

Shane 🇺🇸 ㈯
742 posts

@Shane0xM
Building @GreenfieldLabs // OSS AI · Agentic Coding · Applied AI · Enterprise



🚨Data Breach Alert ‼️ 𝗧𝗲𝗮𝗺𝗣𝗖𝗣 𝗖𝗹𝗮𝗶𝗺𝘀 𝗦𝗮𝗹𝗲 𝗼𝗳 𝗚𝗶𝘁𝗛𝘂𝗯 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝗹 𝗦𝗼𝘂𝗿𝗰𝗲 𝗖𝗼𝗱𝗲 TeamPCP hacking group claimed the compromise and sale of GitHub internal data, allegedly including around 4,000 private repositories containing source code related to GitHub’s main platform and internal organizations. Threat actor: TeamPCP Sector: ICT Data exposure (claimed): Approximately 4,000 private repositories Data type: Source code Observed: May 19, 2026 Status: Pending verification ESIX©: 7.96 Full details and impact assessment on HackRisk.io



Yesterday @coinbase experienced a multi-hour service disruption affecting trading, exchange access, and balance updates. Here's our initial read from Coinbase engineering on what happened, how we recovered, and what we're addressing. At approximately 23:50 UTC on 2026-05-07, our monitoring detected cascading quote failures from internal services that triggered multiple Sev1 incidents that engineering immediately began investigating. Customer-facing impacts included spot trading, Prime, International and derivative exchanges. Root cause: a thermal event (cooling system failure) inside a subset of racks within a single building in AWS us-east-1. We run a primary replica of our exchange infrastructure in a single zone, consistent with industry standards to reduce latency. To prepare for failures like this, we maintain a distributed standby, but during this incident, failures in the primary zone that were designed to be isolated were not, extending the duration of our outage. The failure cascaded down two paths: 1. Multiple hardware components beneath our exchange’s matching engine failed, requiring recovery and failover 2. Distributed Kafka clusters that manage messaging across Coinbase systems failed to remain available, also requiring partition failovers to new hardware brokers with many TiBs of data After isolating the incident: automated tooling drained ~10 Kubernetes clusters worth of related workloads out of the affected zone to stabilize internal services. Most services were back to normal within ~30 minutes of diagnosis. The two things we couldn't automatically drain: the exchange (dedicated hardware and storage) and Kafka (managed service that was designed to be resilient to this, with unique problems). The exchange matching engine is the core system responsible for processing orders and maintaining order books. It is a distributed cluster and requires quorum to safely elect a leader and continue processing trading activity. During the incident, infrastructure-level constraints in the affected datacenter left only a subset of nodes healthy, preventing the cluster from reaching quorum. As a result, trading across Retail, Advanced, and Institutional exchanges were blocked. Recovery required our oncall and engineering teams to execute our disaster recovery plan, restore quorum safely, and validate system health under constrained infrastructure conditions. The team built, tested, deployed, and validated the fix while continuing to manage the broader incident. Kafka recovery was a much larger scale operation. Our primary managed Kafka partitions process many terabytes of data daily and are designed with resiliency guarantees for uninterrupted operation during a datacenter failure just like this. In this case, those guarantees failed and required manual recovery. We again relied on disaster recovery procedures to recover stuck partitions onto new hardware (brokers) that enabled us to safely bring x-service messaging back online across Coinbase. During the lag, customers saw delayed balance streams which resolved automatically once replication caught up. No data lost. Once the engine came back up as part of our standard runbooks, we re-opened markets carefully: all products to cancel-only mode first, audited product states, then moved all markets to auction mode, before restoring trading on Coinbase Exchange. What went right: the team. Incident response across the company came together within minutes, followed well-rehearsed playbooks and used secure automation tooling to recover all services. We have a strong, senior team at Coinbase that worked through rare failure modes to recover all services. To our customers: losing access to your account, even temporarily, is unacceptable. We know that. We're sorry, and we’ll publish a full root cause analysis in the coming weeks 🙏


@WorldClawAI is expanding access to AI and $WLFI plays a key role in the ecosystem. Users can access 300+ models with WorldRouter, and agents can facilitate payments in USD1 on @BNBCHAIN and @solana to support task execution. Locking $WLFI tokens can provide access to additional features and functionality related to the future of AI. Subject to applicable terms and conditions.


Introducing SubQ - a major breakthrough in LLM intelligence. It is the first model built on a fully sub-quadratic sparse-attention architecture (SSA), And the first frontier model with a 12 million token context window which is: - 52x faster than FlashAttention at 1MM tokens - Less than 5% the cost of Opus Transformer-based LLMs waste compute by processing every possible relationship between words (standard attention). Only a small fraction actually matter. @subquadratic finds and focuses only on the ones that do. That's nearly 1,000x less compute and a new way for LLMs to scale.

The Trump administration has informed Anthropic, Google and OpenAI that they are discussing the creation of new AI oversight procedures that would potentially require new AI models to pass a safety review before being cleared for release. Mythos has changed things.


Do you understand what just got open-sourced? A BLOOMBERG TERMINAL. FOR FREE. No $24,000 subscription. No API costs. 100% local on your machine. The data moat is real. The software moat is dead. That is the point. Bookmark this. Install it right now. Takes ten minutes.