Ben Chung

of course these views are my own,

[Erin Burnett OutFront @OutFrontCNN]

Former Trump White House lawyer Ty Cobb on Trump earning over $1 billion last year from crypto ventures: “We are seeing the greatest onslaught of corruption in the history of mankind.”

[Georgia Channing @cgeorgiaw]

Seems like no one's noticed the 80TB of astrophysics data from 30+ sources that just dropped on @huggingface.

...and you only need ~4GB of RAM to load it.

We're talking over 80TB of galaxy imagery taken across the spectrum, spectra of galaxies and stars, time series of variable stars, and a whole zoo of assorted measurements and physical data.

And all of it can now be wrangled on your laptop, thanks to Multimodal Universe's just released cross-matching. SDSS x Gaia means you can match 800k objects against 122M objects, and it never climbs above ~4GB of RAM.

Huge congrats to @smith42mike for leading this and making the world of astro accessible to probably 10,000x more people. Let's discover some shit

[Jeremy KD8TUO 🇺🇸⏦⎓⎎⎍⏚ @ElectronicsbyJH]

Great @CERN lecture note on the basics of RF electronics, covering mixers, filters, directional couplers, oscillators, amplifiers, attenuators, scattering matrices, transfer functions, and more.
A useful reference for RF, ham radio, and SDR work:

https://t.co/NEhrHE6ygH

[BlueDream @58bugeye]

Supreme Court Justice Clarence Thomas was caught sneaking out of speaker Mike Johnson’s office.

A Supreme Court justice should not have a private meeting with the speaker of the house.

What were they talking about?

[Frank C @FrankCMYK]

"I just want to find 11,780 votes," –Donald J. Trump

Isn’t it ironic that the guy caught on tape trying to overturn an election is the same guy screaming about mass voter fraud?

That’s the psychological voodoo Trump pulled on America. He convinced millions of people that a voting system that worked for generations suddenly became “broken” the moment he lost, and broken in a way only he could fix.

But Trump doesn’t fix systems. He breaks them, blames someone else, and then sells himself as the repairman.

Trump is the mass voter fraud.

[vp.net @vpnet_official]

djb (@hashbreaker) told us about an NSA employee who showed up on the IETF TLS mailing list for the first time ever. Their one and only vote: weaken encryption. 🤦‍♂️

The NSA lost the last vote, so now they're packing the next one and we need YOU to help us beat the NSA!

Full conversation in the thread 👇

[Álvaro J @jota_snchez]

Robert Sapolsky es un neurocientífico de Stanford que demostró que el estrés es el asesino silencioso que los médicos ignoran.

Reveló 10 hábitos que haces todos los días y que te quitan años de vida.

1) Repasar conversaciones en tu cabeza

[cr3ghost @cr3ghost]

The creator of Cobalt Strike left the industry in 2021, came back, and is now publishing everything he knows about evasion tradecraft openly and for free.

Tradecraft Garden separates evasion tradecraft from capability. Crystal Palace is the linker that makes it work: position-independent code, binary transformation, code and register randomization, link-time hooking, YARA rule generation from invariant instructions, and a PICO convention for reusable tradecraft modules.

The community built an entire ecosystem on top of it. Crystal Kit for Cobalt Strike, Sliver, Mythic, and Adaptix. Reflective loaders, call stack spoofing, sleep masking, module overloading. Offense and defense both benefit because every technique is published as a testable ground truth.

If you work in red teaming, detection engineering, or EDR evaluation, this is required reading.

TTPs: https://t.co/A4O6Tuh58M
Blog: https://t.co/4jb7cRpcA9

His original Red Team Ops with Cobalt Strike series is also still on YouTube. 9 parts covering the full red team operations workflow. Free. From the person who built the tool. Red Team Ops with Cobalt Strike - Operations (1 of 9): https://t.co/Jd28yWuaYs

Author: Raphael Mudge

#BlueTeam #InfoSec #RedTeam

[sapir federovsky @sapirxfed]

I recently found myself trying to explain FOCI & BroCI to a colleague. I thought I understood it.. I was so wrong😂
So I took a few days to dive deep into this. I hope this will help you as much as it helped me!💙
https://t.co/PVIZxNuhlP

[Mark Di Stefano @MarkDiStef]

KPMG and PwC are causing untold damage to reputations of consultants

EY: Hold my beer lads…

[Adam Chester 🏴‍☠️ @_xpn_]

New blog post is up looking at how LLMs are making local EDR rulesets, YARA rules, and behavioral detections trivial to extract. This post focuses on how simple the harness can be. Buckle up h4xx0rs, the next few months are gonna get interesting! https://t.co/QvzXsPA01F

[Chubby♨️ @kimmonismus]

The worst-case scenario for the United States is becoming increasingly realistic, and I will briefly explain why.

