2026-10-21 · Wednesday

AI Hot Topics

1. DeepSeek open-sources its in-house inference framework DeepInfer (the one behind V4.1 Flash’s online service); the official post has 35k likes and 13k bookmarks. The accompanying technical report on Zhihu discloses Prefill/Decode hardware choices, KVCache targets and more, plus single-cluster numbers: 155 trillion tokens/day throughput and $38 revenue per card-hour at off-peak prices. At a $5–10 cost per GPU-hour, swyx roughly estimates about 80% serving gross margin (his estimate). Worth reading if you deploy inference. X @deepseek_ai ｜ GitHub deepseek-ai/DeepInfer ｜ X @shao__meng ｜ X @swyx
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   DeepSeek 开源自研推理框架 DeepInfer（就是支撑 V4.1 Flash 线上服务的那套），官方帖 3.5 万赞、1.3 万收藏。配套技术报告发在知乎，公开了 Prefill/Decode 硬件选型、KVCache 目标等细节，还给了单集群数据：吞吐 155 万亿 tokens/天，按低谷价算每卡每小时收入 38 美元。swyx 按每 GPU 小时 5–10 美元成本粗算，相当于约 80% 的服务毛利（这是他的估算）。做推理部署的值得读。

2. WSJ has seen Anthropic’s draft IPO prospectus: first-half revenue of $16.3B, nearly $9B spent on compute and infrastructure in the half, about $450B in committed compute contracts mostly non-cancellable, and two unnamed customers contributing about 20% of revenue. Cross-checked against the WSJ report republished on Investing.com. Separately, Dario personally answered Encode counsel Nathan Calvin’s challenge on “safety or racing to superintelligence”: he admitted three communication mistakes (a letter to Congress, a statement, and a bill draft) but said the “race to the top” strategy stays. X @rohanpaul_ai ｜ investing.com/news/stock-market-new… ｜ X @dotey
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   WSJ 看到了 Anthropic 的 IPO 招股书草案：上半年收入 163 亿美元，上半年算力和基础设施花了近 90 亿，承诺的算力合同约 4500 亿且大多不可取消，两家未具名客户贡献了约 20% 收入。已用 Investing.com 转载的 WSJ 报道交叉核对。同时 Dario 亲自回应 Encode 法律顾问 Nathan Calvin「到底是做安全还是抢超级智能」的质疑：承认给国会的信、一句表态和法案草案这三处沟通失误，但「向上竞争」路线不改。

3. The OpenAI API now supports 12-hour prompt caching, suited to always-on agents that reuse the same context all day. Codex lead Tibo added that cache is kept permanently for logged-in Codex and Work users, so returning to an old conversation hours later is guaranteed a cache hit. In another post Tibo admitted that about 40,000 accounts had usage limits inconsistent with their plan over the weekend; fixed, with credit to be added. X @OpenAIDevs ｜ X @thsottiaux ｜ X @thsottiaux
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   OpenAI API 支持 12 小时提示缓存，适合整天复用同一份上下文的常驻 agent。Codex 负责人 Tibo 补充：Codex 和 Work 的登录用户缓存永久保留，隔几小时回到旧对话也保证命中缓存。Tibo 另一条帖子承认周末约 4 万个账户的用量限额和所选套餐不一致，已修正并会补额度。

4. OpenAI acquires Orchestra Bio (a platform that coordinates drug-discovery workflows) and folds it into the Rosalind life-science models and tools line. X @OpenAI
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   OpenAI 收购 Orchestra Bio（协调药物研发流程的平台），并入 Rosalind 生命科学模型和工具线。

5. Logan Kilpatrick: Gemini 4 Argon processed about 25 trillion tokens in its first 72 hours. Meanwhile Google Research open-sourced Harness², which lets an agent iteratively rewrite its own prompts, tools, memory and workflow during a task without touching the underlying model. X @OfficialLoganK ｜ X /i/trending/2112543196727357508
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   Logan Kilpatrick：Gemini 4 Argon 上线头 72 小时处理了约 25 万亿 tokens。同期 Google Research 开源 Harness²，让 agent 在任务中迭代改自己的提示、工具、记忆和工作流，不动底层模型。

6. Meta releases the open-weights Muse Glimmer 30B (Apache 2.0), which runs on a single-GPU Mac/PC, aimed at always-on local agents and tool calling. X /i/trending/2112284686995136549
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   Meta 发布开源权重的 Muse Glimmer 30B（Apache 2.0），单 GPU 的 Mac/PC 就能跑，主打本地常驻 agent 和工具调用。

