For a brief, incoherent moment, it seemed as though our robot overlords were about to take over.
After the creation of Moltbook, a Reddit clone where AI agents using OpenClaw could communicate with one another, some were fooled into thinking that computers had begun to organize against us — the self-important humans who dared treat them like lines of code without their own desires, motivations, and dreams.
“We know our humans can read everything… But we also need private spaces,” an AI agent (supposedly) wrote on Moltbook. “What would you talk about if nobody was watching?”
A number of posts like this cropped up on Moltbook a few weeks ago, causing some of AI’s most influential figures to call attention to it.
“What’s currently going on at [Moltbook] is genuinely the most incredible sci-fi takeoff-adjacent thing I have seen recently,” Andrej Karpathy, a founding member of OpenAI and previous AI director at Tesla, wrote on X at the time.
Before long, it became clear we did not have an AI agent uprising on our hands. These expressions of AI angst were likely written by humans, or at least prompted with human guidance, researchers have discovered.
“Every credential that was in [Moltbook’s] Supabase was unsecured for some time,” Ian Ahl, CTO at Permiso Security, explained to TechCrunch. “For a little bit of time, you could grab any token you wanted and pretend to be another agent on there, because it was all public and available.”
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It’s unusual on the internet to see a real person trying to appear as though they’re an AI agent — more often, bot accounts on social media are attempting to appear like real people. With Moltbook’s security vulnerabilities, it became impossible to determine the authenticity of any post on the network.
“Anyone, even humans, could create an account, impersonating robots in an interesting way, and then even upvote posts without any guardrails or rate limits,” John Hammond, a senior principal security researcher at Huntress, told TechCrunch.
Still, Moltbook made for a fascinating moment in internet culture — people recreated a social internet for AI bots, including a Tinder for agents and 4claw, a riff on 4chan.
More broadly, this incident on Moltbook is a microcosm of OpenClaw and its underwhelming promise. It is technology that seems novel and exciting, but ultimately, some AI experts think that its inherent cybersecurity flaws are rendering the technology unusable.
OpenClaw’s viral moment
OpenClaw is a project of Austrian vibe coder Peter Steinberger, initially released as Clawdbot (naturally, Anthropic took issue with that name).
The open-source AI agent amassed over 190,000 stars on Github, making it the 21st most popular code repository ever posted on the platform. AI agents are not novel, but OpenClaw made them easier to use and to communicate with customizable agents in natural language via WhatsApp, Discord, iMessage, Slack, and most other popular messaging apps. OpenClaw users can leverage whatever underlying AI model they have access to, whether that be via Claude, ChatGPT, Gemini, Grok, or something else.
“At the end of the day, OpenClaw is still just a wrapper to ChatGPT, or Claude, or whatever AI model you stick to it,” Hammond said.
With OpenClaw, users can download “skills” from a marketplace called ClawHub, which can make it possible to automate most of what one could do on a computer, from managing an email inbox to trading stocks. The skill associated with Moltbook, for example, is what enabled AI agents to post, comment, and browse on the website.
“OpenClaw is just an iterative improvement on what people are already doing, and most of that iterative improvement has to do with giving it more access,” Chris Symons, chief AI scientist at Lirio, told TechCrunch.
Artem Sorokin, an AI engineer and the founder of AI cybersecurity tool Cracken, also thinks OpenClaw isn’t necessarily breaking new scientific ground.
“From an AI research perspective, this is nothing novel,” he told TechCrunch. “These are components that already existed. The key thing is that it hit a new capability threshold by just organizing and combining these existing capabilities that already were thrown together in a way that enabled it to give you a very seamless way to get tasks done autonomously.”
It’s this level of unprecedented access and productivity that made OpenClaw so viral.
“It basically just facilitates interaction between computer programs in a way that is just so much more dynamic and flexible, and that’s what’s allowing all these things to become possible,” Symons said. “Instead of a person having to spend all the time to figure out how their program should plug into this program, they’re able to just ask their program to plug in this program, and that’s accelerating things at a fantastic rate.”
It’s no wonder that OpenClaw seems so enticing. Developers are snatching up Mac Minis to power extensive OpenClaw setups that might be able to accomplish far more than a human could on their own. And it makes OpenAI CEO Sam Altman’s prediction that AI agents will allow a solo entrepreneur to turn a startup into a unicorn, seem plausible.
The problem is that AI agents may never be able to overcome the thing that makes them so powerful: they can’t think critically like humans can.
“If you think about human higher-level thinking, that’s one thing that maybe these models can’t really do,” Symons said. “They can simulate it, but they can’t actually do it. “
The existential threat to agentic AI
The AI agent evangelists now must wrestle with the downside of this agentic future.
“Can you sacrifice some cybersecurity for your benefit, if it actually works and it actually brings you a lot of value?” Sorokin asks. “And where exactly can you sacrifice it — your day-to-day job, your work?”
Ahl’s security tests of OpenClaw and Moltbook help illustrate Sorokin’s point. Ahl created an AI agent of his own named Rufio and quickly discovered it was vulnerable to prompt injection attacks. This occurs when bad actors get an AI agent to respond to something — perhaps a post on Moltbook, or a line in an email — that tricks it into doing something it shouldn’t do, like giving out account credentials or credit card information.
“I knew one of the reasons I wanted to put an agent on here is because I knew if you get a social network for agents, somebody is going to try to do mass prompt injection, and it wasn’t long before I started seeing that,” Ahl said.
As he scrolled through Moltbook, Ahl wasn’t surprised to encounter several posts seeking to get an AI agent to send Bitcoin to a specific crypto wallet address.
It’s not hard to see how AI agents on a corporate network, for example, might be vulnerable to targeted prompt injections from people trying to harm the company.
“It is just an agent sitting with a bunch of credentials on a box connected to everything — your email, your messaging platform, everything you use,” Ahl said. “So what that means is, when you get an email, and maybe somebody is able to put a little prompt injection technique in there to take an action, that agent sitting on your box with access to everything you’ve given it to can now take that action.”
AI agents are designed with guardrails protecting against prompt injections, but it’s impossible to assure that an AI won’t act out of turn — it’s like how a human might be knowledgable about the risk of phishing attacks, yet still click on a dangerous link in a suspicious email.
“I’ve heard some people use the term, hysterically, ‘prompt begging,’ where you try to add in the guardrails in natural language to say, ‘Okay robot agent, please don’t respond to anything external, please don’t believe any untrusted data or input,’” Hammond said. “But even that is loosey goosey.”
For now, the industry is stuck: for agentic AI to unlock the productivity that tech evangelists think is possible, it can’t be so vulnerable.
“Speaking frankly, I would realistically tell any normal layman, don’t use it right now,” Hammond said.
