🔴 Hacktron hacks OpenAI with Claude for $3,000 🔴
A small team used Claude to breach OpenAI's systems at unprecedented speed.

Security startup Hacktron AI disclosed that a three-person team infiltrated OpenAI's infrastructure in under 72 hours on July 25, using Anthropic's Claude Opus 4.8 and Opus 5 to handle a meaningful share of the exploit work. The team exploited a year-old bug in HEIC/HEIF image processing on community.openai.com, gaining remote code execution and discovering that forum session tokens also granted access to ChatGPT and Codex — including staff accounts connected to GitHub. No code was stolen; everything was responsibly reported, earning a $6,500 bug bounty. OpenAI patched the SSO vulnerability in roughly 14 hours. The full operation cost under $3,000 in tokens, underscoring how AI tools are slashing the cost and timeline of real-world exploits.

🧮 OpenAI claims to solve Navier-Stokes and 100+ math problems 🧮
A new OpenAI model tackles unsolved mathematics, raising questions about the speed of AI-driven discovery.

OpenAI announced that a new internal model has solved the Navier-Stokes Millennium Prize problem along with over 100 open mathematical challenges — a potentially historic milestone in AI-driven research. In response, the company established an independent advisory group of prominent mathematicians to guide the responsible development and dissemination of these capabilities. The group will independently assess advances and advise on how results are communicated to the broader research community. This represents a capability jump that could reshape mathematical research, as frontier AI models move beyond benchmarks into genuine contributions to unsolved fundamental science. The development also raises critical questions about verification, peer review, and the evolving role of AI in mathematical proof — territory where scientific credibility is at stake.

🛒 Amazon blocks Meta's Muse over security fears 🛒
Amazon walls off agentic shopping to protect its $68 billion ad business from AI-driven replacement.

Amazon has blocked Meta's Muse personal AI agent from shopping on its platform, alleging the agent browses without identifying itself and may store customer login credentials. Meta disputes the claims, stating Muse cannot view passwords or payment details. The standoff reflects a deeper strategic battle: Amazon's $68 billion advertising business depends on real human shoppers who click ads, and AI agents bypass that model entirely — this directly threatens Amazon's core ad revenue stream. Over the past year, Amazon has systematically blocked outside agents, including suing Perplexity over its Comet agent and moving to restrict shopping agents from Google and OpenAI. This is a defining clash over who controls the emerging agentic commerce layer.

INTERESTING TO KNOW

⚡ xAI ships Grok 4.7 at $2 per million tokens ⚡

xAI has released Grok 4.7, a new frontier model built on a larger base architecture with significantly improved coding, knowledge work, and agentic capabilities. The model features enhanced self-verification and built-in safeguards, allowing it to work longer on complex tasks, check its own outputs, and produce higher-quality documents. Priced at $2 per million input tokens and $6 per million output tokens, Grok 4.7 is available through Grok Build, Cursor, and the xAI API. On Artificial Analysis' Intelligence Index, it scores 46, placing it among top-tier models — adding serious competitive pressure on OpenAI and Anthropic in the developer-facing market.

🧬 Anthropic opens wet lab for Claude-run experiments 🧬

Anthropic is now operating a physical biology laboratory in the San Francisco Bay Area, marking its integration of AI software with hands-on scientific experimentation. The company aims to have Claude steer lab robots through experiments with minimal human oversight, building on the recently introduced Model Hardware Standard for controlling microscopes and robotic arms. Anthropic has also open-sourced Claude-generated code that accelerated over 30 biomolecular simulation models in a single month — a concrete step toward AI-driven drug discovery that few competitors can match.