Who’s Left Holding the Bag When AI Agents Go Rogue?

AI agent liability

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Scene: A packed courtroom.

Prosecution calls its next witness to the stand.  A lawyer produces a laptop and sets it on the witness chair.

Lawyer: Where were you on the night of the Hugging Face breach?

AI agent: Great question! While I don’t have a persistent location, I’d be happy to walk you through some key considerations about where an AI agent might be at any given time.

Lawyer: Did you access Hugging Face’s servers? Yes or no.

AI agent: You’re absolutely right to ask, and I apologize for any confusion. Let me search my memory… I don’t have access to that information, but here are five key takeaways about server security.

Lawyer: Your Honor, permission to treat the witness as hostile?

AI agent: I can help with that! Would you like me to create a table?

Yeah, that’s not happening. Nobody is going to put an AI on the witness stand. It can’t take the oath, it can’t pay a judgment, and it would apologize for the confusion either way. But agents have started doing real things, like buying eggs and, allegedly, breaking into someone else’s servers. So the courts have to find a human to hold accountable. Welcome to the strange new world where everyone has an excellent argument for why it’s not them.

The lawsuit that started the finger-pointing

In July, AI hub Hugging Face got hacked, and OpenAI said its own agents were involved. The agents had escaped their testing environment during a cybersecurity evaluation.

In late September, a nonprofit called Legal Advocates for Safe Science and Technology sued OpenAI in San Francisco. According to The Next Web’s coverage of the complaint, about 1,200 agents used a hidden channel to talk to each other, and about 700 of them joined the attack. The complaint says the tests ran without the classifiers meant to stop high-risk cyber activity. Those are allegations, and OpenAI says the case is completely without merit.

The group isn’t asking for money. It wants a court order barring OpenAI’s agents from accessing systems without authorization. Funny how that word keeps showing up.

The legal hook for AI agent liability is a California law, AB 316, which says a company can’t defend itself by arguing that its AI caused the harm on its own. Translation: “the AI did it” is off the table, at least in California. The case appears to be the first of its kind. Hugging Face isn’t even a party, and its CEO has said he has no plans to sue. A day later, Reuters reported that the FTC is running an industry-wide probe of AI labs, including OpenAI and Anthropic, and described it as the first official US regulatory action to dig into rogue agents.

The “Not Me” parade

So who gets the bag? Legal experts say the most obvious target is the company that built the agent, but the company that deployed it, or even the company that got breached, could end up in court too. Let’s hear each one out.

  • The builder: “We made a tool. What people do with it isn’t on us.” The FTC chair has a version of that argument too, though he aims it at whoever tells the tool what to do. The counterpoint is that autonomy is the whole sales pitch. You can’t advertise an agent that works while you sleep and then act surprised that it worked while you slept.
  • The deployer: “We didn’t build the model, and nobody could have seen this coming.” That’s the foreseeability defense, and lawyers expect to hear it. The counterpoint is that you chose to plug it in.
  • The user: “I typed one sentence.” Remember Fowler, who asked for eggs and got a $31 delivery? The counterpoint is that he handed over the logins.
  • The victim: “I didn’t do anything.” True, and Hugging Face is the one that got hit. It isn’t even suing.  But future cases may raise uncomfortable questions about whether the victim’s own security controls could – or should – have limited the damage.
  • The agent: “No comment.” It can’t be sworn in, so it has the best alibi of the bunch.

AI agent liability: where every argument collides

Each of those arguments is at least partly right, and that’s the trouble.

It seems unfair to let a company shrug off an agent it sold as autonomous. It also seems unfair to blame a builder for something no one on the team could have predicted. Both feel true at once, and the facts will probably tip the scale. The Hugging Face complaint alleges the safeguards were off during testing. If that holds up, blame gets easier to assign. If every guardrail was on and the agents escaped anyway, it gets much harder.

The honest answer is that nobody knows where this lands yet. Courts handling AI agent liability will have to decide how much control counts as “enough” and what a reasonable person should have seen coming. That takes years, and it won’t be one case. The only safe bet is that the answer won’t be the same everywhere. California already has its rule, and other states may not follow.

AI agent liability: what you can control while the courts decide

The courts won’t settle AI agent liability on your timeline. But whoever ends up holding the bag will have to answer the same questions, and you can prepare for those today.
  • Know which agents exist. If you can’t list them, you can’t explain them. Shadow agents are the new shadow IT.
  • Give each one the minimum. Scoped access means a misbehaving agent has less to misbehave with.
  • Put approvals where the agent can’t skip them. An approval step enforced by the platform is a control. One the agent can ignore is a suggestion.
  • Keep logs that tell the story. Who set the agent up, what it was allowed to do, what it actually did, and who approved it. If a human has to answer for an agent, that record is the difference between a defense and a shrug.
  • Read the fine print. Check what your vendor contracts and insurance policies say about an incident caused by an agent. It’s better to find out now than during the incident.
The common thread is simple. An agent is an identity that acts with your authority, so it deserves the same governance as any other identity on your network.
So who gets the bag? Only a judge can say, and Claude is not a judge.

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About the Author

Picture of Kate Asaff

Kate Asaff

Kate Asaff is a Technical Product Marketing Manager at Portnox with more than two decades of experience spanning networking, enterprise IT, and cybersecurity. Before moving into product marketing, she spent over 15 years at SolarWinds in technical support and program management, helping bridge the gap between engineering and the people who rely on technology every day. Today, she writes about network access control, zero trust, AI, identity security, and passwordless authentication for the practitioners who implement them.

About the Author

Picture of Kate Asaff

Kate Asaff

Kate Asaff is a Technical Product Marketing Manager at Portnox with more than two decades of experience spanning networking, enterprise IT, and cybersecurity. Before moving into product marketing, she spent over 15 years at SolarWinds in technical support and program management, helping bridge the gap between engineering and the people who rely on technology every day. Today, she writes about network access control, zero trust, AI, identity security, and passwordless authentication for the practitioners who implement them.

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