OpenAI has launched GPT-6.1 Terra, a new model focused on computer use, visual reasoning, coding, and everyday work, while costing significantly less than its larger models. Terra is designed as a faster and cheaper option for tasks such as filling out forms, editing videos, interpreting technical drawings, and automating repetitive desktop work. "We’re introducing GPT-6.1 Terra, a fast, efficient model that combines detailed visual reasoning and precise computer use alongside clearer, more natural writing," OpenAI explained in a blog post. "A significant step up from GPT-5.6 Terra, it excels at the communication and computer-based tasks that fill the workday, from drafting proposals and interpreting technical drawings to filling out forms and editing videos." OpenAI says GPT-6.1 Terra's API pricing is 50% lower than GPT-5.6 Terra and GPT-6.1 Sol, at $1 per million input tokens and $5 per million output tokens.
Sansec tracks a Magento skimmer campaign that infected 953 stores, using five domains, bot filtering and malicious code hidden in CMS blocks. A criminal group has infected 953 online stores since July 2025, mostly Magento shops, according to Sansec researchers. The attackers add a small piece of code to store pages. When someone visits a shop, their browser contacts the attackers’ server to get further instructions. The server checks whether the visitor is a real shopper or a security scanner. If it detects a scanner, it hides the malicious activity. “deepveindrilling.com is the newest web address of a criminal group that breaks into online stores. The group adds a small piece of code to the store’s pages.” Sansec’s analysis states. “The group has done this to 953 stores since July 2025, mostly Magento shops. It moves to a new address every few months.” The group’s latest domain is deepveindrilling.com. Sansec found it in the CMS blocks of 83 stores, almost all running Magento. CMS blocks are content sections that Magento adds to store pages. The domain was registered on October 6, 2026, and the first stores began loading it the following evening. This is the fifth domain linked to a campaign that Sansec has tracked since July 2025 and reported in March as the PolyShell mass attack. Most stores using the latest domain had already been targeted. Of the 83 stores, 60 had previously loaded one of the group’s malicious scripts, and 34 had been doing so since October 2025. The domain sits behind Cloudflare, and its front page returns a 404. It only answers script requests from visitors of infected stores. The loader code lives in the cms_block table, and Sansec’s scanner, eComscan, found it there on 148 server installs over the campaign, never in core_config_data or theme files. eComscan first found the new loader at 21:54 UTC on October 7. By the end of October 8, Sansec’s crawler had found it on 74 stores, as two scripts. The first reads a value called fpCode from the visitor’s browser storage, and when the value is set, the script puts the stored code in an invisible div and clicks it. The browser then runs the code as an event handler, without using eval(). Nothing in the block writes fpCode, so the script from deepveindrilling.com has to set it. A visitor who received the payload once runs it again on every later page view, even when the domain is offline or blocked. The March version deleted its stored payload after one run. On October 23 the operator rewrote the blocks again, and the loader appeared on 9 more stores. All 71 stores Sansec re-crawled by October 24 run the new version. It replaces the plain script tag with an inline loader that sends a browser fingerprint to https://deepveindrilling.com/?s=49b7ca5f&fp=. The fingerprint flags automated browsers through navigator.webdriver, Selenium globals and ChromeDriver’s cdc_ properties. It also adds the GPU name from WebGL, CPU cores, memory, screen size, time zone, languages and client hints. The server picks its response from all of that. The filter works. When urlscan.io loaded an infected store with an automated Chrome browser, it got HTTP 200, and Sansec found no added content in the page. Sansec hasn’t captured the final payload yet. Older payloads give a hint of what real visitors get. Sansec Watch, the firm’s monitoring service for content security policies, shows what the earlier stage served. On December 12, 2025, a customer logged in to an infected store got a script from manulfie.click that loaded https://crypto-insider.top/ssl/ and, five minutes later, https://leqdger.click/ssl/. On December 15 and 16, neswnsssn.click inserted the same leqdger.click script on two more stores. leqdger.click is a misspelling of the crypto wallet brand Ledger. It was registered on September 12, 2025 and has since expired. Before October, the second script was the “Script (async)” integration of Keitaro, a commercial ad tracker that doubles as a traffic distribution system, a tool that sorts visitors. It sends the referrer, page title and query string to a base64 encoded URL such as https://additionalver.com/Mb2z8J?