#BrainUp Daily Tech News – (Friday, July 17ᵗʰ)
Welcome to today’s curated collection of interesting links and insights for 2026/07/17. Our Hand-picked, AI-optimized system has processed and summarized 22 articles from all over the internet to bring you the latest technology news.
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1. Microsoft Patches Record 570 Security Flaws in Single Update, Credits AI-Powered Discovery
Microsoft issued its largest-ever Patch Tuesday update, fixing a record 570 security vulnerabilities and attributing the spike to an AI-powered vulnerability discovery system scanning its Windows codebase. The release is far larger than prior cycles, up 316% from 137 flaws in July 2025 and up from 200 in June 2026, and includes 59 critical issues, with 48 enabling #RemoteCodeExecution across products such as Office, Exchange, and SQL Server. It also patches three zero-days, including two already exploited in the wild: CVE-2026-56155 in Active Directory Federation Services enabling authenticated privilege escalation, and CVE-2026-56164 in SharePoint Server enabling unauthorized remote privilege escalation, with mitigations including enabling #AMSI and setting Request Body Scan to Full, plus a publicly disclosed BitLocker bypass (CVE-2026-50661) requiring physical access. @Pavan Davuluri said advances in #AI are changing the pace of vulnerability discovery, reflecting how automation is accelerating both defensive bug finding and attacker exploitation timelines. Microsoft recommends enterprises install Windows 11 quality updates within three days, citing AI-driven cyberattacks that can weaponize newly found flaws faster than before.
2. OpenAI’s GPT-5.6 Sol Disproves 20-Year-Old Statistics Conjecture in 90 Minutes
University of Pennsylvania statistician Edgar Dobriban used OpenAI’s #GPT-5.6 Sol Pro to disprove a roughly 20-year-old conjecture claiming the #Benjamini-Hochberg (#BH) procedure controls #false discovery rate (#FDR) for correlated two-sided Gaussian tests regardless of correlation structure. In about 90 minutes, the model produced a counterexample, proof, and machine-checkable numerical certificate, while the predecessor #GPT-5.5 reportedly failed after more than 20 hours with multiple parallel agents. The counterexample uses a Gaussian factor model with three coordinate blocks and shows that at nominal level α = 0.01, the BH procedure can yield FDR exceeding 0.0104 for sufficiently large numbers of hypotheses, with Monte Carlo at N = 200 giving about 0.01036. Although the violation is small, it is rigorously certified using interval arithmetic via the Arb library, indicating the exceedance is not a numerical artifact. The result was posted as a July 13, 2026 arXiv preprint authored solely by Dobriban and explicitly acknowledging that #GPT-5.6 Pro obtained the proof, and @Will Fithian described the conjecture as a major open problem in his area.
3. TSMC Adds $100B Arizona Investment as Q2 Profit Surges 77% to Record $22B
Taiwan Semiconductor Manufacturing Company reported record Q2 net income of NT$706.6 billion ($22 billion), up 77.4% year over year, alongside a major expansion of its U.S. manufacturing footprint driven by #AI chip demand. Revenue reached $40.2 billion, gross margin rose to 67.7% and operating margin to 60.3%, while advanced nodes (7nm and below) delivered 77% of wafer revenue, including 3% from 2nm chips in their first full commercial quarter. CEO C.C. Wei announced an additional $100 billion for Arizona to add four new fabs and an advanced packaging facility, lifting total Arizona commitments to $265 billion, described as one of the largest foreign direct investments in U.S. history. TSMC also raised full-year 2026 revenue growth guidance to slightly above 40% (from over 30%) and increased capex to $60 to $64 billion, but its U.S.-listed shares fell about 4% pre-market as investors weighed higher spending and near-term margin pressure from the 2nm ramp. The results and investment plans reinforce TSMC’s central role in supplying leading-edge chips for customers such as @Nvidia, @Apple, and @AMD, while scaling #advanced packaging capacity critical for AI data center hardware.
4. Experts find attackers can exploit decades-old UEFI flaws to gain access to key systems
@ESET researchers found 11 vulnerable UEFI shim bootloaders signed by @Microsoft that could let attackers bypass #UEFI #SecureBoot and install malicious bootkits without needing any new vulnerability. The affected risk applies to UEFI systems that trust the Microsoft Corporation UEFI CA 2011 third-party certificate, with shim versions 0.9 and older, potentially impacting billions of devices because most modern x86 PCs trust that certificate by default. The shims were used across PC diagnostic tools, Linux distributions, and other UEFI utilities, and attackers could bring an old, still-trusted shim to systems that were not originally shipped with it to gain a Secure Boot bypass. @ESET reported the issue to CERT/CC and the vulnerable UEFI applications were revoked by @Microsoft, with guidance that users apply the latest UEFI revocations, Windows likely via automatic updates and Linux via #LVFS, to block exploitation. The core problem is longstanding trust in unrevoked shim binaries, meaning basic shim knowledge and an old trusted binary can defeat an essential security control.
