The rapid diffusion of AI globally and the pace at which AI is developing put us at a societal crossroads. The choices we’re making now will determine who has access to AI and the opportunity it affords. There is perhaps no more important tool than our education systems for addressing the uneven diffusion of AI we’re seeing currently: national adoption runs above 70% in countries such as the United Arab Emirates and falls to low single digits across much of sub-Saharan Africa, close to a tenfold difference.
The way we teach AI and learn with it will have long-lasting impacts on jobs, the workforce, and our broader economy. Learning Curves: Rethinking Education from Classrooms to Careers in an AI-Driven World is a collection of research-driven essays that can help guide those choices. This book brings together the body of work from the second cohort of Senior Fellows from the Microsoft AI Economy Institute (AIEI), a flagship think tank that produces research and convenes experts to generate insights into how AI is reshaping work, education, and the broader economy.
In Learning Curves, researchers consider how AI is reshaping the earliest stages of learning and work, from K–12 classrooms and community and technical colleges to college‑to‑work transitions and entry‑level jobs, and what it will take for that transformation to widen opportunity rather than deepen divides across institutions, communities, and countries.
Below, I share a few of my own reflections that informed my contributions to Learning Curves, a collaborative effort that wouldn’t have been possible without the truly talented, diverse cohort of researchers who contributed to this book.
Before delving into the specifics of how to incorporate AI in classrooms, we need to ask ourselves whether we’re teaching for knowledge, or for learning.
The book, the calculator, the personal computer, the internet, the search engine, and the smartphone all arrived in classrooms carrying real promise alongside the worry that they would hollow out young minds. Usually the truth landed somewhere in between, and where it landed depended less on the tool than on the choices the adults made about how to use it.
The fact is that the AI-native generation is already here, and its members are in classrooms around the world. More than half of US teenagers already use AI chatbots for schoolwork. I’ve personally seen the promise of AI as a force for good in education up close in my own classroom, where I teach a computer science class to elementary school students.
But of course, the good is only part of the story. We can’t shy away from the downsides of incorporating AI into classrooms. While AI can help with accessibility and individualized learning, it can also create over–reliance, contribute to student cheating, or prevent students from recognizing when information may be false.
The rapid deployment of AI in K–12 classrooms needs to come with a sober assessment of how that technology impacts all students. This assessment must go beyond the technology itself to encompass how students, teachers, parents, and society use AI.
If classrooms are where students learn how to think, teachers are the conduit through which this learning happens. In Learning Curves, Joseph Orero, Senior Researcher in AI at Strathmore University’s School of Computing and Engineering Science, posits that teachers aren’t resistant to AI in classrooms; they just need proper training to help them adequately adapt and teach their students critical skills. His research contribution explores game-based learning with AI-enabled African languages.
AI usage and adoption worldwide are also dependent on accessibility. Another chapter of the book looks at barriers and opportunities in Arabic education and finds that the primary barrier teachers encountered when introducing AI writing assistants into classrooms was Arabic digital literacy, particularly students’ typing ability.
Researchers often circled around a similar theme: there is no one-size-fits-all approach to developing AI competency; instead, such an approach must be sensitive to local knowledge and contextualized teaching and learning practices. This means that teachers, in turn, must have training that makes sense for the unique contexts in which their students are learning.
Frank Nagle, now Microsoft’s Chief AI Economist, Sarah Rodriguez, Associate Professor of Engineering Education at Virginia Tech, and other researchers in Learning Curves make the case that, in many ways, nontraditional pathways such as apprenticeships and two-year-degree programs, particularly those that are virtual, are more nimble and thus better able to adapt their curricula to the rapidly changing field of AI.
Education has never been about simply preparing people for the future of work so they can thrive in the labor market. When considered holistically, it is about teaching students not what to think but how to think. In our AI era, education is one of the core institutions through which the future of work will be built, distributed, and made more (or less) equitable. Successful AI integration remains human-centered by focusing on organizational change, durable human skills like empathy and judgment, strong employer partnerships, and learner needs.
As research from Laura Nuriski, Head of Program on the Future of Work at the Centre for European Policy Studies (CEPS), highlights, access to AI alone does not ensure successful integration. Technology transfer, data infrastructure, organizational readiness, and a human-centered approach to building and deploying AI are also key indicators of success.
