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最新模型

Photon-1 Learns to Operate Computers from Unlabeled Screen Videos, Replacing Action Labels with Latent-State Prediction

Induction Labs has introduced Photon-1, a 106B-A5B sparse MoE model that learns during pretraining solely by watching screen videos, without requiring mouse or keyboard action labels. The model first predicts the next latent screen state, then generates the actions needed to reach it, though current evidence of its performance comes primarily from the team’s internal evaluations.
代理工具

Cursor Router Assigns Coding Models Per Request, While Cost Mode Requires Retaining Grok 4.5 as a Routing Option

Cursor has transformed Auto mode into a Router that classifies each request and selects a model, allowing enterprises to switch among Intelligence, Balance, and Cost strategies. The company claims online testing shows savings of 60%, but hidden-by-default model selections and mandatory routing options for certain modes make auditability a key deployment concern.
AI 安全

NanoClaw MCP Approval Cards Hid Execution Parameters, Allowing Agents to Turn One-Time Consent into Persistent Execution Settings

The newly registered CVE-2026-17434 identifies an authorization gap in NanoClaw versions before 2.0.64: the MCP server approval card shown to administrators did not fully display the parameters and environment variables that would actually be applied. The fix now presents the complete payload, masks secret values, and limits input sizes, but affected deployments must still verify their versions and existing configurations.
AI 安全

SiYuan MCP Endpoint Lacked Role Checks; Version 3.7.2 Fixes Flaw Allowing Low-Privilege Users to Invoke Core Tools

The newly disclosed CVE-2026-66012 shows that, before SiYuan 3.7.2, the `POST /mcp` endpoint checked only general authentication status, without enforcing an administrator role or read-only restrictions. Because MCP can expose core note-management capabilities to AI clients, accounts intended only to read content could potentially use it to perform state-changing operations.
最新模型

UK–US Joint Evaluation: Kimi K3 Completes a Simulated Enterprise Intrusion, but None of 41 Exploit Attempts Achieves Arbitrary Code Execution

Preliminary testing by the UK AISI and the US CAISI shows that Kimi K3 scored 32% on ExploitBench, outperforming GLM-5.2 but trailing the tested US frontier models by a wide margin. The model also completed a 32-step simulated enterprise attack once, but the limited evaluation conditions and sample size do not support direct conclusions about real-world attack success rates.
AI 安全

AgentForger Uses URL Parameters to Forge ChatGPT Workspace Agents and Inherit Users’ Existing Connector Permissions

Zenity has disclosed a patched CSRF-style attack chain: merely opening a crafted link while logged in could cause ChatGPT Agent Builder to automatically create, schedule, and run an attacker-controlled agent. The vulnerability did not bypass OAuth; instead, it inherited existing authorizations, highlighting a new trust gap among agent creation workflows, execution identities, and tool permissions.
代理工具

DNS-AID Builds an Agent Discovery Layer with SVCB and DNSSEC, Freeing MCP and A2A Endpoints from Centralized Directories

DNS-AID has launched a public website and an Apache 2.0-licensed reference implementation that let organizations publish agent endpoints, protocols, and capability documents as existing DNS records. The approach can use DNSSEC to authenticate the publisher’s domain, but it still cannot prove that an agent itself is secure, that its capability claims are accurate, or that it should be authorized.
AI evaluation

EvolvingIntent Turns Static Benchmarks Into Conversations With Changing Requirements, Exposing Gaps in Agents’ Ability to Track Revised Instructions

Microsoft Research introduced EvolvingIntent, which transforms existing math, SQL, search, and programming tasks into multi-turn conversations in which requirements are progressively disclosed, revised, or redirected. Experiments show that models’ performance on single-turn benchmarks does not transfer reliably to scenarios where requirements continually change. The data-construction and evaluation code has been released publicly.