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  • Stolen Cloud AI Keys Hit Retailers and Tech Groups with Million Dollar Bills

    Stolen Cloud AI Keys Hit Retailers and Tech Groups with Million Dollar Bills

    Intruders who breach corporate cloud accounts are quietly activating dormant artificial intelligence tools and running models at company expense, running up bills exceeding 100,000 dollars in a day.

    Investigations carried out across 2026 by Mandiant and the Google Threat Intelligence Group revealed intrusions across Asia Pacific, North America and South America that reached cumulative costs of up to 1 million dollars before victims spotted the leaks. The compromises struck retail, transportation, financial services and technology companies that had adopted large language model architectures into their systems.

    How Illicit Resellers Drain Foundation Models

    The campaign, dubbed LLMJacking, relies on a distinct commercial division of labour within cybercrime rings. One group specializes in penetrating corporate environments to harvest credentials, while a separate tier operates illicit platforms known as LLM Mixers to resell that raw model compute to third-party subscribers.

    One service, trading under the name Jet Night, offered paying customers unlimited subscriptions for about 60 dollars a month to access premium foundation models. Comparable commercial access carries legitimate pricing between 100 and 250 dollars. Security investigators determined the syndicate could only sustain that price differential by powering the backend with stolen enterprise credentials.

    During a single intrusion linked to the network, an unauthorized actor channeled more than 500,000 queries to foundation models in under eight hours. The targeted enterprise absorbed an unauthorized token bill approaching 1 million dollars before discovering the drain. Jet Night subsequently recorded sudden outages on its Telegram broadcast channels whenever compromised businesses identified the breach and revoked the active keys.

    Another unauthorized syndicate set up a lookalike domain disguised as an internal corporate host, routing the victim organization’s application programming interface quotas into a commercial resale front operating as newapi.pro.

    The Shift From Cryptojacking to Token Hijacking

    Retailers and consumer tech operators have spent years guarding compute fleets against illicit cryptocurrency mining, but model hijacking works at vastly accelerated speed. Cryptojacking trickles away compute slowly to evade system detection, whereas LLMJacking generates massive spikes in fraudulent cloud charges in a matter of hours.

    Investigators noted that actors reach their goals through token proxying, automated model streaming and unauthorized graphics processing unit hardware provisioning. Rather than manipulating consumer-facing chatbots to spit out rogue lines of code, the attackers bypass the store front-end entirely to tap backend infrastructure.

    For retail and digital commerce platforms in Asia that connect real-time product search, automated customer query desks and dynamic inventory to foundation models, the financial exposure sits directly in the operating budget. Cloud quotas linked to corporate credit accounts or open enterprise billing agreements allow perpetrators to cash out instantly through black-market resale while the operator absorbs the invoice.

    Stolen Keys and Exposed Gateways

    Initial penetration rarely requires novel zero-day attacks. Threat groups scrape publicly exposed GitHub repositories for stray application programming interface keys, running minute test queries designed to avoid triggering usage alerts.

    Most intrusions stem from compromised cloud infrastructure credentials, including unprotected service account keys, active session tokens and corporate GitHub authorization tokens. A group tracked as UNC6993 gained access to a commercial cloud instance via a misconfigured service account credential, quickly bridging across into internal model endpoints. The same operators established a fraudulent registration portal for model developers, tricking visiting engineers into submitting live access tokens that circumvented multi-factor authentication controls.

    Once inside a corporate network, attackers search database tables and data warehouse systems for deeper administrative secrets, occasionally disguising backdoor accounts as internal cost-optimization utilities. In another instance, attackers targeted a vulnerability logged as CVE-2026-40217 inside a LiteLLM routing gateway, escalating basic user credentials into root administrative control.

    Dormant Services Turned on by Intruders

    In multiple forensic investigations conducted by Mandiant, the targeted companies had left their high-tier machine learning services deactivated. Intruders used administrative cloud credentials to switch on the dormant model engines, initiating high-frequency automated requests within minutes.

    The findings indicate that monitoring routine endpoint activity is no longer sufficient for digital commerce operators running hybrid cloud stacks. IT departments now face the operational reality that unmonitored API limits directly threaten gross margins, turning routine cloud administration into an immediate balance-sheet liability.

    Enterprises running production workflows across multiple public cloud providers must track anomalous model activation alerts and enforce hard spend caps on machine learning billing accounts to catch breaches before usage tallies reach six figures.

