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C2機関「艦これ」舞台2025 【突入！礼号作戦1944】presented by avex live creative inc. 観劇して参りました!!! 艦娘みんな本当に可愛くて、物凄くカッコ良くて 何より実在していた！！！ 深海のビジュアルとオーラと魅せ方でみせる 演出も本当にドキドキしました!!! 最後まで怪我のないよう駆け抜けることができるよう祈っています🥺❣️❣️ #艦これ舞台# #礼号作戦# #C2機関# #CLUBeX# 観に行けてよかったー!!!!!!!✨

横浜みなとみらいでお贈りする、C2機関鎮守府新春【New Year SHIGURE Live! 2023】夜戦公演も無事作戦完了しました！ ご参加の提督の皆さん、ToshLOVEの皆さん、応援を頂いたお茶の間の皆さんも、本当にありがとう！ ありがとう！何度もいいますッ！ #C2機関# #新春ライブ# #時雨# #未来# #DIVADIVA#

遅くなってしまいましたが…【C2機関“瑞雲”&“秋刀魚”祭り2022 】1MYBのキーボードとして参加させていただきました！1MYBメンバー、出演者の皆様、そして提督の皆々様があたたかく迎えてくださり嬉しかったです、、本当にありがとうございました！秋刀魚もカレーもおいしかったあ♡ #瑞フェス# #ZUIFes#

【C2機関"瑞雲"＆"秋刀魚"祭り2022 in FSW】 ２日間ありがとうございました！ みなさまと一緒に素敵な秋の思い出が作れて本当に濃い時間でした🍁 高機動型の遊撃隊もどうぞ、よろしくお願いしますねっ😉 #C2機関# #FSW# #艦これ# #ZUIFes# #艦娘遊撃隊改# #霧島# #艦娘遊撃隊#

【C2機関"瑞雲"＆"秋刀魚"祭り2022 in FSW】、略してZUI Fes.！ 参加チケットご案内が開始されました！ この秋、富士の裾野で共に「瑞雲」！ そして、共に「秋刀魚」を！ #C2機関# #FSW# #艦これ# #ZUIFes# #艦娘音頭# #無良提督# #1MYB# #松井咲子# #艦娘遊撃隊# #吉田兄弟# #龍玄とし#

こんにちわ♪ お久しぶりなのです٩( ‘ω’ )و シャドバンの影響もあり、コチラは少し放置してました💦 （現在は解除されたのでもう安心！！w） 皆さんGWはいかがでしたか？ 私は久しぶりに帰省と息抜きに富士スピードウェイへスーパーGTを観戦しに行きました！ 飛行機乗ったり、レンタカー乗ったりでハードな4日間でした_:(´ཀ`」 ∠):w 昨年ぶりに観戦したスーパーGTはもちろん車もカッコいいし、レースは迫力満点！ レースクイーンの皆さんも可愛いし、スマホ片手にずっと写真撮っては出店の食べ物をもしゃり…とても楽しい1日を過ごせました٩( ᐛ )و お写真は… ・グッドスマイルレーシング 初音ミクAMG ・GT500 GRスープラ ・GRスープラセーフティーカー ・C2機関 です！ それから、私の夢が1つ叶ったのでちょっとしたご報告になります٩(ˊᗜˋ*)و 私事ですが、GW前に目標としていたGRスープラの購入が出来ました！ 頑張ってお仕事を続けて出来たのも、皆さんが応援してくれたおかげです♪ 本当にありがとうございます💕 これからも皆さんが楽しんでもえるようにいっぱい頑張ります٩( ‘ω’ )و

DeepSeek-V4-Flash-DSpark has now completed the r0b0bench core-subset protocol on 2× NVIDIA GB10. ⚡ Quality • GSM8K: 95.0% • HumanEval pass@1: 90.9% • ARC-Easy: 96.0% • IFEval lightweight: 79.5% • BFCL multi-turn: 75.5% Performance • Dedicated C1 decode: 79.2 tok/s • Aggregate output throughput: C1 86.9 · C2 145.9 · C4 239.3 · C6 337.8 tok/s • TTFT mean: 221.9 ms • ITL mean: 68.9 ms Long context Needle retrieval passed at 25%, 50%, and 90% depth across a full 1,048,576-token context. ✅ 0 infrastructure errors ✅ Runtime gate passed ✅ 5/5 canaries passed ✅ Package-backed, reproducible result freeze ✅ Valid for publication These are measured results—not projected capabilities or marketing claims.

经典，AI vs AI 真实攻防战👍 这次事件与我们以往处理过的任何事件有一个重要区别：它是由一个自主 AI Agent 系统从头到尾驱动的，而我们也主要依靠自己的 AI 来检测和剖析它。 … 这次行动由一个自主代理框架执行（看起来是基于一个代理式安全研究框架构建的，具体使用的是哪个 LLM 尚不清楚），它在大量短生命周期沙箱组成的集群中执行了数千个独立操作，命令与控制（C2）服务器自迁移部署在公共服务上。这与行业一直在预测的“代理式攻击者”（agentic attacker）场景完全吻合。 … 不对称性问题（The asymmetry problem） 当我们开始日志分析时，首先尝试使用商业 API 背后的前沿模型。但这行不通：分析需要提交大量真实的攻击命令、利用负载和 C2 产物，而这些请求被提供商的安全护栏（safety guardrails）拦截了——它们无法区分事件响应者和攻击者。 我们最终改用 GLM 5.2 在自己的基础设施上运行取证分析。这带来了第二个好处：没有任何攻击者数据或它引用的凭证离开我们的环境。

🚨 Threat Intelligence | On-Chain Backdoor in a Malicious TRAE Extension Following @Will42W’s warning about TRAE IDE extension supply chain risks, SlowMist investigated the malicious extension juannegro.solidity. Although removed from Open VSX, the extension was still available through the TRAE marketplace as of July 18, 2026. It impersonated a legitimate Solidity plugin and acted as a cross-platform malware dropper. Our analysis found that it: 🔹 Impersonates a legitimate Solidity extension and uses the marketplace as the initial malware delivery channel 🔹 Automatically executes after IDE startup and establishes persistence across platforms 🔹 Uses an Ethereum smart contract to store and retrieve dynamic C2 configurations 🔹 Allows attackers to update C2 endpoints and payload delivery without republishing the extension This incident highlights how extension marketplaces can become initial infection vectors, while blockchain infrastructure can be abused for dynamic C2 management. Users who installed juannegro.solidity should remove the extension and check their systems for potential compromise. Full analysis👇

⚡ 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 🫡