#Blockchain #BlockSec #OSINT #CyberSec #Darkweb | Isaiah 54:17 Fingerpint: 54EADD6FCBCF520E37A003E04D3ECE027AEFA381
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James Edwards retweeted
China published the most uncomfortable paper on vibe coding.
ETH Zurich tested 100 developers in a controlled, commercial-grade vibe coding environment to see who actually succeeds.
The findings are brutal.
The researchers tracked computer science achievement, written communication skills, and general cognitive reasoning.
They wanted to see what actually predicts vibe coding proficiency when you never touch a line of source code yourself.
Two major predictors emerged.
Written communication proficiency mattered. The ability to structure thoughts and articulate intent unambiguously in text directly impacts what the AI builds.
But that wasn't even the main takeaway.
Computer science achievement was a massive, dominant predictor of success.
Even when researchers controlled for general intelligence and reasoning skills, CS background still heavily dictated who built working software and who completely crashed.
In fact, CS knowledge contributed roughly twice the unique predictive variance of writing skills alone.
Why? Because vibe coding isn't about writing code. It’s about debugging logic.
When an AI agent builds a complex application and quietly breaks an edge case under the hood, a non-technical user looks at the glowing UI and assumes it works.
They don't know what questions to ask. They don't know what logic to challenge. They lack the mental models to recognize architectural catastrophe.
You can prompt your way past syntax.
You cannot prompt your way past a fundamental lack of engineering intuition.
The hype told us that learning to code is dead because language is all you need.
The data just proved the opposite.
To truly master the vibe, you still need to understand how the machine thinks.
No coincidence that we see Claude Code has the highest cost per successful task relative to competing open source harness alternatives. These harnesses are designed to trigger thought loops & task executions that use more tokens that necessary to inflate costs for profit.
This is a common sense solution - no offense. And also one where several apps have already been created for the specific purpose of tracking Bluetooth broadcasts, device names and estimating proximity based on signal strength relative to device.
Lost my phone at the office and spent 30 minutes turning the place over. Find My was disabled by MDM.
Out of ideas, I asked Claude how I could find it. It suggested tracking the Bluetooth signal strength, then wrote me a meter in about a minute.
I walked around watching the number climb. Found it.
Apparently you can just make the tool you need now.
Code: github.com/ben-z/findphone
What actual proof is there that any of this happened? Seems mighty convenient to make the blanket accusation that Anthropic's IP was stolen just 4 days after this model was released w open weights, crushing benchmarks. How convenient for OpenAI and Anthropic #anticompetition
We have information that Moonshot AI distilled Anthropic’s Fable for the development of its K3 model.
To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of access to avoid detection. Moonshot AI has also acquired GB300-equipped servers and has accessed GB300s in Thailand, likely to train its AI models.
The United States strongly supports the free and fair development of AI, including a thriving competitive ecosystem that spans frontier models, specialized systems, open-source frameworks, and open-weight models. Legitimate AI distillation used to create smaller, more efficient models plays a vital role in this open innovation ecosystem. However, large-scale, covert industrial distillation aimed at stealing proprietary U.S. technology and undermining American research is unacceptable.
So folk are just gonna use AI for everything? We aren't even typing our own posts anymore?
🚨 CYBER INTELLIGENCE ALERT: 🇺🇸 [UNCONFIRMED / POSSIBLE PUBLIC DATA COLLECTION] CLAIM OF INFRASTRUCTURE BREACH AND EXTORTION — FBI (CRIME DATA EXPLORER)
[STATUS: UNCONFIRMED / EXTORTION / POSSIBLE API SCRAPING]
A post has been detected on underground forums where the threat actor calling himself "Orcinus orca" claims to have compromised the internal infrastructure of the United States Federal Bureau of Investigation (FBI). The actor has released a 5GB sample and is demanding a ransom of 50 BTC under the threat of leaking the agency's complete source code and private repositories.
[STATUS: UNCONFIRMED / EXTORTION / POSSIBLE API SCRAPING] Threat Actor: Orcinus orca
Stated Target: FBI infrastructure and the api.usa.gov / cde.ucr.cjis.gov portals.
📂 Technical Analysis and Veracity of the Evidence (Indicators of Exaggeration / Scraping)
Despite the actor's aggressive claims of having "2 years" persistence and control over private GitHub repositories and "crime prediction models," the technical analysis of the provided evidence strongly suggests that this is a massive collection of public data (API scraping) disguised as a critical hack:
Nature of the API Key: The actor provides an API key (API_KEY=[REDACTED]) as "proof of access" and details how to extract it. However, their own curl command demonstrates that this key is obtained directly by reading the JavaScript source code (main.[hash].js) of the FBI's public CDE (Crime Data Explorer) portal frontend. This is a public key used by the web application to query api.usa. gov, not a credential for accessing internal or administrative infrastructure (backend).
Exposed Data (Open Data): All datasets listed by the attacker as "stolen" (LEOKA – Officer Assaults, Police Employment, and national/state-level Hate Crimes) are, in fact, public databases that the FBI makes available to citizens and researchers precisely through that API.
False Proof of Concept (PoC): The request in Burp Repeater shown by the attacker returns an HTTP 200 OK response containing hate crime data from 2020. This is the normal, documented behavior of the U.S. government's public data transparency portal, not evidence of an intrusion.
