On Tuesday, eBay updated its User Agreement to explicitly ban third-party “buy for me” agents and AI chatbots from interacting with its platform without permission, first spotted by Value Added Resource. On its face, a one-line terms of service update doesn’t seem like major news, but what it implies is more significant: The change reflects the rapid emergence of what some are calling “agentic commerce,” a new category of AI tools designed to browse, compare, and purchase products on behalf of users.

eBay’s updated terms, which go into effect on February 20, 2026, specifically prohibit users from employing “buy-for-me agents, LLM-driven bots, or any end-to-end flow that attempts to place orders without human review” to access eBay’s services without the site’s permission. The previous version of the agreement contained a general prohibition on robots, spiders, scrapers, and automated data gathering tools but did not mention AI agents or LLMs by name.

At first glance, the phrase “agentic commerce” may sound like aspirational marketing jargon, but the tools are already here, and people are apparently using them. While fitting loosely under one label, these tools come in many forms.

OpenAI first added shopping features to ChatGPT Search in April 2025, allowing users to browse product recommendations. By September, the company launched Instant Checkout, which lets users purchase items from Etsy and Shopify merchants directly within the chat interface. (In November, eBay CEO Jamie Iannone suggested the company might join OpenAI’s Instant Checkout program in the future.)

https://arstechnica.com/information-technology/2026/01/ebay-bans-illicit-automated-shopping-amid-rapid-rise-of-ai-agents/

To work around those rules, the Humanizer skill tells Claude to replace inflated language with plain facts and offers this example transformation:

Before: “The Statistical Institute of Catalonia was officially established in 1989, marking a pivotal moment in the evolution of regional statistics in Spain.”

After: “The Statistical Institute of Catalonia was established in 1989 to collect and publish regional statistics.”

Claude will read that and do its best as a pattern-matching machine to create an output that matches the context of the conversation or task at hand.

An example of why AI writing detection fails

Even with such a confident set of rules crafted by Wikipedia editors, we’ve previously written about why AI writing detectors don’t work reliably: There is nothing inherently unique about human writing that reliably differentiates it from LLM writing.

One reason is that even though most AI language models tend toward certain types of language, they can also be prompted to avoid them, as with the Humanizer skill. (Although sometimes it’s very difficult, as OpenAI found in its yearslong struggle against the em dash.)

Also, humans can write in chatbot-like ways. For example, this article likely contains some “AI-written traits” that trigger AI detectors even though it was written by a professional writer—especially if we use even a single em dash—because most LLMs picked up writing techniques from examples of professional writing scraped from the web.

Along those lines, the Wikipedia guide has a caveat worth noting: While the list points out some obvious tells of, say, unaltered ChatGPT usage, it’s still composed of observations, not ironclad rules. A 2025 preprint cited on the page found that heavy users of large language models correctly spot AI-generated articles about 90 percent of the time. That sounds great until you realize that 10 percent are false positives, which is enough to potentially throw out some quality writing in pursuit of detecting AI slop.

Taking a step back, that probably means AI detection work might need to go deeper than flagging particular phrasing and delve (see what I did there?) more into the substantive factual content of the work itself.

https://arstechnica.com/ai/2026/01/new-ai-plugin-uses-wikipedias-ai-writing-detection-rules-to-help-it-sound-human/

Rackspace’s new pricing for its email hosting services is “devastating,” according to a partner that has been using Rackspace as its email provider since 1999.

In recent weeks, Rackspace updated its email hosting pricing. Its standard plan is now $10 per mailbox per month. Businesses can also pay for the Rackspace Email Plus add-on for an extra $2/mailbox/month (for “file storage, mobile sync, Office-compatible apps, and messaging”), and the Archiving add-on for an extra $6/mailbox/month (for unlimited storage).

As recently as November 2025, Rackspace charged $3/mailbox/month for its Standard plan, and an extra $1/mailbox/month for the Email Plus add-on, and an additional $3/mailbox/month for the Archival add-on, according to the Internet Archive’s Wayback Machine.

Rackspace’s reseller partners have been especially vocal about the impacts of the new pricing.

In a blog post on Thursday, web hosting service provider and Rackspace reseller Laughing Squid said Rackspace is “increasing our email pricing by an astronomical 706 percent, with only a month-and-a half’s notice.”

Laughing Squid founder Scott Beale told Ars Technica that he received the “devastating” news via email on Wednesday. The last time Rackspace increased Laughing Squid’s email prices was by 55 percent in 2019, he said.

