IBM expects that its consulting infrastructure, added to OpenAI’s frontier AI models, will help business clients uncover security issues faster. According to an IBM news release, the service provides AI analysis that extends beyond typical scanning solutions for organizations with huge codebases. The new offering runs inside client environments with read-only access to code repositories. It analyzes application code, flags areas with potential flaws, and identifies exploitable paths. Organizations can start with targeted evaluations of individual applications and scale up to continuous monitoring as their code evolves.

IBM teams up with OpenAI to release new AI security tools

IBM Consulting Advantage, the company’s AI platform for delivering consulting engagements, powers the security service. “Attackers are already using AI to probe, exploit, and scale threats at machine speed. Defenders need the same advantage, with the security and control enterprises require,” said Mark Hughes, IBM Consulting’s global managing partner for cybersecurity services.

In the official press release, Dane Stuckey, OpenAI’s chief information security officer, said the company is collaborating with AI pioneers like IBM to use frontier models to accelerate defensive security workflows and support enterprises, governments, and other organizations as they identify risks. The application security service builds on Project Lightwell, an initiative IBM launched last month to secure open source software used across enterprise supply chains.

IBM and Red Hat have already committed $5 billion to fund the project, which deploys engineers and AI tools to patch, validate, and manage open source code. OpenAI’s models will work alongside other AI systems within Project Lightwell for code review and remediation tasks. IBM has described the initiative as an enterprise security clearinghouse staffed by a global engineering team. IBM shares jumped 4.6% in after-hours trading, according to Google Finance.

The company holds a market capitalization of about $235.7 billion. IBM has reported revenue growth of close to 10%, and seven analysts have recently raised their earnings estimates for the upcoming period, according to Investing.com. The US’s Commerce Department is separately expected to allocate $1 billion to IBM as part of a $2 billion quantum computing grant program, Cryptopolitan reported in May.

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Amazon MGM Studios confirmed on Thursday that it will not release “Artificial,” the director Luca Guadagnino’s film that chronicles Altman’s chaotic 2023 firing and rehiring at OpenAI. Mike Hopkins, who runs Prime Video and Amazon MGM Studios, informed Guadagnino and his producing team that Amazon would walk away from the planned release. The decision comes months after Amazon committed $50 billion to OpenAI in a February deal that expanded on a $38 billion cloud computing agreement signed in November 2025.

Amazon pulls plug on Sam Altman biopic ‘Artificial’

“We believe that Artificial will be better served if it were released by a different studio and are working closely with the filmmaking team to find the film a new home,” an Amazon spokesperson said. Andrew Garfield stars as Altman in the film, which was written by Simon Rich. Yura Borisov played OpenAI co-founder Ilya Sutskever. Monica Barbaro portrays former OpenAI CTO Mira Murati, while Ike Barinholtz plays Elon Musk. The cast also includes Cooper Hoffman, Jason Schwartzman, Billie Lourd, Mark Rylance, and Chris O’Dowd.

Altman was reportedly painted in an unfavorable light in the early version of Rich’s script, with one scene featuring computer scientist Geoffrey Hinton calling Altman “one of the most manipulative people on the planet.” A source familiar with internal workings at Amazon told reporters that the finished film’s tone turned considerably darker than what was originally pitched, and this led Hopkins to halt the release after watching a cut. An early viewer reportedly stated that Altman and Musk are the two characters audiences would “like the least.”

The business relationship between Amazon and OpenAI predates this deal by years. Amazon was among OpenAI’s earliest investors in 2015. Altman and Amazon founder Jeff Bezos have built a personal friendship over the past decade. Altman attended Bezos’s wedding to Lauren Sanchez in Venice in 2025. That friendship now sits alongside a corporate partnership worth tens of billions. Amazon’s February investment gave OpenAI access to Amazon Web Services infrastructure, including customized AI model development.

Jeff Bezos’ alleged influence and Altman’s legal tussle

With that much capital flowing between the two companies, releasing a film that portrays Altman as power-hungry and manipulative was always going to be an uncomfortable proposition. The film reportedly had a $75 million production and marketing budget. Amazon had reviewed every early iteration of the script before hiring Guadagnino to direct, meaning the studio knew the subject matter from the start. The shelved biopic adds to a public profile that continues to court conflict for the OpenAI CEO.

