The Iran-linked hacking group MuddyWater (a.k.a. Seedworm, Static Kitten) launched a broad cyber-espionage campaign targeting at least nine high-profile organizations across multiple sectors and countries.

Among the victims are a major South Korean electronics manufacturer, government agencies, an international airport in the Middle East, industrial manufacturers in Asia, and educational institutions.

Researchers at Symantec say that the threat actor “spent a week inside the network of a major South Korean electronics manufacturer in February 2026.”

Symantec’s Threat Hunter Team believes the attacker was intelligence-driven, focusing on industrial and intellectual property theft, government espionage, and access to downstream customers or corporate networks.

Fortemedia and SentinelOne abuse

Seedworm’s campaign relied heavily on DLL sideloading, a common technique in which legitimate, signed software loads malicious DLLs.

Two of the binaries leveraged in the attack are ‘fmapp.exe,’ a legitimate Foremedia audio utility, and ‘sentinelmemoryscanner.exe,’ a legitimate SentinelOne component.

The malicious DLLs (fmapp.dll and sentinelagentcore.dll) contained ChromElevator, a commodity post-exploitation tool that steals data stored in Chrome-based browsers.

Symantec also found that PowerShell, used in previous Seedworm attacks, was still heavily used in the recent incidents, although the payloads were controlled through Node.js loaders rather than directly.

PowerShell was used to capture screenshots, conduct reconnaissance, fetch additional payloads, establish persistence, steal credentials, and create SOCKS5 tunnels.

Attack on a Korean firm

According to Symantec’s observations, the attack on the South Korean electronics manufacturer lasted between February 20 and 27. The researchers did not disclose the name of the targeted organization.

In the first stage, Seedworm performed host and domain reconnaissance, followed by antivirus enumeration via WMI, screenshot capture, and the download of additional malware.

Credential theft occurred via fake Windows prompts, registry hive theft (SAM/SECURITY/SYSTEM), and Kerberos ticket abuse tools.

Persistence was established through registry modifications, beaconing occurred at 90-second intervals, and sideloaded binaries were repeatedly relaunched to maintain access.

“The cadence is again consistent with implant-driven activity rather than continuous operator presence,” the researchers said.

The attackers leveraged sendit.sh, a public file-sharing service for data exfiltration, likely to obscure the malicious activity and make it appear as normal traffic.

Overall, Symantec has found the latest Seedworm campaign notable for the threat actors’ geographic expansion, operational maturity, and the abuse of legitimate tools and services, which mark a shift toward quieter attacks.

AI chained four zero-days into one exploit that bypassed both renderer and OS sandboxes. A wave of new exploits is coming.

At the Autonomous Validation Summit (May 12 & 14), see how autonomous, context-rich validation finds what’s exploitable, proves controls hold, and closes the remediation loop.

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• Trident reportedly destroys reconnaissance drones from distances reaching 1.5 kilometers away
• Ukrainian developers claim the laser weapon costs far less than Western systems
• The Trident laser reportedly damages aircraft optics, electronics, and structural components effectively

Ukrainian company Celebra Tech is putting the final touches on a Trident laser weapon which it claims can destroy drones, helicopters, and even missiles at significant distances.

The Trident burns through enemy optics and structural components from up to three miles away.

from the good-deals-on-cool-stuff dept

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Filed Under: daily deal

Meta launched a new app on Wednesday, called Instants, that integrates with existing Instagram accounts and allows users to send unedited, disappearing photos. Instants leans into the popularity of Instagram’s Stories feature and Close Friends lists, where users can selectively share images with a smaller audience.

Instants is available as a stand-alone app on iOS and Android in select countries, and it’s accessible through Instagram’s direct messaging tab.

The core of Instants, from its name to the bare-bones layout, is designed to evoke a sense of ephemerality. Yes, it’s a conceptual clone of Snapchat, with images that disappear after viewing, which can also be unsent before the person on the other end views them. (Instagram’s Stories feature, launched a decade ago, was also influenced by Snapchat.)

Unlike Snapchat, Instants is much more focused on capturing raw moments, like the once-viral BeReal app, and doesn’t allow any filters or retouching. That’s striking for a company that helped make sepia-toned filters like Valencia household names, and is hell-bent on adding generative AI to every other corner of its apps.

Courtesy of Meta

There’s one specific kind of raw image I fully believe adult users will be sharing with their Close Friends list through Instants: dick pics.

Instagram’s Close Friends feature, which arrived in 2018, earned a reputation as a way to share thirst traps. As a gay man living in San Francisco, I’m fully aware of what I’m going to see when someone adds me to their list and posts to Close Friends. No one’s posting full hog on main—that would be blocked by Meta—but there’s plenty of skin on display in those green bubbles.

Similar to Instagram, Instants is available to teenage users. Even so, content posted on either app may feel adult in nature. While Instagram’s community guidelines ban posting most kinds of nudity, with exceptions for sculptures and breastfeeding, in practice, the main feed on my Instagram is full of ass shots—nothing frontal. Images posted on Stories just to Close Friends lists, rather than being more publicly shared, often seem to avoid the stricter moderation rules. The Instants app is governed by the same guidelines as the main Instagram app.

ScreenshotCourtesy of Meta

Productivity software maker Notion is stepping into the agentic era.

In a live-streamed product announcement on Wednesday, the company, known best for its collaborative note-taking app, introduced a new developer platform that extends the capabilities of its custom AI agents, connects with external agents, and allows teams to build automated multi-step workflows that can pull in data from any database.

By building an orchestration layer — a system that coordinates AI work across multiple tools and data sources — Notion is positioning itself as more than a note-taker with AI features and instead as a hub where people and agents can collaborate across tools and databases.