@quxiaoyin raised many valid points, and I agree with her. First of all:

-China certainly does not place such strong emphasis on open source because it cares so deeply about humanism, but because it is a strategy to attract many users, gain market share, put pressure on US models, and also because the models are increasingly being trained on Huawei hardware (think of DeepSeek 4), allowing China to host the entire stack domestically.

-But the underlying logic is far more important: The United States is still building too few data centers to meet future demand. @ChrisGillett wrote an outstanding analysis on this, which I shared a week ago. In short, based on SemiAnalysis data, demand is greater than what is currently being built in terms of data centers.

-Even more importantly, however, the United States lacks sufficient energy and grid capacity. This is a problem that will become much more severe in the near future. China, by contrast, is addressing the issue through a massive expansion of its energy supply. Solar capacity: in 2025 alone, China installed as much solar capacity as the United States did in 10 to 15 years. China is also building 36 nuclear power plants, significantly more than the United States, and is installing them faster.

-In addition, China is managing to become more independent through Huawei chips, even though the country still lags far behind NVIDIA. But here, China is betting on quantity rather than quality.

In short: China is a real threat in the AI race, and the situation for the United States is becoming increasingly precarious. This is also the main reason why China is to be kept away from SOTA LLMs at all costs, so as not to jeopardize the lead under any circumstances.

[Brian Armstrong @brian_armstrong]

How to keep AI spend flat while token usage grows exponentially: Not with friction and spend alerts. With better defaults, routing, and caching.

Better Defaults (not Usage Caps) – Engineers can choose any model they want, but defaults matter. We’re experimenting with defaulting to open weight models like GLM 5.2 and Kimi 2.7 through our LLM gateway, while still encouraging engineers to choose the right model for the task. 91% of our employees were never hitting their usage caps, so instead of lowering caps and driving up alerts, we're moving to cheaper defaults. Note that code reviews use a diversity of models, so they can check each other's work.

Better Routing – In our custom harnesses, we preprocess prompts and route to the best model for the job, considering cache hits and model pricing. For instance, you may want a frontier model for planning, but not for execution where they can be overkill. Ultimately, humans shouldn't be choosing models - AI can automate this task.

Better Caching – Cache misses are the easiest way to drive your cost up. All of our requests are cache aware, so we’re reusing a warm cache wherever possible. For example, our cache hit rate went from 5% → 60% in LibreChat once properly implemented.

Keep Context Lean – Start fresh sessions when switching tasks. Scope file context narrowly. Disconnect unused tools. Don't just compact. The goal isn't fewer tokens used, it's fewer tokens wasted.

Better Visibility – Our engineers can use as many tokens as they want, from whatever model they want, but we’ve made usage visible – and the more you spend on AI, the more impact we expect.

The goal isn't to suppress usage. It's to build the infrastructure that makes exponential growth sustainable.

Putting this into practice has cut our AI spend nearly in half, while our token usage continues to grow.

[Tomas Hernando Kofman @tomas_hk]

@brian_armstrong Super cool to see this Brian. For anyone else looking into routing, we have a guide here: https://t.co/X4o4yov5b7

[Nick VanGilder @nickvangilder]

Last night I added a new section to https://t.co/lL6ENTlNpD called Books (https://t.co/1o8ISA9h0D). The premise is super simple: do you have a book that you like (or maybe wrote) that you think other red teamers or offsec folks at large might enjoy? Sweet. Click add, type in the name of the book, and click search. You’ll be presented with a list of matches to select from.

Under the hood it searches Open Library first (then Google Books as a backup) to auto-pull the cover, author(s), publisher, year, and description, and normalizes the ISBN so nothing gets duplicated. If the author is already on the site elsewhere with a conference talk, training, lab, etc., it’ll connect all of that so you can see the linkages. If they’re not on the site, you have the option to have AI go find their social accounts and add them.