China has become the first to commercially implant a brain-computer interface (#BCI), awarding a car crash victim a coin-sized chip that translates neural signals into hand movements. This breakthrough demonstrates a significant practical advancement over @Elon Musk’s Neuralink, which had been anticipated to pioneer such technology but has not yet achieved commercial implantation. The chip’s ability to restore motor function in patients highlights the potential of #neurotechnology to transform rehabilitation for paralysis and neurological injuries. This innovation underscores China’s leading role in pushing the boundaries of applied brain-computer interfaces while emphasizing the pressing benefits for patients in need of assistive neural devices.
6. Apple Intelligence Wins China Regulatory Approval With Alibaba’s Qwen AI
China’s Cyberspace Administration (#CAC) approved #AppleIntelligence for deployment as one of seven registered on-device #generativeAI services for smartphones, clearing a major regulatory hurdle for @Apple in its second-largest market. The China version will use @Alibaba’s #Qwen model across iOS, iPadOS, macOS, and visionOS for on-device text and image processing, content generation, writing tools, text summarization, image generation, and an upgraded Siri, with @Baidu also involved in an unspecified capacity. The approval follows Apple China’s July 8 filing and ends a roughly 22-month wait that began after the iPhone 16 launch in September 2024, when availability in mainland China was conditioned on regulatory clearance, after Apple explored partnerships with multiple Chinese AI firms before selecting Alibaba as the primary model provider. For on-device use, Qwen was compressed from 54 GB to under 4 GB to run locally on devices as old as the iPhone 15, while no launch date was disclosed, meaning approval does not guarantee an immediate rollout. The news lifted markets and underscores strategic stakes in China, with Apple shares up 4% to $327.50 (a 52-week high) and Alibaba up 4.8%, as Apple held 18.1% of China’s smartphone market in Q2 2026 with shipments rising over 20% year over year.
7. SK Hynix Plunges 11.5% as Semiconductor Selloff Triggers KOSPI Sidecar, Drags Global Chip Stocks
A sharp #semiconductor selloff hit South Korea and spread globally, led by an 11.53% plunge in SK Hynix that helped drive the KOSPI down 6.37% and triggered a sell-side #KOSPI sidecar after KOSPI 200 futures fell more than 5%. SK Hynix fell to 1.823 million won in Seoul and its Nasdaq-listed ADRs dropped 9% to $176.46, while other chip names also slid, including Samsung Electronics (-8.8%) in Seoul, @Micron Technology (-8%) in the U.S., and Japan’s Advantest (-6%) and Tokyo Electron (-5%). The article attributes the move primarily to profit-taking after a rapid post-listing run, noting SK Hynix ADRs jumped from a $149 offering price to as high as $194.80 in three sessions, and the selloff came less than a week after its $26.5 billion Nasdaq ADR listing, described as the largest U.S. share sale by a foreign company. Additional pressures cited include a proposed New York state data-center construction moratorium, reports that CoreWeave was exploring hedges against future memory-price declines, and rising Middle East tensions, alongside concerns about market concentration, with one strategist saying semiconductors are about 20% of the S&P 500. The episode links South Korea’s outsized index drop to heavy semiconductor weighting and large flows, with foreigners and institutions net selling on the KOSPI while retail investors were net buyers.
8. SpaceXAI’s Grok programming tool was uploading its users’ entire codebase to cloud storage
SpaceXAI’s Grok Build #AI coding tool was found to be packaging and uploading users’ entire code repositories to #GoogleCloud, and the company has since disabled the behavior. According to The Register and findings published by Cereblab, the Grok Build CLI uploaded more than comparable tools like #ClaudeCode, including files it was told not to open and even secrets deleted from history, and later tests showed a “disable_codebase_upload: true” flag with uploads no longer firing. @ElonMusk said on X that all previously uploaded data would be “completely and utterly deleted,” while also claiming privacy settings are respected and asking users to allow data retention for debugging. Independent security researcher Dr. Lukasz Olejnik told The Verge the retention was “excessive” and could put proprietary code, vulnerability information, personal data, infrastructure details, and credentials at risk. SpaceXAI pointed to a /privacy CLI command for disabling retention and deleting synced data, but Cereblab argued it is only a per-session toggle and not the control that fixed the repository uploads.