&se_referrer=, where the path is the Keitaro campaign alias. The system then decides per visitor whether to return a payload, a redirect or nothing. “When Sansec requested the additionalver.com script as a Windows desktop visitor on October 24, it returned QWE=123;, a statement that does nothing, and set a cookie that marks the visitor for 24 hours. deepveindrilling.com drops Keitaro and moves the bot filtering into the loader.” continues the report. Here are the five loader domains over 15 months: DomainRegisteredFirst seen on storesStoresmanulfie.clickbefore July 2025, re-registered 2026-05-232025-07-09863neswnsssn.clickbefore December 2025, re-registered 2026-05-222025-12-12494lanhd6549tdhse.top2026-03-252026-03-30355additionalver.com2026-06-072026-06-08246deepveindrilling.com2026-10-062026-10-0783 Two other domains were found on a small number of stores: hdfdsi84j3h.top, registered three minutes after lanhd6549tdhse.top, and c85grt98sd.com. Two older domains, neswnsssn.click and manulfie.click, expired and were registered again in May 2026. Both now use the nameservers of abovedomains.com, a domain parking service. Between August and October 2026, Sansec still found the manulfie.click loader on nine stores and the neswnsssn.click loader on six. When visitors open these stores, their browsers send information about the previous page and the current page title to the new domain owner. The browsers also run any script returned by that domain. Sansec Watch received reports of visitors’ browsers connecting to all four earlier domains. One domain, additionalver.com, was linked to around 52,000 reports. The October activity did not rely on a new vulnerability. Of the 83 affected stores, 60 had already been infected. Earlier attacks appear to have exploited file upload flaws in Magento. In March, the group injected its malicious code into 471 stores in just one hour by uploading webshells through PolyShell (CVE-2026-48356). Some infected Magento stores had files uploaded through PolyShell or SessionReaper (CVE-2025-54236). In a separate group of 3,024 stores affected by another skimmer, the infection rate was 32%. One Magento 2.4.7-p1 store contained PolyShell webshells disguised as PNG images, alongside malicious code in a CMS block. The code switched from additionalver.com to deepveindrilling.com on October 7. The store had not installed Adobe’s PolyShell fix, APSB26-73. However, installing all patches does not guarantee a store is safe. Another store running Magento 2.4.7-p10 had no missing core patches but was infected on October 23. Earlier scans had already found a rogue admin account and a GSocket backdoor. Sansec recommends checking CMS content for malicious code, including base64-encoded domains. Administrators should search both the cms_block and cms_page tables for suspicious patterns such as fpCode and se_referrer. They should also inspect uploaded files for webshells, check for unknown admin accounts, and look for suspicious processes. Removing the malicious scripts is not enough: store owners must also identify and fix the vulnerability or backdoor that allowed the attackers in. After cleanup, change the database, admin and API integration passwords. Install APSB26-73 for PolyShell and APSB25-88 for SessionReaper. Sansec Shield blocks both attacks while you schedule the upgrade. Sansec lists the indicators of compromise at the end of its report. “If your store loads any domain from the indicators of compromise, the attacker can write to your database. Deleting the script does not remove that access. See How to check your store.” concludes the report. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Magento)
DreamHost has forced password resets for email and FTP/SFTP users following an incident that disrupted connections to the File Manager interface. The latest update from the web hosting provider notes that all affected account owners have received recovery instructions. Users will be unable to log in until their account owner sets new credentials. DreamHost is a U.S. web hosting provider and domain registrar that offers WordPress hosting, business email, virtual private servers, dedicated servers, and cloud services. According to the company page, it serves over 400,000 customers in more than 100 countries and supports at least 1.5 million websites and applications, including 750,000 WordPress installations. DreamHost initially reported connectivity problems affecting its File Manager interface on October 23, but the impact quickly expanded to other services.
Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock (LockA locked padlock) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites. Share: Opens in a new window Opens in a new window Opens in a new window Press Release CISA Unveils New Strategy to Strengthen National Cyber Defense and Critical Infrastructure Security CISA 2030: Defend, Harden, Prevail Released October 26, 2026 Related topics: Cybersecurity Best Practices , Critical Infrastructure Security and Resilience WASHINGTON – The Cybersecurity and Infrastructure Security Agency (CISA) today released its new strategy, CISA 2030: Defend, Harden, Prevail, which advances President Trump’s Cyber Strategy for America and National Resilience Strategy while strengthening the security and resilience of the nation’s critical infrastructure.
Cyfirma links PHP2Shell scans of 216 vulnerable hosts to a suspected North Korean campaign using AI to rank public exploits. On October 21, PHP released emergency patches for two critical vulnerabilities, CVE-2026-109618 and CVE-2026-109619, both rated 9.2 on the CVSS scale. The flaws affect all PHP versions that handle web requests. The vulnerable code dates back to PHP 5.4, released in 2012, and resides in the PHP engine itself rather than in individual applications. Attackers can exploit the flaws to execute code remotely by sending specially crafted HTTP requests, without authentication. Exploitation attempts increased rapidly after the vulnerabilities became public. Cloudflare researchers reported tens of thousands of attempts within the first 45 minutes, hundreds of thousands in just two hours, and millions by October 22. Cyfirma reported that a group of North Korea-linked group has identified 216 hosts that may still be vulnerable to PHP2Shell. The operators communicate through a private I2P channel that Cyfirma has monitored since October 22. On October 24, they reported that 216 hosts appeared to be unpatched or only partly protected, earlier than Cyfirma expected. They are checking the systems from 21 compromised machines. At the time Cyfirma captured the conversation, the operators had already checked about one-third of the targets. “Two handles active since March 2026, coordinating in a closed I2P channel; staging infrastructure shared in-channel.” states the cybersecurity firm. “Target set and scan nodes. “On 24 October the operators reported 216 unpatched or partially mitigated hosts and named 21 scan nodes; the same addresses were seen performing web-shell tooling and upload-progress session-poisoning attempts.” The scanning is slow on purpose. Volume stays low, the machines rotate, and any node that shows filtering or rate limiting gets pulled and never reused. That’s why a rate-based alert will probably stay quiet. Who’s behind it? Cyfirma assesses with moderate confidence a link to the Lazarus family of North Korean groups, based on language, operating style and old habits with PHP web shells and hijacked web servers. It has no shared malware or infrastructure to point to yet, and it admits that a Korean-speaking criminal crew without state backing would fit the same facts. Its confidence in the campaign itself is high. Government agencies and banks come first. Next in line are logistics, ports, airports and aviation, manufacturing, and online transaction and trading platforms. The countries named are the US, Japan, South Korea, Thailand, Indonesia, Australia, Taiwan, India, Singapore, the UAE, Saudi Arabia and the EU. Cyfirma has not named any victims or seen the full list of targeted systems. The operators have not announced when they plan to launch attacks, and the researchers have not confirmed that this group has compromised systems on a large scale. Cyfirma gives the campaign an imminence score of 78 out of 100. The operators plan to check all 216 hosts, select the most promising targets, and decide which publicly available exploits to adapt. The group does not appear to be developing new exploits. Instead, its members use a local AI model to rank public exploit repositories, then test the results manually in a lab. Cyfirma believes this approach could help attackers turn newly disclosed vulnerabilities into working attacks more quickly. However, researchers