I resisted the urge to seed the page with tons books right out the gate, so please feel free to add books at your leisure.

[📕「マルウエアの教科書」著者 | 吉川孝志 | 増補改訂版🌟発売中 @MalwareBibleJP]

CVEごとの公開PoCを複数の脆弱性指標と自動突合するOSSダッシュボード「CVE-Map」が公開されています。突合対象はNVD（米国立脆弱性データベース）の深刻度、CISA-KEV（実環境で悪用が確認された脆弱性のカタログ）の登録有無、EPSS（悪用予測スコア）の3種。Go製エンジンがGitHub上のexploitリポジトリを6時間おきに自動巡回し、各CVEにこれらの指標を紐付けて静的HTMLとして出力する設計。

【要点の整理】

・GitHubのCVE関連リポジトリを自動スキャンし、各CVEに対するPoC・Exploitコードの存在を検出。NVD API v2からCVSS・CWE・ベンダー情報、CISA-KEVカタログから実環境での悪用確認状況、EPSSから悪用予測確率をそれぞれ取得し、���別のJSONファイルに集約する構成

・GitHub-Actionsで6時間ごとに自動実行され、出力はすべてGitHub-Pages上にデプロイされる完全静的サイト方式。有料インフラ不要

・ダッシュボードはCVE種別（PoC/Exploit/General）、深刻度（Critical/High/Medium/Low/Unscored）、KEVステータス、EPSS帯域の4軸でフィルタリング可能。年別タイムラインとトレンドチャート、ライブ活動フィードにより脆弱性の推移も把握できる構成

・セキュリティニュースのRSSフィードを1時間ごとに取得するnews_scraperも同梱されており、CVE情報と関連ニュースを並行して参照可能

詳細は以下を参照：
https://t.co/FjIJyG0qzw

[Prof. Eliot Jacobson @EliotJacobson]

How much does normalcy bias affect media reporting?

Here is a chart of global sea-surface temperatures (SSTs) from 1982 to 2026 with the years 2023, 2024 and 2025 omitted.

As of June 27th, global SSTs have set 26 daily record highs in a row.

Media? Is there anybody out there?

[David Miller @Tracking_Power]

Microsoft whistleblower on the firms deep integration into the Zionist genocide:

After nearly two years as a Critical Environment Technician at a Microsoft Italy data center, I choose to resign. This is because, right now, Microsoft is massively expanding its European data centers (aka mass surveillance centers) to use Palestine as a laboratory for its experimental digital weaponry. For the past 994 days, Microsoft has powered the genocide of our people in Palestine, and the company’s European data centers are fundamental to how Microsoft abets crimes against humanity.

On August 6, 2025, reports exposed how Microsoft hosted 11,500 terabytes of intercepted Palestinian phone call data in the Microsoft Netherlands data center, with additional data stored in the Irish data center, amounting to 200 million hours of audio. This trove of mass surveillance data has been described as “one of the world’s largest and most intrusive collections of surveillance data over a single population group.”
This data is used by the Israeli military to identify targets for airstrikes, arrests, and blackmail from the entire Palestinian population. It is also used as training data to build AI-targeting programs. These programs invent arbitrary justifications to murder non-combatants, intentionally adding civilian workers to the Israeli military’s generated “target bank“; the programs also facilitate massacres of entire families at once.

[Melanie D'Arrigo @DarrigoMelanie]

The top 50 mega-donors already spent over $1.3B on the midterms.

Only 20% of that is for supporting Dems.

9 of the top 10 mega-donors are supporting Republicans.

Last cycle, Elon Musk alone spent $290M supporting Trump and Republicans.

But you wouldn’t know that by reading the Republican-billionaire-owned NY Post.

This is what a system rigged for fascism, backed by propaganda, looks like.

How much billionaires spend in an election isn’t a conversation that should be had in a Democracy — it’s time to overturn Citizens United.

[Abdul Mhanni @abdo_mhanni]

Really great blog by https://t.co/71ygpkXIsE on baselining Windows to understand what’s normal for stealthier operations and not standing out during engagements https://t.co/QpLmVO9flp