In May, a jury in Oakland rejected all of Elon Musk’s claims against OpenAI after a three-week trial. Florida Attorney General James Uthmeier filed the first state-led lawsuit against OpenAI and Altman in June, calling ChatGPT a “dangerous product” and seeking potentially billions in penalties. Altman also has close ties with the Trump administration, adding a political dimension to his already complicated public image.

The film had been positioned for a late 2026 awards qualifying run followed by a wide release in early 2027. It would have competed with Aaron Sorkin’s “The Social Reckoning,” a sequel to “The Social Network” that also deals with tech industry power. But with the latest developments, that release strategy is now in limbo. With Amazon out of the picture, the studio is now shopping the project to rival distributors through talent agency CAA.

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These new features address a growing pain point for large companies, as the cost of AI tools rises alongside broader employee adoption. Power users can burn through credits quickly, and these features will help administrators have better visibility into where the spending is going. The company’s Global Admin Console now consolidates ChatGPT and Codex credit usage into one dashboard, according to the OpenAI announcement. Administrators can filter consumption data by individual user, product, and AI model.

OpenAI unveils usage analytics and spending controls

The console also helps with data about trends over time, which would assist IT teams in spotting emerging usage patterns and identifying which employees are consuming the most credits. OpenAI also claims that the data is available to be programmed straight into companies’ financial systems through a unified Cost API. OpenAI first introduced per-role credit limits for custom roles earlier in 2026. The update extends that system further through three different levels.

Firstly, workspace-wide defaults let admins set a baseline credit cap that applies to every employee. Secondly, group-level limits allow different budgets for different teams. Then lastly, individual overrides give specific users higher capacity without raising limits for everyone else. On the employee side, workers can now see how much of their credit budget they’ve used and submit requests for more, including a note explaining what they need the additional capacity for.

Zipline co-founder Ryan Oksenhorn said the company has been using Codex since January 2026 and recently expanded the product’s adoption to the whole company. “We asked the team at OpenAI to build usage analytics to help find and train up folks who haven’t adopted Codex, and for granular usage controls to keep spend predictable,” Oksenhorn said in the OpenAI statement.

He added that the tools are helping Zipline “faster scale productivity of our employees while keeping safeguards in place.” The analytics and updated controls are available immediately to all ChatGPT Enterprise workspaces. Individual employees in those workspaces can view their own credit usage through their workspace settings.

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This statement, which came on June 8, follows from the tough situation of crypto allocators. As the Nasdaq-100 rises by 43%, with lots of money being invested in the robotics industry and SpaceX, the appeal of momentum-trading crypto has disappeared. However, according to Hunter Horsley, the change is no reason to stop trading cryptocurrencies. But it does demand a different investing posture. In his post on X, Horsley advised investors to take a step back and not concentrate on the news of the week or the month’s price movements.

Bitwise CEO urges traders to lean more on fundamentals

Horsley urged people to focus on two things – real progress in the project and year-on-year performance of the assets. The Bitwise CEO explained what he meant by “real progress,” namely, on-chain adoption stats, technological products with good product/market fit, integration with corporations and institutions, and the competency of the teams behind the projects. Two days prior, Horsley made a more straightforward point regarding the frustrations of the crypto market.

The author acknowledged that crypto investors are green-eyed with envy towards the profits brought by AI and space technology, but the reality is that the breakthroughs in technology took much longer to accomplish. For example, SpaceX was founded in 2002 and faced numerous failures, while OpenAI was established back in 2015, seven years before ChatGPT became widely known. Horsley pointed out that there is a gap between crypto natives and institutional capital coming into the market.

In his statement, he noted that crypto investors “are not used to an environment in which an hour is fast. A day is fast. A week is a meaningful period of time, and nobody can recall what was going on 4 weeks ago,” quoting an interview with Milk Road on June 5. The institutional capital works to a different timeline and will likely be better suited for the times ahead. That view is consistent with the comments from Matt Hougan, chief investment officer at Bitwise, writing in a market memo on June 2 that crypto was going through “a painful transformation – from momentum trade to contrarian investment.”