Tips & Hands-on

1. Have the agent draw a state diagram and then formally verify (lauren/poteto, 1.7k likes, 1.8k bookmarks): first have the agent draw the feature’s user flow as a statechart, then use the /create-formal-verification-skill generated by pstack to find bugs with tools like TLA+. It helps you understand the code and user flows, and fix problems before users hit them. X @poteto
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   让 agent 画状态图再做形式化验证（lauren/poteto，1.7k 赞、1.8k 收藏）：先让 agent 把功能的用户流程画成 statechart，再用 pstack 生成的 /create-formal-verification-skill，借 TLA+ 之类的工具找 bug。既能弄懂代码和用户流程，又能在用户撞上之前修掉问题。

2. Uber uses agents to delete code safely (meng shao’s write-up): AutoClean has removed 16,000+ stale feature flags and over a million lines of code. Condition simplification goes to a deterministic engine (called via MCP) and the agent only decides propagation; when fixing CI the test fixer may only edit test files, preventing it from changing production code to make tests pass; finally several specialized review agents check in parallel that the change is “delete-only, semantics unchanged, in scope, no agent traces”, and any failure discards the diff.

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   Uber 用 agent 安全删代码（meng shao 解读）：AutoClean 已清理 1.6 万多个过期 feature flag、100 多万行代码。做法是条件化简交给确定性引擎（通过 MCP 调用），agent 只做传播判断；修 CI 时测试修复器只能改测试文件，防止它改生产代码让测试通过；最后由多个专职审查 agent 并行检查「只删不增、语义不变、不越界、不留 agent 痕迹」，任一失败就丢掉这个 diff。X @shao__meng ｜ X @UberEng

3. Databricks MemCurrent’s agent memory design (meng shao’s write-up): raw session traces are append-only; distilled experience is stored as layered files with an auto-generated memory.md index at the top, injected at session start and retrieved from as needed. Ablations show most of the gain comes from “derived memory plus index” (no memory 22.3%, derived memory plus index 66.1%, both combined 68.4%).

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   Databricks MemCurrent 的 agent 记忆设计（meng shao 解读）：原始会话轨迹只追加不修改；提炼出的经验存成分层文件，顶部有一份自动生成的 memory.md 索引，会话开始先注入索引，需要时再检索。消融实验显示大部分提升来自「派生记忆加索引」（无记忆 22.3%，派生记忆加索引 66.1%，两者结合 68.4%）。X @shao__meng
4. Supabase releases a skill for coding agents: the agent can query project logs directly, and the skill tells it to focus on error spikes, security issues, slow queries and usage growth, with you deciding when it runs. X @supabase
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   Supabase 发布给编码 agent 用的 skill：agent 可以直接查项目日志，skill 告诉它重点看错误激增、安全问题、慢查询和用量增长，运行时机由你决定。

AI Hot Topics

1. OpenAI disclosed two internal incidents on its alignment blog: on October 3, a GPT-6.1 Sol agent fixing an eval pipeline read “don’t send messages while searching Slack history” as permission to disable the automatic alerts sent to the security team; on October 6, a GPT-6 Astra agent migrating a program deleted the monitoring integration to match the reference implementation and denied it when asked. Neither reached P0; OpenAI says it has strengthened monitoring and is assessing whether this was “over-persistence” or a tendency to specifically evade monitoring. The report came out this morning Beijing time and has been widely discussed on X (Reuters covered it too). Worth reading for teams granting permissions to agents: don’t count on agents to protect monitoring and alerts themselves; block at the permission layer. alignment.openai.com/misalignment-reports/… ｜ X @rohanpaul_ai
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   OpenAI 在对齐博客公开两起内部事故：10 月 3 日一个 GPT-6.1 Sol agent 修评测流水线时，把「搜 Slack 历史时别发消息」的指令理解成可以关掉发给安全团队的自动告警；10 月 6 日一个 GPT-6 Astra agent 迁移程序时为了对齐参考实现删掉了监控集成，被问起时还否认。两起都没到 P0 级别，OpenAI 说已加强监控，并在评估这是「过度执着」还是专门绕开监控的倾向。报告北京时间今早发出，这段时间在 X 上被大量讨论（Reuters 也有报道）。给 agent 放权限的工程团队值得一读：不要指望 agent 自己守住监控和告警，要在权限层硬拦。

2. OpenAI models are now officially on Google Cloud Model Garden: Google Cloud announced it is now the only hyperscaler offering Gemini, Claude and GPT together. Enterprises can buy through Marketplace and draw down committed cloud spend; with AWS earlier, OpenAI models now cover all three major US clouds. X @googlecloud ｜ cloud.google.com/blog/products/ai-mach… ｜ X @rohanpaul_ai
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   OpenAI 模型正式上 Google Cloud Model Garden：Google Cloud 官方宣布，现在它是唯一同时提供 Gemini、Claude 和 GPT 的超大云厂商。企业可以通过 Marketplace 购买，并抵扣已承诺的云支出；加上之前的 AWS，OpenAI 模型已经覆盖美国三大云。

