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Anthropic VS code extension on Cursor backdoored for nearly 12 hours
An official extension for Anthropic’s Claude model was backdoored and threatened as many as 5,000 developers' machines, multiple sources reported Friday. Anthropic so far has yet to warn customers of the incident.
The compromised package was a VS Code extension available in the marketplace of Cursor, a maker of AI-assisted developer tools, the company said Friday. The malicious version, 2.1.313, subsequently affected “at most 5,000 users,” presumably when they either downloaded it or their systems automatically fetched and installed it. Anthropic pushed version 2.1.314 several hours after the previous version became available on Cursor, according to independent researcher Kevin Beaumont. Both Beaumont and the CTO and co-founder of security firm Phorian said that version 2.1.313 was distributed through Anthropic’s official account on Cursor. So far, neither Cursor nor Anthropic has explained how the attackers gained control of the account.
In search of cloud credentials“It was a supply-chain compromise where the attacker gained access to the official distribution channel,” Phorian CTO and co-founder Luke Roberts told Ars. “The malicious version 2.1.313 was posted to the official Anthropic account, effectively superseding 2.1.312. Extensions auto-update in Cursor by default, but users can configure this in settings.” Phorian has more details here.
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Smplify wants a human checkpoint between AI agents and your device fleet
One of the great things about Apple device management solutions is that the market for them is growing. Another is that because no two enterprises are alike, there is scope to bring different offerings to the market. I spoke with Ben Greiner, co-founder and COO of Smplify, a new-to-market device management vendor, to find out what his company provides to IT.
Smplify, which just announced $1m in pre-seed funding, offers what could be described as a headless management tool: everything it does is available through the API and CLI. In use, that means you can build it and wield it from within the tools you already use, Greiner explained.
He’s building the company with Preetham Gurram, known in device management circles for his work at MobileIron, SOTI, Automox, Addigy, Scalefusion, and Apple, where he contributed to Apple’s core MDM platforms and zero-touch enrollment at scale.
So, who needs this?“Device management still assumes a person is watching,” said Greiner. “Admins already automate with scripts and pipelines, and now AI agents are showing up that can act on a fleet at machine speed.”
The challenge for IT is that AI is beginning to take actions, rather than suggest them. That means IT must put systems in place to manage and audit the actions AI takes. “Enterprises that win won’t be the ones with the smartest agents; they’ll be the ones that can say exactly what each agent is allowed to do and prove what it did,” he said.
That’s a fair assessment of how things stand. OneTrust’s 2026 AI-ready governance report found that 87% of organizations are encouraging the use of AI agents, but only 47% have clear governance and controls in place. That’s a problem waiting for a disaster.
A recent report from Gartner predicts that 40% of enterprises will demote or decommission autonomous AI agents in the coming months (“by 2027”) because of governance gaps detected only after incidents take place. Patching those gaps is expected to become a big business.
Who watches the watchmen?Once agents can submit changes at lightning speed, who can approve them? How widely deployed can those changes be? The risk is “an agent with the right key can wipe thousands of laptops before anyone notices,” Greiner told me.
This is a matter of AI governance and is something I know is in the thoughts of leaders at other device management companies, including Jamf and Fleet.
“AI is happening whether organizations know it or not. That’s the problem. You can try to block it, but that’s very hard to do well. It’s far better to build visibility and governance around it,” Jamf CEO Beth Tschida told me earlier this year. Jamf launched its own AI Governance suite in July, focused on AI tool discovery, policy enforcement, and reporting.
The Smplify approach puts some of these decisions into the management workflow itself. “Preetham calls it the last-mile control plane: the final checkpoint between what an agent decides and what actually happens on a device,” Greiner said.
What are the risks of unmanaged AI?While most of the conversation is focused on the risk of data leakage or malware, the other risk is lack of accountability. What if an agent gets bad instructions or hallucinates an inappropriate solution to a problem, and then pushes a destructive change across the fleet? By then it’s too late to figure out why it happened and becomes a potentially costly damage limitation exercise.
Fleet CEO Mike McNeil pointed out that part of the risk lies in the difficulty and cost of recovery after an incident. “I’d frame risk by two things: how much privilege the code runs with and how hard recovery is,” he said, noting the risk of scripts running at root, which can take full control of the machine to the extent that reversion can’t undo what’s done.
Greiner thinks the way to minimize the impact of such damage is to create strong rules and boundaries, and to ensure any risky actions are held back pending human approval. The agent can see a problem and create a solution, but can’t apply that fix until IT gives it the go-ahead. It’s very like how human IT works, only now it’s the machine that must report to the boss. Every change is logged with who asked for it, the intent behind it, and the person or policy that approved it.
Creating the opportunity spaceSmplify has built its own platform to help manage devices, including AI management. That platform leans into the native protocols of the platforms it supports, naturally including Apple’s Declarative Device Management (DDM).
“Admins describe what should be true of their devices, and Smplify keeps it true. If a device drifts from that intent, because a setting changed or an update was missed, the platform notices and brings it back in line, automatically or with an admin’s approval, depending on the rules they’ve set,” Greiner said.
He explained how many IT teams use GitOps to “bring discipline” to device management: configuration lives in GitHub, changes go through pull requests, and there’s a history of what happened. It works, but it adds new layers to the management task. He claims his solution has that discipline (versioned intent, review, and approval, and a full history) built in.
Boundaries, Apple and DDMIn the end, I get the feeling that AI management will embrace some of the ideas put in place with Apple DDM. If you think about it, DDM lets IT define a state and leaves it to the tech to work within that definition, and that same sense of boundary setting may be part of the future for AI in IT. AI will be given agency within limited boundaries.
Greiner pointed out, “Apple has also been giving admins controls over Apple Intelligence features, and I expect that to keep expanding as businesses want a say in which AI runs on company devices. Apple’s privacy stance also suits governed AI well: do things on-device where possible and keep a clear line around what leaves it.”
There is one more thing. Because Smplify is an MDM platform while also being API-first, Greiner explained that software companies can offer native device management inside their own products, under their own name, using his company’s solution.
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