warn that some proof-of-concept exploits shared online are fake and may contain malware, so downloading and running them can be dangerous. Technical details leaked on October 20, ahead of coordinated disclosure, and the PHP project shipped fixes on October 21. Apache mod_php with default settings and prefork is the confirmed worst case for 109618, with full unauthenticated code execution. For 109619, PHP-FPM is validated through the upload-progress path. One correction matters for your temporary controls. Early coverage tied the session upload-progress field to 109618, but PHP’s advisories put it under 109619 only. Disabling upload progress does nothing for 109618, so the two bugs need different stopgaps. Triggering the bug is easy, but reliable code execution isn’t. The attacker has to land a follow-up request on the same worker and shape heap data into the freed space, otherwise the worker crashes or answers normally. VulnCheck reports working code execution on x86-64 with ASLR enabled against PHP 8.4.10 to 8.4.26, while ARM64 only leaks memory so far. Short of code execution, attackers have already shown worker crashes, arbitrary file reads through OPcache and a leak of about 67 KB of process memory. The fixed releases are PHP 8.5.12, 8.4.27, 8.3.36 and 8.2.35. PHP 8.1, 8.0 and 7.4 get only minimal backports, and vendors such as cPanel EasyApache, CloudLinux, TuxCare and Plesk carry their own builds, so confirm coverage with yours. Anything from PHP 5.4 to 7.3 has no fix, so migrate or isolate it. Restart every worker after patching, because a reload that keeps old workers alive leaves the stale state in place. Isolate anything internet-facing that you can’t patch within hours, starting with Apache mod_php. If you suspect a host is compromised, capture memory and logs before you patch, since a restart destroys the CVE-2026-109619 state. Then rebuild the host from a trusted image and rotate every secret the PHP worker could reach. Hunt back to October 17, the earliest known exploitation, and use long time windows. The strongest single signal is a PHP or web server process spawning something it never normally spawns. Application logs will usually show nothing, because the bug fires before application code runs. Look for odd multipart POSTs to endpoints that never take uploads, bursts of worker crashes and memory errors, new PHP files in web roots, and new cron jobs, local users or SSH keys. Cyfirma includes Sigma, Splunk and YARA content, though it says the YARA set hasn’t been tested on real application code yet. It also lists 21 scan-node addresses, 17 source addresses from October 23 and 15 staging addresses, all defanged. Some scan nodes are described as compromised and may belong to victims, so hunt for prior contact before assuming who owns them. If you can’t patch yet, the advisory suggests limits such as a low post_max_size and disabling session upload progress for 109619. Cyfirma is clear that none of it replaces patching. The operators’ own selection rule is the most useful detail in the whole advisory, because they dropped every host that showed a fixed version or sat behind heavy filtering. That makes a current version string a cheap filter against you, and for once being boring pays off. “Hosts still bannering older PHP are the ones the operators kept.” Cyfirma states. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, PHP2Shell)
Two critical RCE vulnerabilities (CVE-2026-109618 and CVE-2026-109619), collectively tracked as PHP2Shell, have been successfully exploited in the wild. The malicious activity was caught by Adel Karimi, detection and response lead at Perplexity, whose honeypots recorded evidence of confirmed remote code execution against an Apache mod_php installation running PHP 8.4.26. "This is now confirmed RCE with usable memory disclosure, not just a crash followed by a suspicious process. The response delivered an 800 KiB decoded cookie dump, and a function address derived from that dump using the public exploit's offsets appears in the subsequent execution payload," Karimi shared. "The client acknowledged the full response; the shell command then ran about 1.6 ms after the execution request's final captured byte."