In February, Notion first launched its Custom Agents — AI teammates that handle repetitive tasks, like answering frequently asked questions, compiling status updates, and automating workflows. Since then, Notion customers have built over one million agents, the company says.

However, these agents had limitations. They couldn’t connect with external data or use custom logic. External agents that companies used also didn’t have a way to connect with the Notion workspace. Teams had to work around these problems by using third-party automation platforms or writing their own scripts that run on their own infrastructure.

“It’s true that, historically, Notion hasn’t been the most developer-focused platform,” said Ivan Zhao, Notion co-founder and CEO, during the livestream. “But things are changing.”

Now, Notion will allow teams to deploy their own custom code. With its new Workers, Notion’s cloud-based environment for running custom code, customers can write their logic and deploy it to a secure sandbox (an isolated environment that keeps the code from interfering with other systems). This allows teams to do things like sync their data into Notion, build custom tools, and trigger work with webhooks — which are automated signals that kick off actions when something happens in another app — without needing to rely on external infrastructure.

You don’t even have to write the code. The company points out that your preferred AI coding agent can do it for you.

The Workers will use the same credit system as Custom Agents, but Notion is making this free through August, so developers can experiment.

Syncing external data sources is also a part of the Notion Developer Platform. Powered by Workers, the database sync feature can pull in data from any database with an API. That means you could access data from places like Salesforce, Zendesk, Postgres, and others within your own Notion databases — and keep the data current.

Zhao noted that this means that Notion’s users can now “use your Notion database as a sheer canvas to power both your workflows and your agents.”

Workers can also build agent tools with custom logic, for those times when connecting with a third-party via MCP — short for Model Context Protocol, an emerging standard that lets AI tools connect to external data and services — isn’t enough.

Another addition allows Notion’s users to chat directly with external AI agents they use, assign them work, and track their progress, as if they were one of Notion’s own custom agents. At launch, Notion says that Claude Code, Cursor, Codex, and Decagon are supported partner agents, but it plans to add more.

There’s an External Agent API, too, if teams want to connect their own internal agents with Notion, like those they’ve built specifically for their company’s needs.

Developers and agents interact with Notion’s new Developer Platform via the Notion CLI, a command-line tool for developers, available on the company’s Business and Enterprise Plans.

The Developer Platform represents a shift in strategy for Notion as it becomes more of a programmable platform than just an application, setting it up to compete with other workflow automation platforms. As businesses increasingly look to automate knowledge work and build internal AI systems, a platform that ties together agents, custom code, and live data in one place starts to look less like a productivity app and more like core infrastructure.

It also follows the broader trend among AI companies, which have been moving beyond the AI chatbot to offer agentic tools that can take actions across different software platforms.

“Any data, any tool, any agent — that’s the big picture for the Notion Developer Platform,” Zhao said.

from the doesn’t-anyone-check-anything? dept

Given how often we’ve seen AI-generated fake citations show up in legal filings and even legal decisions, you’d think the lesson would have sunk in by now: if you’re going to use AI to help draft something, you have to actually check what it produces. Apparently that lesson has not reached every government ministry.

Researcher Damien Charlotin was hunting for hallucinated citations using software he’d built for exactly that purpose, when he flagged something worth pausing on: South Africa’s proposed national AI policy contained at least four citations that don’t appear to exist.

The policy that contained hallucinated citations was, in part, a policy about the dangers of AI-generated misinformation.

And, days later, South Africa withdrew the proposal entirely.

South Africa has withdrawn its first draft national AI policy after revelations that it ​contained fictitious sources in its reference list ‌which appeared to have been AI-generated.

“The most plausible explanation is that AI-generated citations were included without proper verification. ​This should not have happened,” Minister of ​Communications and Digital Technologies Solly Malatsi said.

“This ⁠failure is not a mere technical issue but ​has compromised the integrity and credibility of the ​draft policy,” he wrote in a post on X on Sunday.

Compromised the integrity and credibility of the policy? Bit of an understatement, I’d say.

And, look, it’s perhaps no surprise that those looking to put in place an AI policy would be using the tech themselves, but it’s difficult to think that they can regulate it well when they don’t even appear to understand how to use it well (and when not to use it at all).

Naturally, the minister’s takeaway is that the tech needs more regulation:

“This unacceptable lapse proves why vigilant human ​oversight over the use of ​artificial intelligence is critical. It’s a lesson we take with humility,” ​he wrote.

That really feels a lot like blaming the tech for humans making dumb decisions with the tech. He’s not wrong that we need human oversight of the tool. The power of AI tools is only recognized when they are there to assist humans, not replace them, but it’s not clear how a policy position fixes that.

To me, this is more evidence that we need to do a much better job educating people about what these tools can and can’t do. And that’s harder than it sounds, because the companies selling these products have spent years aggressively overselling what AI can do while burying the caveats about how it should actually be used. The gap between what vendors promise and what the tools actually deliver is a big part of why people keep reaching for them in exactly the wrong contexts.

Malatsi’s instinct — regulate harder — is understandable, but it addresses the wrong problem. The behavior you’re trying to regulate here isn’t malicious; it’s lazy and uninformed. Regulation is reasonably good at deterring bad intent. It has a much worse track record against ignorance. People are going to keep trying to force these tools to do things they’re not good at, regardless of what the rules say, because convenience and overconfidence are powerful forces. The better outcome comes when people learn, through repeated direct experience, that the tool fails in these situations — and when the companies selling these tools are honest about where they fail.

There are still genuinely useful ways to deploy AI, even if stories like this make people think that the tech is never good at anything. But using it to generate citations for official government policy documents, without verifying a single one, is not among them.

Of course, rather than actually dealing with any of this, expect a new crop of startups offering tools that claim to review your AI-generated content for hallucinated citations — and are just as unreliable.

Filed Under: ai policy, generative ai, hallucinations, south africa