Your AI assistant just recommended software that doesn't exist. Someone made it exist — and it's malware.
That's not a hypothetical. It happened this year, it's accelerating, and if anyone on your team is using AI tools to build or automate anything — and they probably are — this is your problem too.
The Attack Nobody Saw Coming
Here's the mechanics of it. When developers use AI coding assistants to write automation scripts, integrations, or internal tools, the AI will often suggest specific software packages to install — pre-built libraries that handle common tasks. It saves time. It's one of the reasons AI-assisted development caught on so fast.
The problem: AI models hallucinate package names. They confidently recommend libraries that sound legitimate but flat-out don't exist. It's the same reason a chatbot might cite a court case that was never tried or a study that was never published — the model generates plausible-sounding output, not verified output.
Attackers noticed the pattern. They started monitoring which fake package names AI tools repeatedly suggested. Then they created real packages with those exact names — uploaded to the same public repositories developers use every day — and packed them with malware.
The attack has a name: slopsquatting. Researchers have already found over 200 malicious packages published specifically to exploit AI-hallucinated names. That's a 1,000% increase year over year in this attack vector. Not a rounding error. A thousand percent.
The moment someone on your team runs the install command, the malware is in. Credentials get harvested. Systems get accessed. Data walks out the door.
Why This Is an Operations Problem, Not Just a Developer Problem
I run an e-commerce and import operation. I build automations with n8n, AI agents, and LLMs — not because I'm a developer by training, but because these tools are now genuinely accessible to operators. That's the upside. The downside is that the same accessibility that lets me spin up a workflow in an afternoon also means the blast radius of a bad install is sitting right next to my inventory data, my supplier contacts, and my payment integrations.
If your business uses any of the following, you have exposure:
- AI tools that help write or generate code, scripts, or automations
- Team members building internal tools with AI assistance — even "no-code" tools that touch APIs
- Contractors or freelancers using AI coding assistants on projects for your business
- Anyone connecting third-party integrations based on AI recommendations
This is your software supply chain. You may not think of it that way, but every package that gets installed in a tool your business depends on is a link in that chain. One compromised link is enough.
The attack doesn't require anyone on your team to do something careless. It requires them to trust an AI recommendation without a verification step in place. That's the gap.
What Governance Actually Looks Like (Without the Corporate Jargon)
The fix isn't panic, and it isn't banning AI tools. Both of those responses cost you more than the threat itself. The fix is governance — a word that sounds heavy but really just means: knowing what your AI tools are allowed to touch, and making sure anything that runs in your environment has been checked by a human before it does.
In practice, for a small or mid-sized operation, that looks like:
- Inventory your AI touchpoints. Where is AI being used to write, suggest, or generate code or automations in your business right now? Include contractors. Include "just testing" projects that somehow went live.
- Establish a verification step. Any package, library, or integration recommended by an AI tool gets cross-checked against the official repository before installation. This takes two minutes and blocks slopsquatting entirely.
- Limit permissions by default. Tools and automations should only have access to what they absolutely need. If an automation manages your shipping labels, it has no business touching your accounting credentials. Least privilege isn't a developer concept — it's operational common sense.
- Set a policy for AI-assisted development. If team members or contractors are building things with AI help, they need to know these rules exist. A one-page policy is enough. You don't need an IT department to enforce it.
None of this requires you to understand how the malware works. You don't need to read code. You need to know where AI is involved in building the things your business runs on — and make sure a human with the right checklist is in that loop.
The Broader Point About AI Risk
Slopsquatting is one specific attack, but it points to something larger. AI tools are now embedded in business operations at a depth that most owners haven't fully mapped. That's not a criticism — the tools move fast and the value is real. But the same confidence that makes AI useful also makes it dangerous when it's wrong. It doesn't hedge. It doesn't flag uncertainty. It just recommends — and your team installs.
The businesses that come out ahead here aren't the ones that slow down on AI adoption. They're the ones that adopt with structure. They get the speed advantage and close the gaps that the speed creates.
That's the balance we work toward at Maqia: real automation, real AI integration, real operational leverage — built with the kind of checks that mean you're not handing an attacker the keys along with your efficiency gains.
If you want to map your current AI exposure and build a governance layer that actually fits how your business operates, book a call with us. We'll walk through exactly where the gaps are and what it takes to close them — no enterprise budget required, no developer on staff assumed.