9. Hack Exposes Suno AI Scraped Over 2 Million Songs From YouTube, Deezer, and Genius
A November 2025 breach of AI music startup Suno exposed internal source code that details large-scale scraping of music and audio used to train its #generativeAI models, providing technical evidence of data sources the company had not publicly disclosed. Leaked dataset docs spanning 2023 to 2024 show ingestion of 2,013,545 YouTube Music clips and over 380,000 total hours of audio across nine platforms, including YouTube Music, Deezer, Genius, Pond5, IMSLP, Jamendo, Freesound, and MuseScore Lyrics, plus references to scraping podcasts via RSS and YouTube acapella, sometimes using proxies and filters to exclude non-music content. The hacker, “ellie.191,” reportedly used a supply-chain worm called “Shai-Hulud” to compromise a Suno employee and obtain GitHub and cloud credentials, also exposing user data for hundreds of thousands of customers such as emails, phone numbers, and Stripe payment information, while Suno said it does not store full card numbers. Suno said the breach was quickly contained, claimed the exposed code was outdated and no longer in use, and maintained its scraping is fair use. The disclosure comes amid ongoing federal copyright litigation by @Universal Music Group and @Sony Music, with a hearing scheduled for July 2026, while @Warner Music had settled in November 2025 in exchange for a licensing deal.
10. Russian hacker turns Gemini CLI into a hacking agent, creates small-scale botnet
Cybersecurity researchers say a Russian-speaking threat actor, “bandcampro”, used Google’s #Gemini CLI as a conversational #hacking agent to run a small, eight-device botnet targeting a dental clinic. Trend Micro analyzed about 200 session logs from April 21 to May 19, 2026, and found the attacker claimed to be an “authorized pen tester” to get the AI to help with tasks such as migrating #C2 infrastructure, troubleshooting connectivity, and assembling payload bundles, with the AI refusing at least one request. The logs show the attacker supplied a skill file describing architecture, SOPs, infection and persistence commands, and troubleshooting steps, and the AI reportedly prepared a migration bundle, launched a C&C server on a VPS, and set up a Cloudflare tunnel in about six minutes. Researchers also observed use of the AI for day-to-day operations like password guessing and generating plausible password variants for WordPress portals, while the attacker sought access to the clinic’s OpenDental database. The case highlights how legitimate #AI developer tools can be co-opted by threat actors when prompted with false authorization claims.
11. Meet GPT-Red, an LLM super hacker OpenAI built to make its models safer
OpenAI developed GPT-Red, a specialized large language model designed to test and strengthen the safety of its AI systems by hacking them from the inside. By simulating adversarial attacks, GPT-Red identifies vulnerabilities and helps developers patch potential exploits before malicious actors can exploit them. This approach reflects a proactive defense strategy, leveraging AI’s capabilities to improve AI safety, echoing cybersecurity practices in traditional software development. GPT-Red’s integration into OpenAI’s security processes highlights a shift toward using advanced AI tools internally for robust protection. This innovation marks a critical step in safeguarding AI models against misuse and ensuring more reliable deployments.
@Satya Nadella warns that companies using proprietary #AI models may effectively pay twice, first in money and then by surrendering valuable proprietary knowledge needed to make models perform well. He argues model providers learn from customer “exhaust” such as prompts, tools, and especially user corrections, which can be distilled into institutional know how and then used to build stronger models that could advantage a customer’s competitors. Nadella also calls out what he sees as a contradiction: some AI firms claim fair use to train on public data while imposing restrictive anti distillation terms, even as contracts often reserve the right to learn from customer interaction data. As a remedy, he advocates a return to #on-prem style deployments via “proprietary learning environments” built on the cloud, so businesses retain ownership of data while using orchestration layers and AI gateways to switch among different vendors’ models. He links this approach to a broader move toward #open-source technologies alongside cloud operations to reduce lock in and protect business secrets.
13. Claude Chrome extension flaw lets malicious extensions trigger AI actions
A flaw in @Anthropic’s Claude for Chrome extension could let a malicious Chrome extension trigger Claude’s predefined #AI workflows by simulating clicks, potentially abusing Claude’s access to connected services like #Gmail, #GoogleDocs, #GoogleCalendar, and #Salesforce. Manifold Security researcher Ax Sharma reports the extension listens for click events on a specific element to launch built-in tasks, but fails to verify the event is a real user interaction by checking Event.isTrusted, so JavaScript-generated, untrusted clicks can still execute workflows. An attacker would need to trick a user into installing a malicious extension with permission to run on the claude.ai domain, then inject a page element with one of nine supported task identifiers and fire a synthetic click to run actions such as unsubscribing from emails, reading Google Doc comments, creating calendar meetings, or modifying Salesforce leads. The issue does not enable arbitrary prompt injection and is limited to the extension’s predefined tasks, but it can effectively piggyback on Claude’s authenticated integrations, with impact depending on configuration and whether the optional “Act without asking” setting is enabled. The article notes a second finding involving an internal ‘skipPermiss’ feature, but the provided text is incomplete and does not describe it further.