Hougan believed that investors’ focus shifted to artificial intelligence stocks, robotics firms, and private companies like SpaceX, leaving crypto to rely on long-term fundamentals rather than momentum-based storytelling. The memo is one of the most prominent admissions from Bitwise yet that the next stage of crypto requires something else beyond speculators’ inflows. According to Hougan, there was evidence that the market had started recognizing value based on fundamentals, not the macro story.

Examples of cryptocurrencies that increased in price by 72%, 50%, 44%, and 17% included Hyperliquid, Zcash, Stellar, and BNB, respectively; none of these assets moved because of the market’s strength. “When crypto stops being a momentum trade, fundamentals start to matter,” Hougan wrote. In addition to the SEC Rule, Hougan pointed out the Digital Asset Market Clarity Act, more commonly referred to as the CLARITY Act, as another highly significant but unresolved variable for institutional cryptocurrency adoption. The proposed legislation aims to provide greater clarity on the issue of jurisdiction between the SEC and CFTC.

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The integration allows users to connect financial institutions like Schwab, Fidelity, Chase, Robinhood, Amex, and Capital One. After connecting any financial account, the user will see a dashboard showing how their portfolio is performing, where their money is going, which subscriptions are active, and what payments are coming up. OpenAI says more than 200 million people already bring financial questions to ChatGPT each month. The new tooling turns those generic queries into personalized answers pulled from your actual account data.

OpenAI enables bank account linking

According to the platform, users are expected to click on “Get started” in the Finances option on ChatGPT’s sidebar to start using the tools. Another option is to type “@Finances, connect my accounts” in a conversation. The chatbot then walks the user through Plaid’s authentication flow from there. Plaid handles the actual connection between ChatGPT and the user’s bank or financial accounts.

After a user’s accounts are linked, they can ask ChatGPT, for example, about subscriptions they may have forgotten about, or compare this month’s grocery bill to last month’s. They can even ask ChatGPT to suggest ways to cut back on expenses, estimate how long it would take to pay off a credit card, or help them figure out how much to save each month to reach a goal.

OpenAI also plans to add Intuit support, which would let the chatbot estimate the tax impact of a stock sale. The company wrote, “The vision for ChatGPT is … to help users take action towards improving their financial lives, and we’re working with trusted ecosystem partners like Intuit to do this.” OpenAI said its GPT-5.5 model brings stronger contextual reasoning to finance queries. The company worked with finance experts to build a benchmark specifically for personal finance question quality.

ChatGPT cannot make changes to linked accounts or see full account numbers. It can view balances, transactions, investment holdings, and liabilities, including mortgage and credit card debt. Users can disconnect accounts anytime. Once disconnected, OpenAI will delete synced data within 30 days. The user can also view and delete individual “financial memories,” which are goals or obligations the chatbot has stored. Users can toggle whether their financial conversation data gets used to train OpenAI’s models.

The company did not specify what it might do with aggregated financial data beyond model training, or what additional protections exist against a potential data breach. The feature is live on ChatGPT’s web and iOS apps for Pro subscribers, who pay $200 a month. OpenAI plans to gather feedback from this group before expanding access to Plus tier users. The company’s eventual goal is to make the tools available to all users. Last week, OpenAI released three real-time voice models accessible through its API.

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According to reports, OpenAI confirmed that malicious actors breached two of its employee devices as part of a massive software supply chain campaign called “Mini Shai-Hulud.” OpenAI previously deployed controls to limit supply chain attack exposure after an incident with Axios, but the two affected employee devices had not yet received the updated configurations that would have blocked the malicious package download. The attack targeted TanStack, an open-source library used by millions of developers.

OpenAI confirms breach, denies data exposure

The attackers published 84 malicious versions across 42 npm packages, including the popular @tanstack/react-router, which is downloaded over 12 million times weekly. An external researcher working for StepSecurity detected the malicious packages within roughly 20 minutes of publication and notified npm security directly. This attack exploited the trust users have in automated build systems.