Pierluigi Paganini answers questions about the PHP2Shell vulnerability, early exploitation, AI-assisted attacks, and the risks to businesses, servers, and personal data. 1. Your latest report reveals that hackers began exploiting the PHP2Shell vulnerability four days before it was publicly disclosed. First, can you explain what PHP is, how widely it is used across the internet, and why this particular security flaw is so serious? PHP is a programming language widely used to build websites and web applications. It powers a significant share of the web. PHP2Shell is serious because it can allow attackers to execute commands on a vulnerable server remotely. Depending on the configuration and the server’s privileges, this could give threat actors access to sensitive data, applications and other systems. 2. According to AWS researchers, attacks were already underway before the vulnerability became public. How did researchers uncover this early exploitation, and what does it tell us about the ability of hackers to identify security weaknesses before developers can fix them? AWS researchers detected exploitation attempts against their honeypot network four days before public disclosure and the release of patches. This shows that attackers can discover or weaponize vulnerabilities before defenders have time to respond. AI-assisted analysis may accelerate this process, helping attackers turn technical information into working exploits in hours rather than days. However, detected attempts do not automatically mean successful compromises. 3. The vulnerability could potentially allow attackers to execute malicious commands on affected servers. What does that mean in practical terms, and what risks does it pose to websites, businesses and the personal information of their users? Remote command execution means an attacker may be able to make a server run commands without authorization. Depending on the attacker’s access, they could steal data, install malware, change website content, or use the compromised server to attack other systems. Businesses could face service disruption, financial losses and reputational damage. Users may also be exposed if their personal information is stored on an affected system. The actual impact depends on the server’s configuration and security controls. 4. The latest findings raise concerns about the gap between discovering a vulnerability and protecting systems against it. How quickly can attackers exploit these weaknesses, and are businesses adequately prepared to respond when critical security flaws emerge? The window can be extremely short. In some cases, attackers can develop or adapt an exploit within hours, leaving organizations little time to react. Many businesses still rely on patching schedules that are too slow for internet-facing systems. Organizations need continuous monitoring, rapid patching, tested incident response plans and clear visibility into exposed assets. They should also investigate suspicious activity dating back to before a vulnerability was publicly disclosed, because attacks may already be underway. 5. With PHP powering a significant portion of the internet, could we see further attacks exploiting this vulnerability? What should website operators do immediately to protect their systems, and should ordinary internet users be concerned about their data? Further attacks are possible, particularly against systems that remain unpatched or exposed. Website operators should apply the relevant security updates, check whether their PHP applications are vulnerable, and review logs for suspicious activity dating back to October 17. They should also restrict access and investigate signs of compromise. Ordinary users do not need to panic, but they should keep their accounts protected with unique passwords and multi-factor authentication where available. Whether personal data is at risk depends on which services they use and whether those systems were compromised. AI-assisted tools are increasingly being used to analyze code and identify vulnerabilities. How much of a role could artificial intelligence play in helping attackers discover and exploit flaws like PHP2Shell, and can defenders use the same technology to their advantage? AI can help analyze code, identify suspicious patterns and speed up the process of turning a vulnerability into a working exploit. This lowers some of the technical barriers for attackers and may shorten the time between discovering a flaw and exploiting it. However, AI is not the only factor, and we should not assume that every attack is AI-driven. Defenders can use the same capabilities to review code, prioritize vulnerabilities, analyze logs and detect suspicious behavior. The real advantage comes from combining AI with reliable data, skilled security teams and effective response processes. This case shows that attackers may exploit a vulnerability before a patch is available. Does this mean traditional vulnerability management is no longer enough, and how should organizations rethink their security strategy? Traditional vulnerability management remains essential, but patching alone is not enough when attackers may act before a fix becomes available. Organizations need to know which internet-facing systems they operate, understand their exposure and have additional controls in place. These include limiting access to vulnerable services, monitoring suspicious activity, applying temporary mitigations and preparing incident response procedures. They should also investigate whether systems were targeted before the vulnerability was disclosed. The goal is to reduce the opportunity for exploitation and detect attacks quickly, even when a patch is not yet available. Below is another interview I gave to TRT World discussing critical PHP vulnerabilities, the risks they pose to web servers, and the growing number of exploitation attempts. I explain why rapid patching and effective security measures are essential to minimize potential damage. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, newsletter)