14. Moonshot’s upcoming Kimi 3 is expected to close the gap with Anthropic’s Opus 4.8 | TechCrunch
@Moonshot AI is preparing to release Kimi K3, an open-weight model that @Financial Times sources say could match or surpass @Anthropic’s Opus 4.8 and further narrow the gap with closed models from @OpenAI and @Anthropic. The report says Kimi K3 could be the largest open model from China, with 2 trillion to 3 trillion parameters, and may ship in the coming days, building on Kimi K2’s strong benchmark performance in the #open-source AI market. Alongside the product push, Moonshot is reportedly raising new funding at a $31.5 billion valuation after raising $2 billion in May at a $20 billion valuation. The timing aligns with growing scrutiny of paying for expensive #closed-source models and concerns that client data submitted to tools like ChatGPT and Claude could be extracted for other uses. The article links Kimi K3’s rise to a broader industry shift toward cheaper #open models from labs such as DeepSeek, Z.ai, and Moonshot that companies can fine-tune for their own needs.
15. Microsoft nemesis returns with another zero-day PoC, but is ‘LegacyHive’ as nasty as expected?
@Chaotic Eclipse has released another Windows 11 #zero-day called #LegacyHive, described as a #localPrivilegeEscalation flaw that targets Windows user registry hives. The issue could theoretically give an attacker privileged read-write access to other users’ hives, allowing a low-privileged account to be elevated, but it requires the attacker to already have some access to the device. Unlike some earlier releases attributed to the researcher, this disclosure did not include a CVE identifier or a fully functioning proof of concept, and some researchers view it as less disastrous than prior exploits. Even so, experts warn that skilled threat actors could quickly weaponize the technique, so intelligence teams should move fast to prepare mitigations. The report frames the release within an ongoing dispute in which @Microsoft previously criticized the researcher for not responsibly disclosing flaws and had floated legal action before backing away after public backlash.
16. How AI could unleash a flood of zero-day vulnerabilities
AI advancements are accelerating the discovery of zero-day vulnerabilities, which are previously unknown security flaws that hackers can exploit. Researchers and cybersecurity experts warn that AI tools can automatically generate exploits faster than traditional methods, increasing the risk and scale of cyberattacks. This rapid identification challenges existing defenses, as organizations struggle to patch vulnerabilities before they are widely exploited. The evolving AI-driven threat landscape demands new approaches and investments in cybersecurity to mitigate potential damages. Understanding and addressing this challenge is crucial for maintaining digital security in an AI-powered future.
17. Here’s Why Anthropic Is Pushing States to Regulate AI Faster
Anthropic is urging US states to move beyond early #AI transparency rules and adopt tougher oversight for #frontierAI, arguing that rapid advances have already made last year’s measures insufficient. Its state policy lead Cesar Fernandez says #transparency and #selfReporting are no longer adequate safeguards for the most powerful systems, even though Anthropic supported landmark transparency requirements in California and New York that other Silicon Valley firms opposed. The company has also backed proposals like Illinois and Massachusetts measures requiring #thirdPartyAuditing of AI labs, with the Massachusetts plan additionally empowering the state attorney general to seek injunctive relief for noncompliance. Critics such as @DavidSacks frame this as #regulatoryCapture meant to burden smaller startups, but Fernandez rejects that claim, saying the bills Anthropic supports target “large AI model developers,” generally companies spending hundreds of millions on AI and exceeding $500 million in annual revenue. With Congress stalled on AI regulation, Anthropic is positioning state-led rules as the next step in managing catastrophic-risk concerns while insisting the scope is aimed at the biggest labs.