The malicious code was published using TanStack’s own legitimate publishing keys, making it look like an official update. Mini Shai-Hulud is a self-reproducing malware that steals credentials like GitHub tokens, cloud keys, and SSH keys once a developer or CI/CD system installs it. The malware then attempts to republish to other packages the victim maintains. Security researchers report that the campaign has compromised packages across the npm and PyPI ecosystems.

Beyond OpenAI and TanStack, the attack has affected code belonging to Mistral AI, UiPath (NYSE: PATH), OpenSearch, and Guardrails AI. Researchers note that the payload installs a persistent daemon that acts as a “dead-man’s switch.” If a victim revokes a stolen GitHub token, the malware can trigger a command to wipe the user’s home directory. Following the attack, OpenAI enlisted a third-party forensics firm to assist with the investigation.

The company said it found no evidence that its user data was accessed or that its production systems, intellectual property, or software were compromised. However, the attackers still managed to extract some credential material from internal code repositories that those devices had access to. This included code-signing certificates for macOS apps. Now, Mac users must update their ChatGPT Desktop, Codex, and Atlas apps latest by June 12, 2026, or the software will be blocked by macOS security protections.

OpenAI said it has found no evidence of malicious software signed with its certificates and no unauthorized modifications to published applications. The company noted that new notarization with the old certificates has already been blocked, meaning any fraudulent app attempting to use them would lack Apple’s notarization and be stopped by macOS security protections by default.

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According to the OpenAI team, GPT-5.5 combines native computer use with advanced reasoning. It autonomously navigates the software tools required for high-level professional tasks. The model’s ~1.1 million-token context window allows it to process massive financial datasets that previously required manual chunking. OpenAI’s financial team used GPT-5.5 to review 24,771 K-1 tax forms (71,637 pages) and completed the task two weeks faster than the previous year.

OpenAI says the model features general-purpose capabilities

In its statement, OpenAI said GPT-5.5 also scored 88.5% on internal investment banking modeling tasks and 60% on the FinancialAgent v1.1 benchmark, outperforming GPT-5.4 by four points. An employee of the Go-to-Market team has confirmed that automating weekly business reports will save roughly 5-10 hours of manual work per week. In addition, OpenAI says GPT-5.5 was used to help write code for its own serving infrastructure.

The model also achieved “System-Level Optimization” by analyzing production traffic patterns to write custom load-balancing heuristics, increasing its own token generation speed by 20%. A developer in one test asked the model to “re-architect a markdown editor.” It returned a nearly complete 12-diff stack with minimal human correction. OpenAI notes that the new model is more efficient, reaching the correct answer in fewer turns and using 40% fewer tokens for the same Codex tasks.

However, the per-token price is double that of GPT-5.4. Dan Shipper, the founder and CEO of Every, describes GPT-5.5 as the first coding model that has “serious conceptual clarity.” To test GPT-5.5, Shipper brought in GPT-5.5 after he and his best engineer spent days debugging a post-launch issue in an app to rewrite part of the system. He says GPT-5.5 achieved what GPT-5.4 could not: it examined the broken code and produced the rewrite that the engineer eventually decided on.

GPT-5.5 unlocks faster help for harder problems, the firm says

The model can “remember” and cross-reference entire libraries of information without losing its place, reducing the “hallucinations” that plagued earlier versions. OpenAI also claims that GPT-5.5 is optimized for “self-correction” and autonomy. It is better at interpreting ambiguous instructions and using a computer interface (clicking, typing, browsing) to complete objectives without human intervention.

However, the primary source of excitement is GPT-5.5’s shift toward agentic autonomy. The model becomes specifically useful when an agent is needed to operate software, manage terminal-heavy workflows, or reason across an entire codebase (500K+ tokens) with high retrieval accuracy.

Meanwhile, early GPT-5.5 Pro testers say there is a massive improvement in both the quality and the difficulty of the work ChatGPT can take on. Its lower latency makes it more practical for demanding tasks than GPT-5.4 Pro. GPT-5.5 Pro’s responses are well-structured, relevant, useful, and accurate. They perform particularly well in law, data science, business, and education.