Whether we’re talking about the classroom or the boardroom, it’s worth keeping in mind that AI tends to do the most good when it strengthens human capability and the most harm when it substitutes for it. That holds as true in a fourth- grade reading lesson as in a software team or a hospital ward.
The children in our schools deserve tools that serve their learning rather than stand in for it, and that is within our power to provide. Our most successful future with AI will be one that is human-centered, inclusive, and designed to help people thrive.
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Yesterday, two critical vulnerabilities were disclosed in PHP, the scripting language used by many websites and online services: CVE-2026-109618 and CVE-2026-109619. Attackers can exploit them to remotely execute commands on any server running PHP, with no authentication required. The exploit has been dubbed PHP2Shell.
The PHP security team announced an upcoming emergency update on October 20 and released patches fixing the vulnerabilities the following day.
We’ve already covered the technical details of these vulnerabilities and explained what companies and server administrators should do. You may have safely skipped that news because you don’t run any servers — but unfortunately, the issue is not limited to businesses.
Nearly 70% of websites run on PHP, including services we use every day: wikis, online stores, smart devices with web interfaces, home network-attached storage (NAS), smart-home controllers, and much more.
Today, we explain how these vulnerabilities could affect you personally and what you can do to reduce the risks.
The vulnerability allows an attacker to steal authentication tokens from server memory. These tokens essentially act like electronic passes — telling a website that the user has already signed in. As a result, an attacker may be able to access someone else’s account without entering a password or two-factor authentication code, putting messages, documents, delivery addresses, order histories, and other confidential information at risk.
If you have network-attached storage (NAS) or a video surveillance system at home that uses a vulnerable PHP version, it may also be at risk. Depending on what level of access they gain, attackers could potentially copy, delete or encrypt files they can access.
If an attacker gains access to a vulnerable website, they can use it in virtually any way they want: trick visitors into downloading a malicious file or clicking on a phishing link, display dangerous instructions, replace payment forms or login pages with malicious ones — the list goes on and on. As a result, someone visiting a legitimate website could not only lose access to their account, but also lose money or accidentally infect their device with malware.
Below are examples of services directly affected by the vulnerabilities.
Jeedom is a smart-home platform that lets users control lighting, sensors, heating, blinds and home IoT devices. Attackers could abuse this in many ways: they could disable the alarm, track when the homeowner is away, access video from the door intercom, and more.
The developers confirmed that the new vulnerability affects their application, and have already released an emergency update — Jeedom 4.6.2. Users need to run the update twice for it to work. The developers say a fully fixed version for home users will be released in the coming days.
As mentioned above, PHP is used by roughly 70% of websites. This doesn’t mean every one of them is vulnerable: it depends on the PHP version in use and whether the site owners have already updated it. Many government websites in Europe have already suspended operations because of the new vulnerability.
Unfortunately, a website may still be vulnerable even if it appears to be working normally. An attacker could potentially take control of any legitimate website whose server hasn’t been patched yet. They could fake payment or login pages, host malicious files, or persuade users to download an “urgent update” that is actually malware.
Ordinary users have no reliable way to check whether such instructions or files are safe, so be sure to use reliable anti-phishing and antivirus protection. If you suspect that your data may have been stolen, check the active sessions in your account settings. If you spot suspicious activity or devices you don’t recognize, sign out of all active sessions and change your password. Use a password manager — it can generate a truly strong, unique password that you won’t have to memorize yourself.
Bad news for gamers: some video games whose servers use PHP are also at risk. If you don’t want attackers to get hold of your accounts, be sure to update the passwords for your gaming platforms, stores and accounts.
To buy time for updates, some developers temporarily took their services offline. Final Fantasy XIV, Pokemon Champions, games from Bandai Namco Entertainment, Uma Musume: Pretty Derby, Granblue Fantasy, Shadowverse: Worlds Beyond, and many others went into emergency maintenance. Nintendo Switch Online and the GOG and Steam stores were also affected.
Unfortunately, there’ve also been more drastic consequences. Yesterday, the developers of World Quest announced that the game would shut down permanently after 15 years: it relied on outdated infrastructure that would have been extremely difficult and costly to fix. For the same reason, the mobile game Please Save My Pandemonium! shut down after more than ten years of operation.