  • Hackers Hijack Corporate Cloud AI Accounts, Racking up $100,000 Daily Bills

    Hackers Hijack Corporate Cloud AI Accounts, Racking up $100,000 Daily Bills

    Cybercriminals are hijacking corporate access to large language models across the Asia-Pacific region, driving unauthorized cloud billing charges past USD $100,000 in a single day. The findings, released this week by Mandiant and the Google Threat Intelligence Group, revealed that victims spanned retail, financial services, transportation and technology across Asia Pacific, North America and South America.

    For some targets, aggregate billing reached almost USD $1 million before administrators discovered the breach and revoked access keys. The financial damage mounts much faster than conventional cryptojacking, which typically drains server capacity at a slow, continuous pace. In one investigated incident, attackers executed more than 500,000 API calls against advanced language models in less than eight hours.

    How Attackers Breach Cloud Accounts

    Intruders frequently exploit credentials leaked inside public GitHub code repositories or harvest access through compromised browser sessions and stolen identity tokens. In several documented breaches, the targeted companies had never activated machine learning or model features within their cloud accounts. Attackers simply logged into dormant environments, turned on the services themselves and began issuing high-volume automated requests.

    A threat group tracked as UNC6993 gained access to corporate systems in mid-2026 by exploiting a misconfigured service account key. The group also operated a fake web portal that prompted internal users to submit active session tokens alongside JSON payloads, allowing attackers to slip past multi-factor authentication checks and passwords entirely. Another cluster extracted API keys from public repositories and tested them using single-token queries to avoid tripping intrusion detection systems.

    Once inside a tenant, attackers escalated system privileges to secure their hold. Intruders created administrative backdoor accounts masked as legitimate billing optimization utilities and injected unauthorized SSH keys into corporate compute instances. Some attackers exploited vulnerability CVE-2026-40217 in the open-source LiteLLM gateway, elevating basic virtual keys into full administrative proxy permissions.

    Illicit Resale Through Discount Gateways

    Stolen model capacity feeds an organized underground market where criminal syndicates divide tasks between network infiltration and wholesale resale. Broker networks bundle compromised corporate keys into centralized routing proxies known as LLM Mixers. These illicit hubs rely on open-source utilities like new-api and gcli2api to manage traffic distribution.

    One illicit routing platform, operating under the name Jet Night, transferred nearly USD $1 million in artificial intelligence compute charges onto a single victim company. Jet Night resold unlimited model access to paying underworld customers for approximately USD $60 a month, undercutting legitimate commercial plans that cost between USD $100 and USD $250. Service interruptions announced on underground messaging channels like Telegram directly matched instances where breached corporate victims detected anomalies and cancelled their compromised access credentials.

    Other attackers expanded their operations by provisioning high-end graphics processing unit clusters across multiple cloud regions. Intruders submitted administrative requests for higher computing quotas, deploying persistent backdoors based on the Manus agent framework to automate operations at corporate expense.

    The Real Cost for Regional Retail Operators

    For Asia-Pacific retailers racing to deploy automated customer service bots, inventory forecasting and algorithmic pricing engines, the findings alter cloud risk calculations. Regional retail groups have rushed to integrate machine learning endpoints into e-commerce storefronts without auditing legacy cloud consoles or default cloud permissions. A compromised key can trigger hundreds of thousands of dollars in operational liabilities before month-end accounting reconciliation notices the discrepancy.

    The threat extends well beyond unexpected invoices. When criminal syndicates route unvetted third-party traffic through corporate model instances, retail operators face potential regulatory and data exposure liabilities across regional jurisdictions. Security teams must now treat unexpected cloud API activations as urgent containment priorities rather than routine billing errors.

    Containment Measures and What to Watch

    Defensive guidelines published in the investigation urge companies to monitor code repositories for exposed tokens, audit cloud consoles for unapproved model services, and enforce strict spending caps. Organizations should configure model-level rate limits and mandate hardware-backed, phishing-resistant multi-factor authentication across developer systems.

    Whenever possible, threat actors want to use this technology to gain a scale advantage over defenders. They achieve that with agentic tools and by stealing tokens from unwitting third parties. Locking down these resources will not only protect organizations from runaway costs, but also protect the broader community from a deluge of cheap, autonomous attacks.

    John Hultquist, Chief Analyst at the Google Threat Intelligence Group, noted that companies must aggressively control access to the computing resources they are bringing online to stop external actors from exploiting corporate budgets. Cloud providers and enterprise clients are now monitoring whether upcoming security updates for tools like LiteLLM and automated API spending hard caps will curb unauthorized token abuse before enterprise cloud budgets reset for the next fiscal quarter.