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The malware remained on the npm registry for a week and has so far infected about 178 developers before it was removed on March 10. According to reports, @openclaw-ai/openclawai posed as a legitimate OpenClaw CLI tool but instead ran a multi-stage attack. The malware collected sensitive data from developers. It extracted crypto wallets, macOS Keychain passwords, cloud credentials, SSH keys, and AI agent configs. The extracted data connects hackers to cloud platforms, codebases, and crypto.

GhostClaw malware scans clipboard for crypto data

According to researchers, the GhostClaw malware monitors the clipboard every three seconds to capture crypto data. This includes private keys, seed phrases, public keys, and other sensitive data related to crypto wallets and transactions. Once the developer runs the ‘npm install’ command, a hidden script installs the GhostClaw package globally. The tool runs an obfuscated setup file on developers’ machines to avoid detection.

A fake OpenClaw CLI installer then appears on the screen. It prompts the victim to enter their macOS password through a Keychain request. The malware verifies the password using a native system tool. After that, it downloads a second JavaScript payload from a remote C2 server. The payload, called GhostLoader, acts as a data stealer and remote access tool. Data theft begins after the second payload download.

GhostLoader does the heavy work. It scans Chromium browsers, Macintosh operating system (macOS) Keychain, and system storage for crypto wallet data. It also monitors the clipboard almost continuously to capture sensitive crypto data. The malware even clones browser sessions. This gives hackers direct access to logged-in crypto wallets and other related services. Moreover, the malicious tool steals API tokens that connect devs to AI platforms like OpenAI and Anthropic.

Attackers ramp up their crypto theft activities

The stolen data is then sent to threat actors via Telegram, GoFile, and command servers. The malware can also run numerous commands, deploy more payloads, and open new remote access channels. Another malicious campaign that relies on OpenClaw’s hype also spread on GitHub. The malware, which was discovered by cybersecurity researchers from OX Security, aims to contact devs directly and steal crypto data.

Attackers create issue-threads in GitHub repositories and tag potential victims. Then they falsely state that chosen devs are eligible to receive $5,000 in CLAW tokens. The messages then lead recipient devs to a fake website that looks exactly like openclaw[.]ai. The phishing website sends a crypto wallet connection request that starts harmful actions when accepted by the victim. Linking a wallet to the site can lead to instant theft of crypto funds, warns OX Security researchers.

Further analysis of the attack reveals that the phishing setup uses a redirect chain to token-claw[.]xyz and a command server at watery-compost[.]today. A JavaScript file with malicious code then steals crypto wallet addresses and transactions and sends them to the hacker. OX Security found a wallet address tied to the threat actor that might hold stolen crypto. The malicious code has features to monitor user actions and remove data from local storage. This makes malware detection and analysis harder.

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The most notable case came from a Chinese influence campaign that got exposed by accident when a Chinese law enforcement official used ChatGPT like a personal diary. The official wrote about an operation targeting Chinese critics living in other countries. The campaign involved hundreds of operators and thousands of fake social media accounts, according to OpenAI.

The operation tried to impersonate United States immigration officers to scare a dissident by falsely saying their public statements broke American law. In other cases, operators used forged documents claiming to be from a county court to try getting critics’ social media accounts taken down.

OpenAI gives insight into a new harassment campaign

They created a fake obituary and gravestone photos to spread false rumors about one dissident’s death. These rumors actually showed up online in 2023, a Chinese-language Voice of America article confirmed. Ben Nimmo, who leads investigations at OpenAI, called the effort industrialized harassment aimed at critics of the Chinese Communist Party through multiple channels.

Using ChatGPT as a record-keeping tool ended up exposing the operation. ChatGPT worked as a journal for the operative to track the covert network, while other tools generated most of the actual content that got spread through social media. OpenAI banned the user after finding the activity. OpenAI investigators matched descriptions from the ChatGPT user with real online activity.

The user described faking a Chinese dissident’s death by creating a phony obituary and gravestone photos for posting online. In another case, the ChatGPT user asked the system to create a plan for damaging the reputation of incoming Japanese Prime Minister Sanae Takaichi by stirring up anger over American tariffs. ChatGPT refused. But in late October, when Takaichi took power, hashtags showed up on a popular forum for Japanese graphic artists attacking her and complaining about tariffs.