“Home clouds” have become popular in recent years for good reason: many users prefer to keep backups of their data at home rather than online. A number of companies make NAS devices, and at least three — QNAP, Synology and ASUSTOR — have said the vulnerabilities affect their products. An update has also been released for Unraid, an operating system for home servers, network storage and media servers.
The manufacturer confirmed that the vulnerabilities affect several versions of its NAS operating systems — QTS and QuTS hero — as well as applications including QuMagie, Note Station 3 and certain versions of QVR Surveillance. A successful attack could put photos, documents, notes and camera recordings at risk.
At the time of publication of this blogpost, QNAP is still preparing updates, so the main priority is to temporarily disconnect NAS from the internet. QNAP recommends disabling port forwarding on the router — to prevent NAS from automatically opening ports — and allowing access to the management panel only from the home network or through a VPN.
Both vulnerabilities have been officially confirmed in PHP packages 7.3, 7.4, and 8.0–8.4, as well as in Mail Station and Synology Calendar. Fixes have already been released for PHP, starting from version 7.4, as well as for Mail Station and Synology Calendar. PHP 7.3 won’t be fixed. The company separately notes that the PHP component built into its operating system cannot be reached from outside the device, so the risk of attack is very low.
ASUSTOR also officially confirmed both vulnerabilities, and immediately removed PHP 7, 7.3, 7.4, and 8.1 packages from App Central. The company recommends immediately backing up your data, removing older PHP packages, and using PHP 8.3 or 8.4.
In today’s operating-system update, PHP was upgraded to version 8.4.27 with fixes for the vulnerabilities. The developers recommend that all users update to Unraid 7.3.4. Containers with their own PHP installation must be updated separately: the new PHP version in the operating system doesn’t replace PHP inside containers.
At the time of publication, we haven’t found public confirmation from other major manufacturers (such as TerraMaster, UGREEN, Buffalo, or Western Digital) that their devices are affected by these vulnerabilities — only user discussions on forums.
But the fact that only some NAS manufacturers have confirmed the problem so far doesn’t guarantee that your devices are safe — especially if they’re fairly old or come from a lesser-known or defunct manufacturer. In that case, first disconnect the devices from the internet while keeping them accessible only on the local network, and then investigate whether they’re vulnerable.
Nextcloud is a free, open-source platform for creating your own cloud storage, serving as an alternative to Google Drive, Dropbox, and Microsoft OneDrive. It lets you store and synchronize files across devices, share them with other users, and work with documents, photos, calendars and contacts. The data can be stored on your own server or NAS rather than on a third-party company’s servers.
If you store important data in Nextcloud, check how your cloud instance is configured. If you use Nextcloud All-in-One, update to version 14.4.1 where the vulnerability has already been fixed.
If your Nextcloud installation is configured differently, you need to update PHP yourself on the device or server.
What other risks can your home devices face? Read our articles:
Two critical vulnerabilities have been discovered in the popular PHP programming language. The vulnerabilities, identified as CVE-2026-109618 and CVE-2026-109619, allow attackers to remotely execute code on a server running PHP without authentication. The language’s development team has released updates for all supported branches, but the first attempts to exploit the vulnerabilities were observed even before the patches were published. The exploit has been named PHP2Shell.
The architectures of popular marketplaces, e-commerce platforms, and learning management systems (LMS) are written in PHP. In addition, PHP is used in various content management systems (CMS) such as WordPress, Drupal, Joomla, and so on, which power most websites on the internet.
In this blogpost, we discuss CVE-2026-109618 and CVE-2026-109619 in detail, and explain how companies can protect their infrastructure. Read the Securelist expert blog to learn how events surrounding these vulnerabilities unfolded before the patch was released.
According to PHP web site, versions prior to 8.2.35, 8.3.36, 8.4.27, and 8.5.12 are vulnerable to CVE-2026-109618 and CVE-2026-109619. There are no official fixes for older branches. According to unofficial reports, the vulnerabilities also affect PHP versions starting with 5.4.0.
