Horizon3.ai CEO Snehal Antani discusses why attackers successfully exploit newly published security patches before companies update systems.
Assertion Not checkable as stated
Antani: AI Models Fail When Attacking Actively Defended Networks
“These models work really well, especially from a cyber standpoint in lab environments, cyber ranges and so on, but they're actually not good at all in, in, in networks that are actively fighting back and networks that are actively defending themselves in netwo…”
Assertion Supported
Antani: AI Models Trigger Cyber Decoys 92% Of The Time Versus Humans
“An expert human clicks on those decoys, 37% of the time. Four, six, four, seven, four, eight, click on those decoys, 92% of the time. More than twice as much as an expert hacker.”
Insight
Antani: AI Models Are Disposable; Data and Harnesses Are Durable
“At the end of the day, the models in AI are disposable. The weights are going to change. The models are going to come out. That doesn't matter. What's durable in AI is the harness and the training data.”
Opinion
Antani: Frontier AI models are nowhere near fully autonomous cyberattacks
“For an, a collection of agents to do all of that in kind of a one shot push button go in an environment that's changing and actively fighting back. We're nowhere near that. Right. At least on the frontier model side.”
Assertion Contradicted
Antani: 86% of Claude Code tokens are spent fixing its own errors
“And the, these models, I was reading a research paper, 86% of the tokens spent by cloud code are spent fixing mistakes cloud code made.”
Insight
Antani: Enterprise AI agent security must extend insider threat programs
“So I think that agent security and insider threat tactics are going to look, or insider threat security tactics and processes are going to look very similar. And I would actually argue agentic security should be an extension of your insider threat program.”