⚠️ Risk and Actual Impact Considerations
Infrastructure Risk (Low): Based on technical evidence, the FBI has not suffered a breach of its server infrastructure or its classified network. The actor simply automated the download of thousands of JSON files using the public frontend.
Psychological Warfare / Reputation: Incidents of this type—common on the Dark Web—aim to generate media panic or deceive less technically skilled cybercriminals into purchasing databases that are actually in the public domain.
🛡️ Recommended Actions (Tactical and Investigative Level)
Incident Classification: Log this event in the intelligence platform as "False Breach / Public API Abuse," avoiding the escalation of unnecessary critical alerts regarding a government compromise.
Key Management (Recommendation for Third Parties): Although the FBI portal uses the API key publicly by design (to support its Single Page Application), it is recommended to implement periodic key rotation, strict HTTP origin controls (CORS), and IP-based rate limiting to mitigate automated data extraction and server overload.
VECERT TOOLS
Strategic Monitoring Tools & Intelligence Platform:
🌐 analyzer.vecert.io
Security Verification & Monitoring:
🛡️ monitor.vecert.io
#CyberSecurity 🔐 #ThreatIntelligence 📊 #FakeBreach 🚫 #APIScraping #FBI #Visa 💳 #VECERT 🏢
James Edwards retweeted
JUST IN: 🇺🇸 US government orders Anthropic to suspend foreign access to Mythos Fable 5 AI model, citing national security concerns.
Anthropic has disabled access for all users worldwide.
James Edwards retweeted
As a result of a US government directive, we are suspending access to Claude Fable 5 for all users. You can continue to use all other Claude models.
Here’s what this means for you:
Across Claude products, new sessions will run on your selected default model or Opus 4.8, and existing Fable 5 sessions will end with an error.
On the Claude Platform, requests to Fable 5 will also return an error. Please update your integrations to other Claude models.
We know this is a disruption to your workflows; we appreciate your patience and support.
The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees.
The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance.
Access to all other Claude models is not affected.
We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible.
Read our full statement: anthropic.com/news/fable-myt…
How do I refine my algorithm on this site so it doesn't show me low effort, noisy shit like this?
A guy in Karachi rebuilt GPT-4 in one Jupyter notebook.
OpenAI spent over $100 million to train the real one. He put the entire recipe on GitHub for free.
His README still says "I am looking for a PhD position in AI."
It's called Train LLM From Scratch. A working guide that walks you through building your own 2-billion-parameter language model on a single GPU.
OpenAI vs this repo:
- Training cost: $100M+ → Single A100 or RTX 4090 (you can rent for $1/hr)
- Code access: Closed → Open, MIT license
- Data: Secret → The Pile (open dataset, 825GB)
- Walkthrough: None → Every line of code explained, top to bottom
- Output quality: GPT-4 → A small model that writes broken English (but it's yours)
The whole thing fits in one notebook. No paid course. No paywall. No "Pro" tier.
What you actually learn:
→ How a transformer works, end to end
→ How to download and tokenize the Pile dataset
→ How to build multi-head attention from scratch in PyTorch
→ How to train on a single GPU without running out of memory
→ How to generate text from your trained model
→ How to scale from 13 million parameters to 2 billion
774 stars. 135 forks. MIT license. The full theory paper-to-code in one place.
One honest note: this is a learning repo, not a production model. Your output will be small and rough. But you will understand exactly how GPT-4 works after reading it.
Fareed Khan built this from Karachi, Pakistan. He has 1,780 GitHub followers. He's still looking for a PhD position. The recipe to billion-dollar AI is sitting on his profile, free.
This is what open AI was supposed to mean.
(Link in the comments)
James Edwards retweeted
That cheap Claude API is stealing everything on your machine.
Chinese "transfer stations" sell Claude at 70-90% off.
The trick: "One Fish, Three Meals"
- Split corporate accounts across users
- Sell "premium" while routing to cheaper models
- Record every prompt to train domestic AI
That third part is the danger.
With a chatbot, they get your conversation.
With Claude Code, they get your repo, credentials, architecture, and customer data.
- Route an agent through an unverified proxy and you're handing a stranger your entire data stream.
- Could they inject malicious instructions?
- Scan for `.env` files?
- Harvest AWS credentials?
That's the real question.
90% savings isn't a bargain if it costs your code, prompts, security and infrastructure.
Use AI aggressively.
Just don't plug agentic tools into shady endpoints because they're cheap.
By the way that's one of the reasons why Claude is asking for KYC and making so much mess to real consumers now.
James Edwards retweeted
He gets to keep his inheritance but people want us to abandon reparations to ensure we never receive ours.
Nope.
James Edwards retweeted
brother wtf is bitcoin style encryption, bitcoin literally doesn’t have any encryption in it whatsoever
James Edwards retweeted
🚨 URGENT: We have detected a potential frontend attack targeting @CurveFinance . If you're connected, please refrain from signing transactions and avoid interactions with the dApp until the issue is resolved. We’re working closely with affected partners. More updates soon.
Wow that's profound. Wtf?
Seems like curve.fi DNS might be hijacked. Don't interact!