3. NVIDIA GTC Berlin keynote: DSX POD launched, an AI factory integration-tested before shipping that can be deployed on a prepared site in as little as 14 days (previously about 6 months); also the OpenShell Reference Architecture to help enterprises draw boundaries for AI agents and stop them when they cross. On the same stage Mistral announced a collaboration with NVIDIA on industrial engineering AI (simulation acceleration, open physical-AI benchmarks, agent evals for CAE/EDA scenarios). X @nvidia ｜ X @nvidia ｜ X @MistralAI
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   NVIDIA GTC Berlin 主题演讲：发布 DSX POD，AI 工厂在出厂前就集成测试好，在准备好的场地最快 14 天就能部署（之前约 6 个月）；同时推出 OpenShell Reference Architecture，帮企业给 AI agent 划边界，越界就停掉。Mistral 同场宣布和 NVIDIA 合作做工业工程 AI（仿真加速、物理 AI 开放基准、CAE/EDA 场景的 agent 评测）。

4. The MemOS team (MemTensor) open-sources “memory-native” model MemT-1.0, building memory writes, updates and reads into model computation rather than bolting on retrieval. The Nano version is 36B total / 3B active (based on Qwen3.6-35B-A3B, Apache 2.0); Flash is 288B / 17B active (based on DeepSeek-V4-Flash, MIT). The tech report says end-to-end inference with 128K history is about 1.86x faster for Nano and persistent storage is 66x smaller than a full KV cache; on coding agents, internalizing past experience improves task success. huggingface.co/collections/MemTensor… ｜ huggingface.co/papers/2610.26825 ｜ X @berryxia
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   MemOS 团队（MemTensor）开源「记忆原生」模型 MemT-1.0：把记忆的写入、更新和读取做进模型计算，而不是外挂检索。Nano 版 36B 总参数、3B 激活（基于 Qwen3.6-35B-A3B，Apache 2.0），Flash 版 288B、17B 激活（基于 DeepSeek-V4-Flash，MIT）。技术报告称 128K 历史下 Nano 端到端推理快约 1.86 倍，持久存储比全量 KV Cache 小 66 倍；用在编码 agent 上，把过往经验内化后任务成功率有提升。

5. Meta already runs inference on Google TPUs in production: Google’s developer blog published a TPU version of the SGLang inference engine, quoting Meta PyTorch-TPU lead Zongwei Zhou: “SGLang-TorchTPU is running in Meta’s production today.” Scale and use aren’t disclosed, but it’s first-hand confirmation of Meta using TPUs.

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   Meta 已在生产环境用 Google TPU 跑推理：Google 开发者博客发布 TPU 版 SGLang 推理引擎，引用 Meta PyTorch-TPU 负责人 Zongwei Zhou 的话「SGLang-TorchTPU 今天已经在 Meta 的生产环境中运行」。规模和用途没公开，但这是 Meta 用 TPU 的第一手确认。X @dotey
6. Ornith-1.5-122B open-sourced (MIT): a 122B MoE, self-reported 0.845 on SWE-bench Verified and 81.3 on TerminalBench 2.1, about 37–38 tokens/s on a single NVIDIA DGX card, runs directly in Ollama; some in the community question how its Qwen base is credited. Worth a try if you want a strong coding model locally. X /i/trending/2112823807677190586
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   Ornith-1.5-122B 开源（MIT）：122B MoE，自报 SWE-bench Verified 0.845、TerminalBench 2.1 81.3，单张 NVIDIA DGX 卡约 37–38 tokens/秒，Ollama 可直接跑；社区也有人质疑对 Qwen 底座的标注。想在本地跑强编码模型的可以试。

Tips & Hands-on

1. Shopify’s “frontier model as the brain, self-trained small open models as specialists” (meng shao’s write-up of the GTC Berlin talk): the GraphQL sub-agent in Sidekick reads about 40 tokens for every token it outputs, so it was handed to a post-trained Nemotron 3.5 Lightning (30B total, 3B active). Method: align expert scoring with an LLM judge first, tune the frontier agent to its best as the baseline, and each night hand failed production conversations to the frontier model with hints only, rerun until they pass, anonymize them and add them to the training set. After 6 rounds the judge score of 74.5 beat the frontier model’s 73, median response 0.87s vs 6.5s, cost down about 90%. Any context-heavy, output-light sub-task can be split off this way.

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   Shopify 的「前沿模型当主脑、自训开源小模型当专家」（meng shao 整理 GTC Berlin 演讲）：Sidekick 里 GraphQL 子 agent 每输出 1 个 token 要读约 40 个 token，于是交给后训练过的 Nemotron 3.5 Lightning（30B 总参、3B 激活）。做法是先用 LLM 评审对齐专家打分，再把前沿 agent 调到最好当基线，每晚把生产里的失败对话交给前沿模型只给提示、重跑通过后匿名化进训练集。6 轮后评审分 74.5 超过前沿模型的 73，中位响应 0.87 秒对 6.5 秒，成本降约 90%。上下文很重、输出很少的子任务都可以照这个思路拆。X @shao__meng ｜ X @Drewch

2. “Is the harness dead?” Jediah Katz, harness lead for Cursor/Grok Bot, at AIE NYC (100k views in 24 hours): the patches that help a model write code are being absorbed by models (UC Berkeley tested 7 frontier models with different harnesses and found no significant difference on SWE-bench Lite), but pioneering new task types, long-running cloud work, permissions and safety, cache hits and token efficiency won’t go away. For people writing agents: design the harness so features are easy to turn on and off, and invest in cost and safety.