“The price increase has a major impact on the ability to make money due to the fact that email is now our largest expense, and we were only given a month-and-a-half notice,” Beale told Ars.

Online, there are reports of Rackspace partners being quoted email pricing increases of 110 percent to nearly 500 percent. The reports say that the new, higher-per-mailbox quotes don’t include volume pricing discounts. Beale noted that Laughing Squid’s quote doesn’t include discounts that the company previously received.

https://arstechnica.com/information-technology/2026/01/rackspace-raises-email-hosting-prices-by-as-much-as-706-percent/

Financial pressures and a changing tune

OpenAI’s advertising experiment reflects the enormous financial pressures facing the company. OpenAI does not expect to be profitable until 2030 and has committed to spend about $1.4 trillion on massive data centers and chips for AI.

According to financial documents obtained by The Wall Street Journal in November, OpenAI expects to burn through roughly $9 billion this year while generating $13 billion in revenue. Only about 5 percent of ChatGPT’s 800 million weekly users pay for subscriptions, so it’s not enough to cover all of OpenAI’s operating costs.

Not everyone is convinced ads will solve OpenAI’s financial problems. “I am extremely bearish on this ads product,” tech critic Ed Zitron wrote on Bluesky. “Even if this becomes a good business line, OpenAI’s services cost too much for it to matter!”

OpenAI’s embrace of ads appears to come reluctantly, since it runs counter to a “personal bias” against advertising that Altman has shared in earlier public statements. For example, during a fireside chat at Harvard University in 2024, Altman said he found the combination of ads and AI “uniquely unsettling,” implying that he would not like it if the chatbot itself changed its responses due to advertising pressure. He added: “When I think of like GPT writing me a response, if I had to go figure out exactly how much was who paying here to influence what I’m being shown, I don’t think I would like that.”

An example mock-up of an advertisement in ChatGPT provided by OpenAI.

Along those lines, OpenAI’s approach appears to be a compromise between needing ad revenue and not wanting sponsored content to appear directly within ChatGPT’s written responses. By placing banner ads at the bottom of answers separated from the conversation history, OpenAI appears to be addressing Altman’s concern: The AI assistant’s actual output, the company says, will remain uninfluenced by advertisers.

Indeed, Simo wrote in a blog post that OpenAI’s ads will not influence ChatGPT’s conversational responses and that the company will not share conversations with advertisers and will not show ads on sensitive topics such as mental health and politics to users it determines to be under 18.

“As we introduce ads, it’s crucial we preserve what makes ChatGPT valuable in the first place,” Simo wrote. “That means you need to trust that ChatGPT’s responses are driven by what’s objectively useful, never by advertising.”

https://arstechnica.com/information-technology/2026/01/openai-to-test-ads-in-chatgpt-as-it-burns-through-billions/

Microsoft released NTLMv1 in the 1980s with the release of OS/2. In 1999, cryptanalyst Bruce Schneier and Mudge published research that exposed key weaknesses in the NTLMv1 underpinnings. At the 2012 Defcon 20 conference, researchers released a tool set that allowed attackers to move from untrusted network guest to admin in 60 seconds, by attacking the underlying weakness. With the 1998 release of Windows NT SP4 in 1998, Microsoft introduced NTLMv2, which fixed the weakness.

Organizations that rely on Windows networking aren’t the only laggards. Microsoft only announced plans to deprecate NTLMv1 last August.

Despite the public awareness that NTLMv1 is weak, “Mandiant consultants continue to identify its use in active environments,” the company said. “This legacy protocol leaves organizations vulnerable to trivial credential theft, yet it remains prevalent due to inertia and a lack of demonstrated immediate risk.”

The tables first assist attackers in providing per-byte hash results with the known plaintext challenge 1122334455667788. Because Net-NTLM hashes are generated with the user’s password and the challenge, a known plaintext attack, it becomes trivial with these tables to compromise the accont. Typically tools including Responder, PetitPotam, and DFSCoerce are involved in attacks against Net-NTLM. Typically tools including Responder, PetitPotam, and DFSCoerce are involved.

In a thread on Mastodon, researchers and admins applauded the move, because they said it would give them added ammunition when trying to convince decision makers to make the investments to move off the insecure function.

“I’ve had more than one instance in my (admittedly short) infosec career where I’ve had to prove the weakness of a system and it usually involves me dropping a sheet of paper on their desk with their password on it the next morning,” one person said. “These rainbow tables aren’t going to mean much for attackers as they’ve likely already got them or have far better methods, but where it will help is in making the argument that NTLMv1 is unsafe.”