Microsoft unveils similar trends in its report

The OpenAI report also covered several scam operations from Cambodia that used the platform for romance and investment fraud, plus influence campaigns linked to Russia targeting Argentina and Africa. In a separate report published by Microsoft in collaboration with OpenAI, looking at how nation-state actors from Russia, North Korea, Iran, and China are trying out large language models to support cyber attack operations.

Both companies shut down efforts by five state-affiliated actors by closing their accounts. The Microsoft report found these actors mainly wanted to use services for simple jobs like searching publicly available information, translating content, fixing coding errors, and running basic programming tasks. No major or new attacks using the models have been found so far. This gap between fear and reality happens during tough competition between Washington and Beijing over control of this technology.

The role it plays in military and economic matters has also become a major fight. The Pentagon recently told another company, Anthropic, it has until Friday to remove certain safety features from its model or risk losing a defense contract. Microsoft said it’s working on principles to lower risks from bad use of these tools by nation-state groups and criminal organizations. These principles include finding and stopping bad users, telling other service providers, working with other groups, and being transparent.

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While water concerns might be fading, the real problem of massive energy consumption keeps growing. Speaking at an event in India last week, Altman called online claims about water usage “completely untrue” and said newer facilities don’t depend on water for cooling anymore. Traditional data centers have used millions of gallons to cool equipment, but technology is changing. A recent study still projects water demand for cooling could more than triple in the next 25 years as computing needs expand.

OpenAI CEO talks energy use in AI data centers

In his statement, Altman said energy use is a fair concern. The world needs to shift quickly to nuclear, wind, and solar power as AI use grows, he said. When asked about comparisons between human and AI energy efficiency, he argued the comparison should look at energy per query after training, not the training process itself.

He compared training AI models to raising humans, noting it takes 20 years and lots of food before a person becomes productive. However, that comparison got criticized. Indian tech billionaire Sridhar Vembu, who attended the same summit, said he doesn’t want to see technology equated with people. His comment shows broader worries about AI potentially replacing human workers.

Data centers used electricity comparable to entire countries like Germany or France in 2023, based on International Monetary Fund numbers. This happened shortly after ChatGPT launched and sparked an AI boom. The GW Ranch project in West Texas will cover 8,000 acres and use more electricity than Chicago. It will make power through natural gas and solar panels, avoiding delays from utility companies struggling with capacity issues.

Similar projects are planned or underway in Wyoming, New Mexico, Pennsylvania, Utah, Ohio, and Tennessee. Meta, OpenAI, Oracle, and Chevron are backing these developments. Some states passed laws making approvals easier. In West Virginia near Davis, a planned data center will include a gas plant big enough to power every home in the state.

Nation’s largest grid suffers strain as communities pushback

The United States runs 5,246 data centers using at least 17 gigawatts of power. One large nuclear plant makes one gigawatt, enough for 300,000 to 750,000 homes. These facilities will include some solar power, but most will run mostly on natural gas because other sustainable options don’t provide steady output. Without grid backup, gas becomes necessary.

Energy researcher Michael Thomas warned that this approach is “catastrophic for climate goals.” His firm found 47 off-grid data center projects nationwide. Elon Musk built an off-grid facility in Memphis last year using portable gas generators to avoid grid limits. His xAI data center went online in months instead of years. But the Environmental Protection Agency ruled in January that his setup broke emissions regulations and ordered the company to get proper permits.

Meta is also moving ahead with multiple off-grid projects. One in New Albany, Ohio, will use two gas power plants and launch later this year. Another in El Paso links 813 smaller generators. Local officials protested, saying Meta promised clean energy but delivered gas power instead. The company said it would meet clean energy commitments by purchasing renewable energy credits and adding clean power to the grid elsewhere.

Communities are now fighting back against data center proposals in populated areas. Citizens in Tucson beat a project called Blue over water concerns in the desert and potential electricity bill increases. A large data center can use 5 million gallons of water daily, matching a town of 10,000 to 50,000 people, based on Environment and Energy Institute numbers. San Marcos, Texas, rejected a proposed 1.5 billion dollar data center last week after months of public opposition.

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