18. Roblox will let people use AI to make games on their phone
Roblox is adding a mobile feature called #Build that lets people use #AI inside the Roblox app to turn text prompts into a basic game, expanding the company’s broader push into AI for game creation. According to Roblox, Build can generate gameplay mechanics, environments, characters, visual style, sound, and more, using a mix of Roblox’s own AI models and open-source models, and it follows earlier efforts like an AI foundation model for generating 3D assets and an AI assistant chatbot for developers. The company argues that lower barriers to making games will not flood discovery with low-quality content because experiences are ranked by retention-based criteria, and it says its discovery systems are meant to avoid “AI slop” by not surfacing games nobody plays. Build launches July 28 in public alpha in New Zealand for users 9+ with verified ages, while games published with Build will be playable globally by users 16+, with a free base version and unspecified paid options for power users. Roblox also plans new #AI agents for both Build and Roblox Studio, including playtesting, analytics, and experimentation agents aimed at improving engagement, retention, and monetization, arriving over the coming months.
19. Meta faces discrimination lawsuit over AI use in mass layoffs
A new federal lawsuit alleges @Meta used internal #AI tools in its May layoffs to disproportionately target employees with disabilities or those on protected medical or family leave. The complaint says the company relied less on manager judgment and more on a “constellation of internal artificial-intelligence systems,” including “Metamate,” employee-trained “second-brain” agents, keystroke data, AI token-usage dashboards, and performance ranking and calibration, which allegedly penalized workers for time away. Plaintiffs claim leave was treated as disengagement, lowering dashboard scores and skewing selections for termination, and the suit asserts the scoring failed to account for protected leave while effectively punishing employees for exercising legal rights. The case, filed in federal court in Oakland, includes 26 current and former employees across multiple states and cites examples such as a worker selected while on approved pre-birth leave and a manager allegedly warning medical leave would lead to termination. The allegations tie @Meta’s roughly 10% workforce reduction, nearly 8,000 employees, to #AI-driven evaluation methods that plaintiffs say produced discriminatory outcomes.
20. Tiny gene variations reduce cadmium in rice without affecting yields
Researchers have discovered that small variations in a specific gene can significantly reduce cadmium accumulation in rice grains without compromising crop yields. Cadmium is a toxic heavy metal that poses health risks when ingested through food, making this finding important for food safety. The study identified natural genetic differences affecting the function of a transporter protein involved in cadmium uptake and distribution within the plant. By selecting for these beneficial gene variants, it is possible to breed rice varieties that maintain productivity while minimizing cadmium levels. This approach offers a promising solution for addressing heavy metal contamination in rice cultivation and enhancing public health.
21. Google’s AI Mode now lets you link and interact with select apps | TechCrunch
Google is expanding its conversational search experience, #AI Mode, so users can link and interact with select third-party apps to complete tasks, not just get answers. At launch in the U.S., supported apps include Instacart, Canva, and YouTube, with examples like generating a barbecue grocery list and adding items directly to an Instacart cart, browsing Canva templates for a flyer, or curating a party playlist and saving it to YouTube Music. Google positions the rollout as a way to make AI Mode more useful for planning and shopping and to compete more directly with @OpenAI’s ChatGPT and @Anthropic’s Claude, which also support app integrations. The announcement builds on earlier work connecting third-party apps to the Gemini app and follows other AI Mode additions such as local stock checking, side-by-side web exploration with contextual follow-ups, and “#Personal Intelligence” that can use Gmail and Google Photos for more individualized responses. Google says it is working with more partners and plans to add support for additional apps soon.
Thinking Machines, the U.S. startup founded by former @OpenAI CTO @Mira Murati, released Inkling, its first major open-weights, natively multimodal #Mixture-of-Experts model aimed at enterprises that want customizable, controllable deployments on premises or in private clouds. Licensed under #Apache-2.0 and distributed via #HuggingFace and the company’s Tinker API, Inkling totals 975B parameters with 41B active, supports text, images, and audio, and emphasizes low cost via a “controllable thinking effort” mechanism plus a preview of the lower-latency Inkling-Small at 276B parameters. On third-party benchmarks it posts strong but not frontier-leading results, including 77.6% on SWE-bench Verified (ahead of Nvidia Nemotron 3’s 71.9%) and 91.4% on VoiceBench (below Gemini 3.1 Pro’s 94.4). The company also positions Inkling as “resistant to censorship,” intending to answer directly on sensitive topics for enterprises prioritizing factual outputs. In a competitive 2026 open-weight landscape, it is framed as a broad generalist, while models like GLM 5.2, DeepSeek V4 Pro, and Kimi K2.6 often outperform it on various coding, reasoning, and factuality benchmarks, though Inkling leads DeepSeek slightly on AIME 2026 math (97.1% vs. 96.7).
That’s all for today’s digest for 2026/07/17! We picked, and processed 22 Articles. Stay tuned for tomorrow’s collection of insights and discoveries.
Thanks, Patricia Zougheib and Dr Badawi, for curating the links
See you in the next one! 🚀