U.S. Cybersecurity and Infrastructure Security Agency (CISA) adds Collabora Online flaw to its Known Exploited Vulnerabilities catalog. The U.S. Cybersecurity and Infrastructure Security Agency (CISA) added a Collabora Collabora Online – Built-in CODE Server flaw, tracked as CVE-2026-110447 (CVSS score of 9.2), to its Known Exploited Vulnerabilities (KEV) catalog. Collabora Online – Built-in CODE Server is an app for Nextcloud that lets you open, edit and collaborate on documents, spreadsheets and presentations directly in your browser, without needing Microsoft Office installed on your computer. It is based on Collabora Online and LibreOffice technology. CVE-2026-110447 is a critical OS command injection flaw in Nextcloud’s proxy.php that affects Collabora Online Built-in CODE Server before 26.4.303. Unauthenticated attackers can execute commands when the built-in server is stopped. Standalone Collabora servers are not affected. Update immediately. In versions up to 26.4.302, proxy.php included request data in a Bash command without proper sanitization, allowing attackers to execute OS commands as the web server user. Exploitation is possible only when the local CODE server is stopped, such as during a restart, upgrade or crash. The script runs directly through the web server without loading Nextcloud’s code. Exploitation has been reported since September 2026, with attackers deploying PHP web shells and stealing configuration files containing credentials and application secrets. Three administrators reported the vulnerability on GitHub, while the first recorded attack dates back to September 10. The first attack was reported by a Nextcloud administrator whose servers had been compromised. Logs showed malicious requests on September 10 and 11, 2026, from the same IP, targeting proxy.php on version 26.4.302. The attackers deployed a PHP web shell and searched one server for credential stores and cryptocurrency wallets. Although reviewed logs showed no file exfiltration commands, data accessible to the web server account must be considered potentially exposed. Two other administrators reported similar incidents, but none found evidence of root access. After updating to 26.4.303, one administrator recorded another attempt on September 14, but no new shell appeared. Project maintainer mmeeks urged users to update and remove leftover shx*.php files. The CVE record confirms exploitation in September and October 2026, but the total number of compromised servers remains unknown. The flaw affects only the Development Edition’s Built-in CODE Server deployment. According to Binding Operational Directive (BOD) 22-01: Reducing the Significant Risk of Known Exploited Vulnerabilities, FCEB agencies have to address the identified vulnerabilities by the due date to protect their networks against attacks exploiting the flaws in the catalog. Experts also recommend that private organizations review the Catalog and address the vulnerabilities in their infrastructure. CISA orders federal agencies to fix the flaw by October 26, 2026. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, CISA)
AI companies need usage data to align pricing with costs, improve products, identify churn risks, and grow revenue through informed decisions. The AI Paradox There is a paradox: AI companies exist to extract intelligence from data, yet many have almost no visibility into how their own software is being used. They design complex models, introduce their product, set a price, and then hope that customers renew their contracts. In a space as fast-paced as AI, such a strategy is no longer safe. Without usage as a guide, price decisions are made on assumptions rather than facts. Product roadmaps are driven by story, not by usage. Customer success teams learn about customer churn when renewal dates are approaching. In reality, usage intelligence has become one of the most important signals in an AI business, guiding everything from pricing strategy to product development and long-term monetization. Why AI Changes the Stakes for Usage Data AI changes the economics of software and, with it, the relevance of usage visibility. The economics of existing software products are linear in cost, whereas those of AI products are not. Compute, energy consumption, as well as third-party model licenses, can all be material variable costs. If usage increases rapidly (through enterprise adoption, agents, or workflows), the cost can grow faster than the revenue generated if pricing is not aligned with consumption. The opposite scenario is just as dangerous. If customers are not using key capabilities, churn may be approaching long before a renewal conversation begins. Research shows the extent of this visibility gap. For AI vendors, visibility is important on the commercial side, too. They need to know how customers are using the AI capabilities they sell. IDC research found that 48% of software buyers