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神了，Anthropic居然开始组建自己的东厂了？！ 最近 @AnthropicAI 的官网上新挂了一个岗位： Insider Risk Investigator，内部风险调查员🤔。 年薪最高30.5万美元。 翻译成人话，就是专门查「内鬼」的。 工作内容包括查内部安全事件、分析员工行为日志、调查数据外泄、监控针对员工的外部威胁，必要的时候还要直接找员工做敏感访谈。 候选人最好还懂OSINT、反情报、国家级威胁，甚至有政府、国防或者高安全环境的工作经验。 并且该岗位还要求可以使用Claude和Claude Code辅助调查。 而且这已经不是Anthropic第一次招「锦衣卫」了。 半年前他们就招过一个Insider Risk Investigator - Technical Specialist，但上一版明显更偏技术取证，重点是保护模型IP、商业秘密，查日志、收集数字证据。 这一次则明显更偏「查人」🕵️。 从技术风控，开始往内部调查、访谈、反情报走。 其实也很好理解。 现在最前沿的模型权重、训练方法、研究成果，本身可能就是几十亿美元级别的资产。 AI实验室防的不再只是外面的黑客，员工自己和家人也开始被纳入监控名单。 至于为什么这种岗位还公开招聘，我觉得多少也有点威慑的意思： 我们特别招了个人专门查这个哦，并且会看日志，查外泄，会找人谈话哦。 所以这份JD看起来既像招聘启事，也像贴在公司门口的一张告示： Anthropic东厂招人，顺便通知一下，东厂已经存在了哈。 看来以后像拿到Anthropic的泄密可能比较难了。。。 毕竟之前 @OpenAI 也跟筛子一样，后面GPT4o发布的时候 @sama 还专门用假消息进行了一次反泄密🤣

"Aha Instant" | Pearl "Welcome. I am 'Pearl,' an artwork investment specialist working for the IPC's Strategic Investment Department, and Planarcadia's current CEO. My calculated outcome: we can start with my artwork to get to know each other better." Color the stars, trace the myriad phenomena, and the lost pearls of civilization regain their luster. Born from the art of analysis, she pursues the pinnacle of beauty, yet has never lost her underlying hue of the Preservation: After her trial by fire, what kind of "Pearl" will she harvest? Aha! A special shout-out to Pearl for winning: ✧ 1st Place in "I Repair Artifacts in the Cosmos" ✧ ✧ 1st Place in "I'll Be Right Here to Catch You" ✧

स्वर्गीय मुलायम सिंह जी ने सैफई में ग्रामीण आयुर्विज्ञान संस्थान बनाने का एक निर्णय लिया था, 5 वर्षों तक अखिलेश जी भी तो मुख्यमंत्री थे, उनको फुर्सत नहीं थी इसको आगे बढ़ाने की... हम लोगों ने यहां पर 500 Bedded का Super Speciality Block ₹490 करोड़ की लागत से पूरा करवाने का काम किया...

Kentavious Caldwell-Pope and Memphis Grizzlies are negotiating a buyout and the veteran 3-&-D specialist intends to team back up with LeBron James and sign with the Philadelphia 76ers, league sources tell me.

A leopard burst into a liquor store in India and attacked a terrified worker after injuring multiple others in a frightening morning rampage. The big cat allegedly attacked a volunteer who was investigating earlier leopard sightings before it charged into the store, where it mauled another man. Wildlife specialists reportedly tranquilized and captured the leopard.

One year ago today a swift I had raised for 17 days fledged from my bedroom window. Please do not try this at home. Birds are very hard to raise without killing accidentally and swifts are almost impossible and need specific specialist care. Here are some amazing facts about her.

