation, attackers can intercept users’ voice inputs to Muse, inject malicious commands, and potentially obtain Muse’s authentication credentials. Muse itself has access to system resources such as files and cameras; whatever permissions users grant Muse, malicious programs could leverage Muse to abuse those access rights. Notably, this is not a vulnerability enabling remote Mac intrusion—attackers must first execute the code locally on the device. When Meta launched Muse, it highlighted its security design, which includes the Muse Secure VM and an independent Sentinel Agent. The first zero-day vulnerability, however, was found in a hidden setting on the Mac client that can be modified by a regular local process.