Both vulnerabilities received a score of 9.2 on the CVSS v4.0 scale. They arise because, after a request is interrupted (for example, due to a memory shortage), PHP leaves invalid data in the memory buffer, and subsequently accesses it, allowing code to be executed on the server. One of the confirmed attack chains via CVE-2026-109619 exploits the `session.upload_progress` mechanism (which tracks file upload progress), which is enabled by default in PHP.
By exploiting these vulnerabilities, attackers can remotely execute code on the server with web server process privileges without authentication.
According to PHP developers, all installations of unpatched versions that process web requests are at risk, including PHP-FPM, Apache with mod_php, php-cgi, FrankenPHP, and LiteSpeed. The greatest risk lies with mod_php: researchers demonstrated an exploit for it in which an unauthenticated request triggers the attack even before the application code is executed.
We’ve compiled key recommendations from the PHP developers and experts at Kaspersky.
Only the immediate installation of patches will fully resolve the issue, but if that isn’t possible, it’s recommended to implement temporary measures. PHP developers provide step-by-step instructions for each vulnerability.
Authors: Yun Zheng Hu
Today Fox-IT is publicly releasing its full Cobalt Strike Beacon Corpus, containing 56,843 raw beacons and their parsed configurations, from 190,182 sightings collected from 30,604 unique IP addresses running a Team Server (the Cobalt Strike command-and-control server that beacons connect back to) between 4 July 2018 and 29 September 2026, over eight years of beacon data. The corpus is available on Hugging Face: https://huggingface.co/datasets/fox-srt/cobaltstrike-beacon-corpus
Back in March 2022 we published Mining Data from Cobalt Strike Beacons. That post covered 128,340 beacon sightings collected from July 2018 to February 2022, and it introduced our Python project dissect.cobaltstrike for parsing them.
Since then, public scanning for Team Servers has become routine, and Cobalt Strike has shipped versions 4.6 through 4.13. Researchers have regularly asked us for an updated dataset. And here it is, a large, consistent, long-running dataset for the infosec community to build on. The corpus includes the raw beacon payloads, not just our parsed output, so anyone can reproduce our results or improve on them.
We also see publishing this corpus as an act of preservation. C2 infrastructure is short-lived, as the median Team Server is reachable for just 14 days, and the beacons it serves vanish with it. Eight years of collection captures things that can no longer be observed today, like the waves of cracked 4.0 builds or the adoption of leaked versions. By publishing the raw beacons alongside the parsed data, we keep that record available for anyone to study, long after the servers themselves are gone.
The corpus is published on Hugging Face as two Parquet files:
| File | Size | Rows | Contents |
|---|---|---|---|
| beacons.parquet | 52 MB | 190,182 | Every sighting of a beacon, with collection metadata, network context and the parsed beacon configuration. |
| payloads.parquet | 9.7 GB | 56,843 | The raw beacon payloads, wrapped in CaRT as an extra safety layer so the samples are neutered until you deliberately unpack them. |
All beacons were downloaded directly from internet-facing Team Servers, mostly on TCP ports 80 and 443 (HTTP and HTTPS) and UDP port 53 (DNS), with a small number on other ports. We deliberately didn’t include samples from other sources such as VirusTotal, so the corpus reflects the Cobalt Strike landscape as it was visible on the internet.
The collection method matches our 2022 post. We fingerprint likely Team Servers on the internet, then request a beacon payload from each one using a URI that passes Cobalt Strike’s checksum8 check. Every beacon that comes back is parsed with dissect.cobaltstrike, which decodes the configuration block. The result is stored as a sighting.
Logindissect.cobaltstrike to parse the beacon and export the configurationNote that there might be some small gaps in the collection due to automation issues that we did not catch in time.
Most research only needs the beacons.parquet dataset. The payloads.parquet dataset containing raw beacon payloads is only required if you want to re-parse the beacons or look into the ones that failed parsing.
I’m a big fan of DuckDB (and SQLite), and over time I’ve become fond of SQL for querying data as well. DuckDB is very fast, and AI assistants are very good at writing SQL queries. These days, that beats hand-writing pandas code and the matching matplotlib charts. That’s why I recommend exploring the data with DuckDB, for example in a Jupyter notebook.