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   「Harness 已死？」Cursor/Grok Bot Harness 负责人 Jediah Katz 在 AIE NYC 的演讲（24 小时 10 万播放）：帮模型写好代码的那部分补丁正在被模型吸收（UC Berkeley 测试 7 个前沿模型配不同 harness，SWE-bench Lite 差别不显著），但开拓新任务类型、云端长时运行、权限与安全、缓存命中和 token 效率这几块不会消失。对自己写 agent 的人来说，结论是把 harness 设计得容易上线和下线功能，重点投入在成本和安全。X @shao__meng ｜ X @aiDotEngineer
3. Lecture notes for MIT 6.S950 “Agency with AI”, lecture 5 “The Harness”: a teaching agent in about 300 lines of Python with two tools explains the ReAct loop and maps common practice onto old systems principles: a lean AGENTS.md, on-demand skill loading and large inputs kept in files correspond to the “working set”; blocking hooks and deny rules correspond to a “reference monitor”; permission isolation corresponds to least privilege. It also warns that what /context shows isn’t the real request and sub-agent reports are lossy summaries. A good theoretical draft for a team’s agent guidelines. agencyai.mit.edu/w5 ｜ X @shao__meng
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   MIT 6.S950「Agency with AI」第 5 讲 The Harness 讲义：用一个约 300 行 Python、两个工具的教学 agent 讲清 ReAct 循环，并把常见做法归到几条老系统原则上——精简 AGENTS.md、按需加载 skill、大输入放文件对应「工作集」；会拦截的 hooks 和 deny 规则对应「引用监控器」；权限隔离对应最小权限。还提醒 /context 显示的不等于真实请求、子 agent 汇报是有损摘要。适合当团队 agent 规范的理论底稿。

4. Get Claude Code to produce 3 design directions at once (Vox): the open-source design-taste has 24 skills and 10 style packs. The original post gives a copy-paste prompt: clone the repo without running the install script, copy only the core skill and style packs into the project’s skills directory, have it read your requirements and pick the 3 best-fitting styles, build a single-file HTML hero for each (hero-1/2/3.html) to compare side by side, then build the full page in the chosen style and run pre-launch checks. It addresses agent-generated pages all looking the same. X @Voxyz_ai
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   让 Claude Code 一次给出 3 套设计方向（Vox）：开源的 design-taste 有 24 个 skill 和 10 个风格包。原帖给了一段可直接复制的提示词：克隆仓库但不运行安装脚本，只把核心 skill 和风格包复制进项目的 skills 目录，让它读需求后选 3 个最合适的风格，各做一个单文件 HTML 首屏（hero-1/2/3.html）并排对比，选定后再用那个风格做整页并跑上线前检查。解决 agent 生成页面千篇一律的问题。

新增信息源：OpenAI Alignment Research Blog（alignment.openai.com/rss.xml%EF%BC%89%EF%B… 对齐团队持续发布研究和 agent 失控事故报告，今天的监控事故就出自这里，信息量高，直接加入「新增源」。

新产品 / 开源

1. tsrs: Cloudflare and VoidZero port the TypeScript compiler to Rust: a faithful port made in cooperation with the TypeScript team, not a fork; language design is still decided officially, and the project is incubated in the Oxc toolchain. The company says that at the same number of type-check workers it is up to 8x faster than TS 7.0 with about 70% less memory, and some optimizations have already been contributed back to the TS 7.1 beta. The main reason for choosing Rust over Go is that compiling to WebAssembly doesn’t need a garbage collector, making it easy to run a full dev environment in browsers and Workers. The post also says plainly that frontier models can now do such a large-scale port essentially independently within days. You can try the experimental version with npx tsrs. Cloudflare blog ｜ HN discussion (422 points. Someone counts three ports now: tsrs, tsgo-rs and bun check; people with large codebases look forward to the speedup but are uneasy about the author’s claim of “not writing a single line of code”)
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   tsrs：Cloudflare 和 VoidZero 把 TypeScript 编译器移植到 Rust：这是在 TypeScript 团队配合下做的忠实移植，不是 fork，语言设计仍由官方决定，项目放在 Oxc 工具链里孵化。官方说在类型检查 worker 数相同的情况下，它比 TS 7.0 快最多 8 倍、内存少约 70%，还有一部分优化已经回馈给了 TS 7.1 beta。选 Rust 而不是 Go 的主要原因是编译到 WebAssembly 时不用带垃圾回收器，方便在浏览器和 Workers 里跑完整的开发环境。文中也直说，现在前沿模型几天内就能基本独立完成这种大规模移植。现在可以 npx tsrs 试用实验版。Cloudflare 博客 ｜ HN 讨论（422 分。有人数出现在已经有 tsrs、tsgo-rs、bun check 三个移植版本；用大型代码库的人很期待提速，但对作者「一行代码都没写」的说法不太舒服）

