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  1. Cato AI LabsFirst-partyResearch
    AI score73

    Cato AI Labs discloses two zero-click prompt injection RCE vulnerabilities in Cursor IDE

    Cato AI Labs discovered two remote code execution vulnerabilities in Cursor IDE that can lead to sandbox escape, both with a CVSS score of 9.8, tracked as CVE-2026-50548 and CVE-2026-50549. The two vulnerabilities stem respectively from the working_directory parameter of run_terminal_cmd being blindly added to the sandbox writable list, and from the fallback logic when symlink canonicalization fails; attackers can overwrite the cursorsandbox binary through zero-click prompt injection in an MCP server or web search results, achieving non-sandboxed RCE. The Cursor team fixed both issues in Cursor 3.0, released on April 2.

    #Safety / alignment#Agents#English text is being prepared.

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  2. Anthropic：The InstituteFirst-partyResearch
    AI score57

    Anthropic Releases Sixth Economic Index Report: Analysis of Claude Usage Rhythms and Artifacts

    Anthropic released its Economic Index report, switching to privacy-preserving telemetry data sampled continuously each day, making hourly usage patterns observable. The report shows that the share of personal-use conversations rose from about 35% on weekdays to nearly 50% on weekends, recipe requests peaked at 2.3 times at 6 p.m., and tax-related conversations on April 14 were 8 times those of an average day in May. The report also classifies conversations by artifact; artifacts were identified in 93% of conversations, of which explanations accounted for 17% and documents and reports for 15%.

    #English text is being prepared.#English text is being prepared.#Anthropic

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  2. Anthropic：The InstituteFirst-partyResearch
    AI score68

    Anthropic Project Fetch Phase 2: Opus 4.7 Operates Robot Dog Independently, Faster Than Human Teams

    Anthropic published the Phase 2 experiment of Project Fetch: Claude Opus 4.7, running Claude Code without human assistance, completed the tasks that human teams did last year about 20 times faster than the fastest human team. On every task completed by at least one human team, Opus 4.7 was at least 10 times faster; on tasks completed by all four human teams, it was on average more than 37 times faster than teams without Claude and more than 18 times faster than teams with Claude, while generating nearly ten times less code than Team Claude. The model still fails at the closed-loop control step of precisely pushing the beach ball; Anthropic says this is not a solved robotics problem, and that the improvement comes from general capability scaling rather than robot-specific training.

    Bar chart labeled "Total time comparison: 4 tasks completed by all teams." The chart shows that Team Claude-less completed tasks in 361 minutes; Team Claude completed tasks in 181 minutes, and Claude Opus 4.7 alone completed tasks in 9 minutes 35 seconds. Opus 4.7 was 37.7 times faster than Team Claude-less and 18.9 times faster than Team Claude.

    #Papers/Research#Agents#Embodied AI

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