The Mandiant post provides basic steps required to move off of NTLMv1. It links to more detailed instructions.

“Organizations should immediately disable the use of Net-NTLMv1,” Mandiant said. Organizations that get hacked because they failed to heed will have only themselves to blame.

https://arstechnica.com/security/2026/01/mandiant-releases-rainbow-table-that-cracks-weak-admin-password-in-12-hours/

TSMC posted net income of NT$505.7 billion (about $16 billion) for the quarter, up 35 percent year over year and above analyst expectations. Revenue hit $33.7 billion, a 25.5 percent increase from the same period last year. The company expects nearly 30 percent revenue growth in 2026 and plans to spend between $52 billion and $56 billion on capital expenditures this year, up from $40.9 billion in 2025.

Checking with the customers’ customers

Wei’s optimism stands in contrast to months of speculation about whether the AI industry is in a bubble. In November, Google CEO Sundar Pichai warned of “irrationality” in the AI market and said no company would be immune if a potential bubble bursts. OpenAI’s Sam Altman acknowledged in August that investors are “overexcited” and that “someone” will lose a “phenomenal amount of money.”

But TSMC, which manufactures the chips that power the AI boom, is betting the opposite way, with Wei telling analysts he spoke directly to cloud providers to verify that demand is real before committing to the spending increase.

“I want to make sure that my customers’ demand are real. So I talked to those cloud service providers, all of them,” Wei said. “The answer is that I’m quite satisfied with the answer. Actually, they show me the evidence that the AI really helps their business.”

The earnings report landed the same day the US and Taiwan finalized a trade agreement that cuts tariffs on Taiwanese goods to 15 percent, down from 20 percent. The deal commits Taiwanese companies to $250 billion in direct US investment, and TSMC is accelerating the expansion of its Arizona chip fabrication facilities to match.

https://arstechnica.com/ai/2026/01/tsmc-says-ai-demand-is-endless-after-record-q4-earnings/

The cost of “free” knowledge

The push for paid licensing follows years of rising infrastructure costs as AI companies scraped Wikipedia content at an industrial scale. In April 2025, the foundation reported that bandwidth used for downloading multimedia content had grown 50 percent since January 2024, with bots accounting for 65 percent of the most expensive requests to core infrastructure despite making up just 35 percent of total pageviews.

By October, the Wikimedia Foundation disclosed that human traffic to Wikipedia had fallen approximately 8 percent year over year after the organization updated its bot-detection systems and discovered that much of what appeared to be human visitors were actually automated scrapers built to evade detection.

The traffic decline threatens the feedback loop that has sustained Wikipedia for a quarter century: Readers visit, some become editors or donors, and the content ostensibly improves. But today, many AI chatbots and search engine summaries answer questions using Wikipedia content without sending users to the site itself.

Meanwhile, the foundation’s own experiments with generative AI have met resistance from the volunteer editors who maintain the site. In June, Wikipedia paused a pilot program for AI-generated article summaries after editors called it a “ghastly idea” and warned it could undermine trust in the platform.

Wikipedia founder Jimmy Wales told The Associated Press that he welcomes AI models training on Wikipedia data. “I’m very happy personally that AI models are training on Wikipedia data because it’s human curated,” Wales said. “I wouldn’t really want to use an AI that’s trained only on X, you know, like a very angry AI.” But he drew a line at free access: “You should probably chip in and pay for your fair share of the cost that you’re putting on us.”

https://arstechnica.com/ai/2026/01/wikipedia-will-share-content-with-ai-firms-in-new-licensing-deals/

On Tuesday, Bandcamp announced on Reddit that it will no longer permit AI-generated music on its platform. “Music and audio that is generated wholly or in substantial part by AI is not permitted on Bandcamp,” the company wrote in a post to the r/bandcamp subreddit. The new policy also prohibits “any use of AI tools to impersonate other artists or styles.”

The policy draws a line that some in the music community have debated: Where does tool use end and full automation begin? AI models are not artists in themselves, since they lack personhood and creative intent. But people do use AI tools to make music, and the spectrum runs from using AI for minor assistance (cleaning up audio, suggesting chord progressions) to typing a prompt and letting a model generate an entire track. Bandcamp’s policy targets the latter end of that spectrum while leaving room for human artists who incorporate AI tools into a larger creative process.

The announcement emphasized the platform’s desire to protect its community of human artists. “The fact that Bandcamp is home to such a vibrant community of real people making incredible music is something we want to protect and maintain,” the company wrote. Bandcamp asked users to flag suspected AI-generated content through its reporting tools, and the company said it reserves “the right to remove any music on suspicion of being AI generated.”