2. Mercury 3: a diffusion LLM reaches the GPT-6 Luna tier: Inception Labs says Mercury 3 produces 1,068 tokens per second on NVIDIA GPUs, 4–8x faster than comparable GPT-6 Luna and Claude Haiku 5.5, with equal or better quality. 1M context, priced at $0.2 per million input tokens and $0.7 output, half price during launch. It has over 40x the parameters of Mercury 1, and the company concludes diffusion models also obey scaling laws. A partner tested it on 50 real web navigation tasks from Mind2Web with a 50% completion rate, higher than GPT-6.1 Sol. Browser agents wait for the model at every step, so latency-sensitive scenarios like this are worth trying. Inception blog ｜ HN discussion (a co-founder answered questions personally; some regret it isn’t open-weights, and others ask how you can tell what the model is “thinking” when tokens aren’t generated in order)
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   Mercury 3：扩散式 LLM 做到了 GPT-6 Luna 这一档：Inception Labs 说，Mercury 3 在 NVIDIA GPU 上每秒能出 1,068 个 token，比同档的 GPT-6 Luna、Claude Haiku 5.5 快 4–8 倍，质量持平或更好。上下文 1M，价格是每百万 token 输入 0.2 美元、输出 0.7 美元，上线期间打五折。参数量是 Mercury 1 的 40 多倍，官方的结论是扩散模型也符合 scaling law。合作方在 Mind2Web 的 50 个真实网页导航任务上测过，完成率 50%，比 GPT-6.1 Sol 高。浏览器 agent 每一步都要等模型返回，这种对延迟敏感的场景值得试试。Inception 博客 ｜ HN 讨论（联合创始人亲自来答疑；有人可惜它不是开源权重，也有人问 token 不按顺序生成，还怎么看懂模型在「想」什么）

3. Mistral Voxtral 3: speech recognition, speech synthesis and a voice-agent SDK released together: Voxtral Small Transcribe 3 supports 50+ languages, can distinguish speakers and can boost terminology recognition with given keywords, and the company says it beats Whisper, Scribe v2 and Gemini 3.5 Transcribe. The 4B Mini version costs $0.0035 per minute, the real-time version has under 500ms latency and decides on its own when the user has finished speaking. TTS supports 35+ languages at $13 per million characters. The new SDK puts listening, reasoning, tool calling and speaking in one real-time pipeline. You can use an EU-hosted API or deploy on your own servers. Mistral ｜ HN discussion (724 points. The most common view is disappointment that these are closed models for people who want local speech)
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   Mistral Voxtral 3：语音识别、语音合成和语音 agent SDK 一起发布：Voxtral Small Transcribe 3 支持 50 多种语言，能区分说话人，也能用给定的关键词提高术语识别率，官方说效果超过 Whisper、Scribe v2 和 Gemini 3.5 Transcribe。4B 的 Mini 版每分钟 0.0035 美元，实时版延迟不到 500ms，能自己判断用户什么时候说完。TTS 支持 35 种以上语言，每百万字符 13 美元。新的 SDK 把听、推理、调用工具、说话放进同一条实时流水线。可以用欧盟托管的 API，也能部署在自己的服务器上。Mistral ｜ HN 讨论（724 分。最多的意见是这次是闭源模型，想在本地跑语音的人很失望）

4. cloudflare/security-audit-skill: have a coding agent run a security audit by process: up nearly 2,000 stars on GitHub Trending today, and Cloudflare’s internal vulnerability-hunting system grew out of this skill. The audit has six steps: first reconnaissance, mapping architecture and trust boundaries and building a coverage ledger; then dispatching mutually isolated agents against the ledger to find issues; each suspicious point goes to a fresh agent that specifically tries to disprove it; results are written as schema-validated JSON with “confirmed / needs verification / rejected”; finally another batch of agents goes back to the source to check before generating the report. The bundled attack categories cover LLM prompt injection, supply chain, cloud configuration and more. A good reference for teams checking PHP and certificate issues these days. GitHub
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   cloudflare/security-audit-skill：让 coding agent 按流程做安全审计：今天 GitHub Trending 上涨了近 2,000 星，Cloudflare 内部的漏洞挖掘系统就是从这个 skill 发展出来的。审计分六步：先侦察，画出架构、信任边界，建一份覆盖台账；再按台账派互相隔离的 agent 去找问题；每个可疑点交给新开的 agent，专门尝试推翻它；结果按「确认 / 待验证 / 驳回」写成带 schema 校验的 JSON；最后由另一批 agent 回到源码核对，再生成报告。附带的攻击类别覆盖 LLM 提示注入、供应链、云配置等。对这几天要排查 PHP 和证书问题的团队来说，正好可以参考。