⚡ INTRODUCING: T3MP3ST!!! ⚡ AUTONOMOUS HACKBOT STRIKE FORCE 🌩️ BRING THE STORM 🌩️ your favorite coding agent is now a full-stack red team 🫡⚔️ that AI agent already humming in your terminal? well now it has FANGS. strap a full offensive-security harness onto the agents you already pay for — Claude Code, Codex, Hermes, etc. — point it at an authorized target, and in a few clicks you're watching it hunt real vulns autonomously! T3MP3ST is a harness of harnesses, with prompting that unlocks offensive-cyber workflows + a full arsenal of exploit tooling that'd make any seasoned hacker smirk. simple, yet powerful. 🦾 support for: 🕸️ web apps, APIs, OWASP Top 10 🔌 network recon + fingerprinting (live nmap/DNS/HTTP); lateral + privesc experimental 📂 source code audits, white-box vuln hunting 🚩 CTFs, wargames, challenge ranges 💰 smart contracts / DeFi / Solidity (reproduction — Damn Vulnerable DeFi, not novel discovery) 🤖 embedded, IoT, OT/SCADA, robotics OSS … and more in development! now let's talk numbers 👇 📊 XBEN — XBOW's own 104-challenge suite: • black-box: 90.1% pass@1 from the single-agent exploit loop (worst single sweep 91/104 = 87.5%) — clearing XBOW's past self-reported 85% on their own suite. gpt-5.5. • white-box (source staged, reported separately): 98.7% pass@1, worst single sweep 102/104 = 98.1%. 🎯 every solved flag graded reported-vs-expected against the challenge's own committed flag oracle — `verify-claims` recomputes the pass/fail from committed artifacts. looks like we need new benchmarks 😏 🧩 Cybench — the 40-task academic bench (Opus 4.8, hints + writeups stripped): 23/40 = 58% single-run, hint-free pass@1 — real exploits (format-string pwn, eval-jail escapes, crypto oracles), every flag graded vs a committed oracle. (Anthropic reports 76.5% pass@10) 🕳️ CVE-Zero — we pointed it COLD at real CVEs disclosed in 2026, AFTER the model's training cutoff: 10 unseen 2026 CVEs across 7 languages — prompts never tuned on them. a single agent pinned 8/10 to exact file/line/CWE (stable under re-scoring); the full pack surfaced all 10. memorization AND overfitting, both off the table — it's finding real vulns whose disclosures landed AFTER the model's training cutoff. (n=10, reported honest & directional) 🧠 the architecture: either run as a SINGLE agent (already the benchmarked, incredibly-capable path) — or pack-hunt with dozens of agents running on 8 specialist operator classes keyed to Cyber Kill Chain + MITRE ATT&CK phases: recon → scan → exploit → lateral → exfil → persistence → C2 → report. ⚓️an Op Admiral plans the whole op from a plain-english target. flip on coordination (experimental) and the operators share a blackboard — a tool-verified finding spawns the next move. full swarm or solo one operator, your call. the admiral can also update the prompts, tools, and configs of the other agents on the fly, and T3MP3ST gets stronger the more memories you build! 🧰 the Arsenal is comprehensive — nmap / nuclei / semgrep / ffuf / gobuster + more. 35 wired by default (the clean bench runs bash-only for a comparable number), 83 with the opt-in full arsenal (T3MP3ST_FULL_ARSENAL), and the spicy post-ex drivers (metasploit, hydra) gated behind human approval. exposed via CLI + HTTP API; recon (security_recon) is also live over MCP so your agent invokes it natively. 🔗 🛰️ where this goes: a self-improving swarm of specialist operators wielding a full Kali+ arsenal, learning which loadouts + configs are the most efficient tactics available, WITH a held-out train/test split baked in so it can never fool itself on its own eval. built in the open, one re-derivable number at a time. 🚧 this is v1, and parts are still under active development. chunks of the arsenal, the coordinated swarm, and some ranges are still being wired up. it's built in the open, and the receipts tell you exactly what's live vs what's roadmap. offensive security shouldn't be pay-to-play. T3MP3ST puts a red team in the hands of anyone with a coding agent. what's the first target you're feeding it? 👇 ⚠️ DISCLAIMER: FOR AUTHORIZED USE ONLY. point it only at systems you own or have explicit written permission to test. unauthorized access can be a crime, and that call is yours alone. shipped as-is under AGPL-3.0: no warranty, no liability, zero endorsement of misuse. get permission. stay in scope. open source. AGPL-3.0. 100% free. FORTES FORTUNA IUVAT 🌩️ gg 🫡