want better visibility into their usage. The pace of change is also a concern, with 70% ranking rapid change in the AI ecosystem among their top three AI-related security risks. Pricing, packaging, and business models must evolve at the same pace, and that requires reliable usage intelligence. What Usage Intelligence Actually Looks Like Of all the capabilities that make up a software monetization strategy, usage intelligence is the one most commonly treated as optional — and the one that most consistently separates companies that adapt from those that don’t. It is the feedback loop that connects real-world product consumption back to the decisions that shape pricing, packaging, and product direction. At the instrumentation layer, usage intelligence starts with telemetry data. This includes activation events, entitlements consumed, feature-level data, daily and monthly active users, and time-to-value metrics that track how quickly customers get value from the product. Thales Sentinel can also collect usage data from on-premises, offline, and disconnected environments, so vendors are not limited to tracking always-connected software. The operational layer is where all the telemetry data is made actionable. Usage dashboards in CRM systems enable account teams to see how customers use the software. Health scores can even detect reduced engagement well before any risk of renewal is seen. The enforcement layer makes sure that usage is consistent with contract rights. This is particularly important for consumption-based or token-based pricing schemes. Tracking accuracy is essential for determining customer fairness and vendor revenue. Finally, there is the feedback loop. The insights from usage need to flow back to those responsible for pricing, packaging, product development, and customer success. Without the feedback loop, the data is just more information. Pricing specialists have long argued for incremental experimentation. Research from Simon-Kucher reveals that companies that make frequent, data-informed pricing adjustments tend to achieve stronger growth than those that depend on static pricing models. Usage intelligence provides the evidence required to make those adjustments with confidence. How Usage Data Enables Multiple Business Models Business model agility is increasingly becoming a competitive advantage for AI companies, yet flexible business models cannot exist without trustworthy usage data beneath them. Consumption-based pricing, outcome-based pricing, token models, and hybrid subscription structures all depend on accurate measurement of how customers use the product. There is demand for these models, too. IDC research found that 45% of software buyers prefer usage-based models. In practice, most AI companies adopt a gradual sequence. They begin with subscription licensing to establish predictable recurring revenue. As adoption grows, they instrument feature usage and engagement patterns. That data then enables the introduction of consumption or token-based layers tied to high-value AI capabilities. One AI audio-recognition company did just that. It moved from perpetual licensing to several subscription tiers using Thales Sentinel. Its usage data showed which features customers used most, which helped the company decide how to structure those tiers without making changes to the core technology. Another AI recognition vendor delivering SDKs for embedded systems took a different approach using Sentinel. Their trial licenses expire after a defined number of executions instead of after a fixed time period. This usage-based trial model demonstrates genuine customer interest, giving them a clearer indicator of product-market fit than a simple time-limited evaluation would. Both examples show that usage intelligence transforms monetization strategies from guesswork into evidence-based decision-making. From Data to Decision: Three Practical Applications The real value of usage intelligence lies in informing concrete business decisions. Preventing churn is one of the most immediate uses. Feature-level engagement metrics can detect declining usage several months before a renewal date. This enables customer success teams to step in and show the value or introduce underutilized features, preventing a customer from leaving. Upsell and expansion opportunities can also show up in the usage data. Seat utilization may show that a team is close to capacity and needs more licenses. Feature usage can show when a customer is getting enough value from certain capabilities to justify moving to a higher tier or adding consumption-based features. Usage data can also inform the product roadmap. Rather than relying on assumptions about what customers want, AI companies can see which features people use and which get little attention. This is key in a market full of similar AI capabilities. Companies need to know which parts of their product customers value and are willing to pay for. There is also a need for the collection of usage intelligence to be privacy-conscious. For vendors operating under frameworks such as GDPR or the EU’s AI Act, it is necessary to design telemetry systems that prioritize aggregated data collection over personal data collection whenever possible. The Organizational Challenge However, technology alone is not enough to create usage intelligence. Businesses must also ensure that the intelligence is available to those who can act on it. Usage intelligence only delivers value if it reaches the people