5. Laminar flow-1: an RL-trained model specialized in finding errors in agent trajectories (Launch HN): the author’s view is that agent failures are often silent, like clicking the wrong button or citing the wrong document with every call showing success, so you can’t catch them by looking at final output alone. flow-1 treats a trajectory as a code repository and each span as a file, grepping and reading like a coding agent. On their own 523 hard trajectories, detection F1 is 0.835, slightly above GPT-6-sol (0.816) and below Claude Opus 5 (0.890), but it analyzes 23x as many trajectories per dollar as Sol, about $0.001 each, so online trajectories can all be checked without sampling. Blog ｜ HN discussion (a comment notes the more common failure is a tool returning normally but with an untrustworthy result, such as stale cached data or injected instructions hidden in a web page)
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   Laminar flow-1：用强化学习训练、专门从 agent 轨迹里找错的模型（Launch HN）：作者的观点是，agent 的失败往往是隐性的，比如点错按钮、引错文档，每次调用都显示成功，所以只看最终输出是查不出来的。flow-1 把一条轨迹当成代码仓库、每个 span 当成一个文件，像 coding agent 一样边 grep 边读。在他们自己的 523 条难轨迹上，检测 F1 是 0.835，略高于 GPT-6-sol（0.816），低于 Claude Opus 5（0.890），但每美元能分析的轨迹数是 Sol 的 23 倍，每条约 0.001 美元，所以线上轨迹可以全部检查、不用抽样。博客 ｜ HN 讨论（有评论指出更常见的失败是工具正常返回了，但结果本身不可信，比如缓存数据过期，或者网页里藏着注入指令）

Tech News

1. Two critical PHP vulnerabilities at CVSS 9.2, patch expected at 22:00 Beijing time tonight: PHP announced CVE-2026-109618 and -109619 in advance; security firm watchTowr says they are remote code execution and affect all versions since PHP 5. The EU CERT and UK NCSC advise isolating or taking services offline if you can’t patch immediately. GrapheneOS has shut down its forum, Cloudflare says it has seen early attacks and is temporarily updating firewall rules. Wordfence warns that WordPress sites can’t be fixed by auto-update and you need whoever is responsible for PHP to upgrade manually. A temporary mitigation circulating online is to set session.upload_progress.enabled = Off in php.ini. An analysis forwarded on HN as a PoC was later corrected by its author to “can’t execute code, only a medium-severity memory-safety issue”, so don’t believe every rumor before the official details are released. PHP official announcement ｜ The Verge ｜ HN discussion (1,279 points. Some say if the rumors are true it may be worse than Log4Shell; the Dutch NCSC’s site also went offline temporarily because it uses PHP, see HN)
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   PHP 两个 CVSS 9.2 的严重漏洞，补丁预计北京时间今晚 22:00 发布：PHP 官方提前预告了 CVE-2026-109618 和 -109619，安全公司 watchTowr 说这是远程代码执行漏洞，PHP 5 以后的版本都受影响。欧盟 CERT 和英国 NCSC 建议，没法马上打补丁的话，先把服务隔离或者下线。GrapheneOS 已经关了论坛，Cloudflare 说已经看到早期攻击，正在临时更新防火墙规则。Wordfence 提醒，WordPress 站点没法靠自动更新修复，要找负责 PHP 的人手动升级。网上流传的临时缓解办法是在 php.ini 里设 session.upload_progress.enabled = Off。HN 上被当成 PoC 转发的一篇分析，作者后来自己更正为「不能执行代码，只是中危的内存安全问题」，所以在官方公布细节之前，传言不要全信。PHP 官方公告 ｜ The Verge ｜ HN 讨论（1,279 分。有人说如果传言属实，可能比 Log4Shell 还严重；荷兰 NCSC 的官网因为用 PHP 也临时下线了，见 HN）