An example of using DuckDB to query the dataset on Hugging Face directly:
SELECT watermark,
count(*) AS sightings,
count(DISTINCT collected_from_ip) AS servers,
min(collected_on) AS first_seen,
max(collected_on) AS last_seen
FROM 'hf://datasets/fox-srt/cobaltstrike-beacon-corpus/data/beacons.parquet'
GROUP BY watermark
ORDER BY sightings DESC
LIMIT 20;
Take a look at our Jupyter notebook in the Hugging Face repository as a starting point. It contains every query and chart from the sections below, so you can rerun them or adapt them to your own research questions.
Here are a few quick results to show what the corpus can answer. They’re a starting point, not a full analysis. As with our 2022 post, we invite researchers to explore the data; see also “Research ideas” below.
Each Cobalt Strike release takes over from the last, but old versions linger. Cobalt Strike 4.0 dominated most of 2020, 4.1–4.2 drove the early 2021 peak of about 3,000 beacons a month, 4.3–4.4 led from mid-2021 through 2022, and 4.5–4.8 took over in 2023. Since 2024, 4.9 and 4.5–4.8 have shared the lead, while 4.10+ remains a small share. Volume has since dropped to around 200 beacons a month, partly because fewer servers stage their beacon, which brings us to the next graph.
Our collection relies on beacon staging, meaning a Team Server can serve its beacon as a downloadable payload to anyone who requests the right URI or DNS record. Operators can turn this off (the host_stage option in the Malleable C2 profile), and disabling it is common OPSEC advice. To measure how much this affects our beacon collection, we counted two numbers per month:
These are monthly totals, not a server-by-server match. On average, the Team Servers that handed out a beacon were only about 32% of those we fingerprinted, and that share has drifted down from around 40% in 2023 to 20–25% in 2026. In other words, because not every server hands out a beacon, the corpus shows only part of the Cobalt Strike landscape, and that part is getting smaller. Disabled beacon staging is the most likely reason, but not the only one. Servers can go offline between fingerprinting and download or block our scanners, and our fingerprint doesn’t catch every Team Server.
The dashed sections mark months when beacon collection wasn’t running, because of an automation error that went unnoticed for a while.
The median Team Server was reachable for 14 days. 35% were seen on a single day only, just 14% were still serving a beacon after three months, and only 2% after a year.
We identify a Team Server by its public key and C2 domains from the beacon configuration (or its IP address when the configuration contains no domains), so a server that moves to a new IP is still counted once. This allows us to measure how long a Team Server typically stays online. Identifying servers by public key alone or by ip:port gives almost the same result, a median lifetime of 14–15 days. These are first-to-last-sighting spans, so a server may have been online before our first and after our last sighting. Servers still active in the last 30 days are left out.
Most public scanning focuses only on HTTP(S) beacons, but we’ve also collected DNS beacons since 2020 (apart from the months when our automation broke). DNS beacons have declined much less steeply than HTTP(S) ones, perhaps because they get far less attention in public research and OPSEC advice, so fewer operators think to lock them down. After a peak in 2022, they have mostly hovered around 100 a month since 2024, with a median of 120 over the whole period.
The corpus also includes 128 unique beacons (0.23%) that we downloaded but couldn’t parse. Note that the corpus doesn’t contain HTML pages or other responses that were unlikely to be a beacon. We excluded those before publishing. At first glance, most are beacons with custom modifications that dissect.cobaltstrike can’t parse yet. And some payloads from the early years aren’t Cobalt Strike at all, but Metasploit Meterpreter payloads. We’ve deliberately left them in for researchers to analyse. You can find all unparsed beacons with: WHERE config_json IS NULL
The unparsed count used to be higher, but we managed to bring that down. We noticed some operators customised their beacon configs, for example by shuffling the order of the configuration settings or changing their type values, which broke our parser (and probably most others). The corpus helped us find these cases, so we made the config scanning of dissect.cobaltstrike independent of layout and added many other features and fixes along the way. See the dissect.cobaltstrike v1.3.0 release notes.
Some other research questions that could be answered using the corpus:
dissect.cobaltstrike. Figure out why.Eight years of Cobalt Strike beacons are now one download away on Hugging Face. Run your own queries, pick up one of the research ideas above or come up with your own, dig into the beacons we couldn’t parse, and share what you find.
Before you start, read the Limitations section on the dataset card. The raw payloads are real Cobalt Strike beacons, so handle them like any other malware sample.