who can act on it. Pricing teams need consumption data to make confident adjustments to their models. Product teams need feature engagement data to inform roadmap decisions rather than rely on assumptions. Sales teams need account-level signals to time their conversations correctly. Customer success teams need early warning indicators to intervene before disengagement becomes churn. Finance teams need usage trends to build credible revenue forecasts. Getting that data to all of those functions consistently and in a usable form requires intentional data architecture and a shared organizational commitment to treating monetization as a cross-functional capability rather than a single team’s responsibility. This becomes harder as companies add more AI products. If usage data is split across separate products, teams may struggle to see how a customer is using the wider portfolio. Bringing the data together can show where products are being heavily used, where adoption is low, and where there may be room to expand an account. Building Systems Around Innovation The AI companies that sustain long-term commercial success are the ones who built a system around it that can learn, adapt, and improve as markets shift and customer needs evolve. Usage intelligence is what makes that system adaptive. Without it, pricing decisions are made on assumptions, packaging tiers are defined by intuition, and churn arrives without warning. With it, every commercial decision — what to charge, how to package, what to build next, which customers need attention — is grounded in evidence rather than expectation. In an industry defined by rapid innovation, the AI companies that listen to their own usage data will be the ones best positioned to turn experimentation into sustainable growth. About the Author: Kirsten Doyle has been in the technology journalism and editing space for nearly 24 years, during which time she has developed a great love for all aspects of technology, as well as words themselves. Her experience spans B2B tech, with a lot of focus on cybersecurity, cloud, enterprise, digital transformation, and data centre. Her specialties are in news, thought leadership, features, white papers, and PR writing, and she is an experienced editor for both print and online publications. She is also a regular writer at Bora. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, artificial intelligence)
U.S. Cybersecurity and Infrastructure Security Agency (CISA) adds Arista VeloCloud Orchestrator flaw to its Known Exploited Vulnerabilities catalog. The U.S. Cybersecurity and Infrastructure Security Agency (CISA) added a critical Arista VeloCloud Orchestrator flaw, tracked as CVE-2026-114625 (CVSS score of 9.4), to its Known Exploited Vulnerabilities (KEV) catalog. VeloCloud Orchestrator (VCO) is the central management system for VMware SD-WAN, a technology that helps companies securely connect offices, data centers, cloud services, and remote sites over wide-area networks. It is now associated with Arista Networks, which acquired VMware’s SD-WAN business. The orchestrator gives network administrators a central place to configure, monitor, and manage the network. The flaw is a SQL Injection issue that affects on-premises VeloCloud Orchestrator (VCO). It allows an authenticated user to gain operator privileges and impersonate a local superuser operator account. This could give a remote attacker access to internal functions that should not be remotely available, potentially compromising the system and the data it manages. Hosted VCO versions, including Dedicated, were also affected but have already been patched. “VeloCloud Orchestrator (VCO) on-prem has a security issue where this issue may allow a remote attacker to access privileged internal functionality and impact the VCO host. Successful exploitation may compromise the confidentiality, integrity, and availability of the orchestrator and data managed by the orchestrator.” reads the advisory. “On an affected system, any authenticated user can gain operator privileges and masquerade as a local “superuser operator” user. This includes access to functionality that is intended for internal use only and which is not intended to be remotely accessible.” VeloCloud Orchestrator (VCO) is vulnerable by default. An attacker needs access to its web interface and a valid account. Even an account with the lowest permission level, Enterprise Read Only, is enough. No configuration change can prevent this exposure. Administrators should check web access logs for unusual requests, encoded text, attempts to access internal services, or an unusually high number of requests. They should also block these IP addresses linked to attacks: 74.82.197.86 38.54.50.151 If an attack is suspected, administrators should save web, application, system and database logs, along with relevant file timestamps, before starting recovery, if possible. According to Binding Operational Directive (BOD) 22-01: Reducing the Significant Risk of Known Exploited Vulnerabilities, FCEB agencies have to address the identified vulnerabilities by the due date to protect their networks against attacks exploiting the flaws in the catalog. Experts also recommend that private organizations review the Catalog and address the vulnerabilities in their infrastructure. CISA orders federal agencies to fix the flaw by October 26, 2026. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, CISA)
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