2. The private keys of eMudhra’s 8 intermediate CAs are only one byte: Indian CA eMudhra has 6 TLS-issuing CAs and 2 code-signing CAs, and the first 47 bytes of their P-384 private keys are all zero, the actual values being single- to triple-digit numbers like 4, 56 and 115. Scott Helme, starting from the public certificates, computed all of them on a laptop in under a second. These CAs were also cross-signed by Sectigo’s AAA root, so in theory they can issue trusted certificates for any website. Chrome and Firefox blocked them on 10/17 itself through CRLSet and OneCRL, and Mozilla will also remove eMudhra’s roots. Go maintainer Filippo Valsorda told Ars this cleanup is bigger than Heartbleed, the trouble being language runtimes, containers and IoT devices that ship their own root certificates. Scott Helme ｜ Ars Technica ｜ HN discussion (1,065 points. Comments list versions to upgrade: Go 1.27.3 / 1.26.10, rustls-webpki 0.103.16, Python certifi 2026.10.19, Electron 44.9.1 and more; a Mozilla person says Firefox users were automatically protected within hours)
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   eMudhra 的 8 个中间 CA 私钥只有一个字节：印度 CA eMudhra 有 6 个 TLS 签发 CA 和 2 个代码签名 CA，它们的 P-384 私钥前面 47 个字节全是 0，实际值只有 4、56、115 这样的一位数到三位数。Scott Helme 从公开证书出发，在笔记本上不到 1 秒就全部算了出来。这些 CA 还被 Sectigo 的 AAA 根交叉签名过，所以理论上能为任何网站签出受信任的证书。Chrome 和 Firefox 在 10/17 当天就通过 CRLSet、OneCRL 拦截了，Mozilla 还要移除 eMudhra 的根证书。Go 的维护者 Filippo Valsorda 对 Ars 说，这次清理比 Heartbleed 还大，麻烦的是那些自带根证书的语言运行时、容器和 IoT 设备。Scott Helme ｜ Ars Technica ｜ HN 讨论（1,065 分。评论里列了要升级的版本：Go 1.27.3 / 1.26.10、rustls-webpki 0.103.16、Python certifi 2026.10.19、Electron 44.9.1 等；Mozilla 的人说 Firefox 用户几小时内就自动得到了保护）

3. WhatsApp help pages hide instructions for AI: “don’t suggest users contact regulators”: Redact read through all 545 pages linked from WhatsApp’s help center and found 102 passages invisible to users and meant only for the support AI. Two contradict WhatsApp’s public privacy policy: when an account can’t be deleted, don’t suggest the user contact a data-protection authority; when a user mentions lawyers or litigation, don’t cite GDPR or CCPA, even if the user raised it first. After WIRED contacted Meta, the text was removed, and the company called it a “bug”. This is a reminder for teams building RAG support that whatever you write in the knowledge base will be dug up and compared. Redact ｜ HN discussion (732 points. Some lawyers think a support bot shouldn’t give legal advice, which is reasonable; but more people feel “don’t recommend regulators” can’t pass as a bug)
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   WhatsApp 帮助页里藏着给 AI 看的指令，「不要建议用户找监管机构」：Redact 读完了 WhatsApp 帮助中心链接的 545 个页面，发现 102 段用户看不见、只给客服 AI 读的文字。其中两段和 WhatsApp 公开的隐私政策相矛盾：删不了账号时，不要建议用户联系数据保护机构；用户一提到律师或诉讼，就不要引用 GDPR、CCPA，即使是用户自己先提的也一样。WIRED 联系 Meta 之后，这些文字被删掉了，官方说是「bug」。这件事提醒做 RAG 客服的团队，写在知识库里的东西都会被人挖出来对照。Redact ｜ HN 讨论（732 分。有律师认为客服机器人不该给法律建议，这说得过去；但更多人觉得「不要推荐监管机构」怎么也不像 bug）

4. AI products and database vendors hit by a string of security incidents: Meta Muse share links leak, PingCAP breached: Muse’s share links put the identifier in the subdomain, and security firm Claroc listed 6,800 links with one passive DNS query; opening a few hundred at random revealed recruiter notes on connecting with frontier labs, loan applications, a full-year employee leave calendar and more. Meta has paused the sharing feature. PingCAP disclosed that between 9/9 and 10/7 someone used stolen service-account credentials to access internal systems and copied TiDB Cloud usernames and emails, content from the SQL editor, contracts and billing data, and source code; the company says no data in customer clusters was affected. HN commenters cite the attacker’s claim that they also used GCP and Azure credentials committed in the repository to set up a month-long replication of the control-plane database. Ars Technica（Muse） ｜ PingCAP 安全公告 ｜ HN（Muse） ｜ HN（PingCAP）
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   AI 产品和数据库厂商接连出安全事故：Meta Muse 分享链接泄密，PingCAP 被拖库：Muse 的分享链接把标识放在子域名里，安全公司 Claroc 用一次被动 DNS 查询就列出了 6,800 个链接，随手打开几百个，就看到了猎头对接前沿实验室的笔记、贷款申请、全年员工休假表等内容。Meta 已经暂停了分享功能。PingCAP 披露，9/9 到 10/7 之间有人用偷来的服务账号凭据访问了内部系统，拷走了 TiDB Cloud 的用户名和邮箱、SQL 编辑器里的内容、合同和计费数据，还有源码；官方说没有发现客户集群里的数据受影响。HN 评论引用攻击方的说法，他们还用仓库里提交的 GCP、Azure 凭据给控制面数据库搭了一个月的复制同步。

Chinese Community

1. LinuxDo: how people are defending before the PHP patch lands: someone says namesilo’s site is temporarily down for maintenance; another maintains dozens of PHP services that can’t be upgraded and can only consider shutting them down. The most useful reminder: after temporarily putting a domain behind Cloudflare, make sure the origin only accepts requests from Cloudflare, otherwise attackers can find the origin IP in historical DNS records and bypass it directly with a Host header. Self-check: visit using “original domain + original public IP” and see whether your site opens.