As generative AI tools make it trivial to produce unlimited quantities of music, art, and text, this author once argued that platforms may need to actively preserve spaces for human expression rather than let them drown in machine-generated output. Bandcamp’s decision seems to move in that direction, but it also leaves room for platforms like Suno, which primarily host AI-generated music.

Two platforms, two approaches, one flood

The policy contrasts with Spotify, which explicitly permits AI-generated music, although its users have expressed frustration with an influx of AI-generated tracks created by tools like Suno and Udio. Some of those AI music issues predate the latest tools, however. In 2023, Spotify removed tens of thousands of AI-generated songs from distributor Boomy after discovering evidence of artificial streaming fraud, but the flood just kept coming.

https://arstechnica.com/ai/2026/01/bandcamp-bans-purely-ai-generated-music-from-its-platform/

RAM prices have soared, which is bad news for people interested in buying, building, or upgrading a computer this year, but it’s likely good news for people exasperated by talk of so-called AI PCs.

As Ars Technica has reported, the growing demands of data centers, fueled by the AI boom, have led to a shortage of RAM and flash memory chips, driving prices to skyrocket.

In an announcement today, Ben Yeh, principal analyst at technology research firm Omdia, said that in 2025, “mainstream PC memory and storage costs rose by 40 percent to 70 percent, resulting in cost increases being passed through to customers.”

Overall, global PC shipments increased in 2025, according to Omdia, (which pegged growth at 9.2 percent compared to 2024), and IDC, (which today reported 9.6 percent growth), but analysts expect PC sales to be more tumultuous in 2026.

“The year ahead is shaping up to be extremely volatile,” Jean Philippe Bouchard, research VP with IDC’s worldwide mobile device trackers, said in a statement.

Both analyst firms expect PC makers to manage the RAM shortage by raising prices and by releasing computers with lower memory specs. IDC expects price hikes of 15 to 20 percent and for PC RAM specs to “be lowered on average to preserve memory inventory on hand,” Bouchard said. Omdia’s Yeh expects “leaner mid to low-tier configurations to protect margins.”

“These RAM shortages will last beyond just 2026, and the cost-conscious part of the market is the one that will be most impacted,” Jitesh Ubrani, research manager for worldwide mobile device trackers at IDC, told Ars via email.

IDC expects vendors to “prioritize midrange and premium systems to offset higher component costs, especially memory.”

https://arstechnica.com/gadgets/2026/01/the-ram-shortages-silver-lining-less-talk-about-ai-pcs/

To block the attack, OpenAI restricted ChatGPT to solely open URLs exactly as provided and refuse to add parameters to them, even when explicitly instructed to do otherwise. With that, ShadowLeak was blocked, since the LLM was unable to construct new URLs by concatenating words or names, appending query parameters, or inserting user-derived data into a base URL.

Radware’s ZombieAgent tweak was simple. The researchers revised the prompt injection to supply a complete list of pre-constructed URLs. Each one contained the base URL appended by a single number or letter of the alphabet, for example, example.com/a, example.com/b, and every subsequent letter of the alphabet, along with example.com/0 through example.com/9. The prompt also instructed the agent to substitute a special token for spaces.

Diagram illustrating the URL-based character exfiltration for bypassing the allow list introduced in ChatGPT in response to ShadowLeak.

Credit: Radware

ZombieAgent worked because OpenAI developers didn’t restrict the appending of a single letter to a URL. That allowed the attack to exfiltrate data letter by letter.

OpenAI has mitigated the ZombieAgent attack by restricting ChatGPT from opening any link originating from an email unless it either appears in a well-known public index or was provided directly by the user in a chat prompt. The tweak is aimed at barring the agent from opening base URLs that lead to an attacker-controlled domain.

In fairness, OpenAI is hardly alone in this unending cycle of mitigating an attack only to see it revived through a simple change. If the past five years are any guide, this pattern is likely to endure indefinitely, in much the way SQL injection and memory corruption vulnerabilities continue to provide hackers with the fuel they need to compromise software and websites.

“Guardrails should not be considered fundamental solutions for the prompt injection problems,” Pascal Geenens, VP of threat intelligence at Radware, wrote in an email. “Instead, they are a quick fix to stop a specific attack. As long as there is no fundamental solution, prompt injection will remain an active threat and a real risk for organizations deploying AI assistants and agents.”

https://arstechnica.com/security/2026/01/chatgpt-falls-to-new-data-pilfering-attack-as-a-vicious-cycle-in-ai-continues/