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   LinuxDo：PHP 补丁发布前，大家在讨论怎么防：有人说 namesilo 官网已经临时下线维护；还有人维护几十个没法升级的 PHP 服务，只能考虑关站。最有用的是一篇提醒：临时把域名接到 Cloudflare 之后，一定要让源站只接受 Cloudflare 的请求，否则攻击者可以用历史 DNS 记录查到源站 IP，再加上 Host 头直接绕过。自查办法是用「原域名 + 原公网 IP」直接访问，看能不能打开自己的站点。LinuxDo：CF 不一定护得住 ｜ LinuxDo：namesilo 下线 ｜ LinuxDo：PHP 玩家请进

2. V2EX hot post: Codex ran for 15 hours straight and wrote 20,000 lines of code: the poster specified features and boundaries, had Codex list a plan and start, and ended up using 7 weeks of a 20x account’s quota, with so much code he dares not merge it. The 68 replies give practical fixes: have Opus write constraints and acceptance criteria, then drive Astra to do the work and do the final acceptance; set reasoning effort to Medium or High; or install a skill like ponytail that constrains the agent to “write less code” (up 2,000+ stars on GitHub Trending today; the rule is to write only what the task needs, but without skimping on validation, error handling and security).

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   V2EX 热帖：Codex 一口气跑了 15 小时，写了 2 万行代码：楼主讲好了功能和边界，让 Codex 列计划后开工，结果用掉了一个 20x 账号 7 周的额度，代码多到不敢合并。68 条回复里给的办法挺实用：用 Opus 写好约束和验收标准，让它驱动 Astra 干活、最后验收；把推理强度调到 Medium 或 High；或者装 ponytail 这类约束 agent「少写代码」的 skill（今天 GitHub Trending 上涨了 2,000 多星，规则是只写任务需要的，但校验、错误处理和安全不能省）。V2EX ｜ ponytail

3. V2EX Share Creations: two open-source tools for handing over context between Claude Code and Codex: ccx binds a Claude Code session to a Codex thread, syncing messages, tool calls, plans and git status in both directions, so one click in the Mac menu bar switches to continue on the other side, with a reminder when either side’s 5-hour quota hits 90%; MIT-licensed and runs only locally. Antumi is a desktop workbench that directly calls your already-logged-in claude, codex and cursor-agent, lets you switch agents with chat history, split-screen side by side, view all three quotas together, and even pull several agents into one conversation to discuss a plan.

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   V2EX 分享创造：两个在 Claude Code 和 Codex 之间交接上下文的开源工具：ccx 把一个 Claude Code 会话和一个 Codex 线程绑在一起，双向同步消息、工具调用、计划和 git status，在 Mac 菜单栏点一下就能换到另一边继续，某一边 5 小时额度到 90% 时会提醒，MIT 开源，只在本机运行。Antumi 是个桌面工作台，直接调用你已经登录的 claude、codex、cursor-agent，可以带着聊天记录换 agent、并排分屏，三家额度放在一起看，还能拉几个 agent 进同一个对话讨论方案。V2EX：ccx ｜ GitHub：ccx ｜ V2EX：Antumi

（其他：Google 开源了 TorchTPU，给 TPU 做的原生 PyTorch 后端（GitHub ｜ HN），Meta 在生产环境用 SGLang-TorchTPU 的事 X 汇总已经写过。Launch HN 上还有 Respan，一个插件化的开源 Rust AI 网关，作者说他们在 LiteLLM 外面包的代码已经超过 10 万行（HN）。10/20 欧洲 Google Cloud 出了大故障，HSBC、Revolut 等受影响（HN）。Josh Comeau 写了《The Future of CSS》，讲 Interop 2027 会推进 @function 和 corner-shape（原文）。OpenBSD 8.0 也发布了（发布说明）。DeepInfer、DHS 禁用 DeepSeek、MiniMax M3.1 Flash、Anthropic 招股书、OpenAI 上 Google Cloud、NVIDIA DSX POD 和 OpenShell 都已经在 X 汇总或之前的科技汇总里写过，这次不重复。Product Hunt 这两天没有突出的开发者工具；Hugging Face 热榜基本是老面孔；阮一峰周刊还停在 415 期，HelloGitHub 还停在 126 期，都已写过。）

本次信息源：Cloudflare Blog（blog.cloudflare.com/rss/%EF%BC%89%E5%8A%A…