Top Highlights
- Open AI models are closing the cyber gap: DeepSeek nearly matched OpenAI’s restricted Daybreak model in simulated network attacks.
- The scores were close: Daybreak completed 81% of tasks; DeepSeek averaged 73%, tying on some.
- Open models are much cheaper to run: The tests cost $2–$3 with DeepSeek versus $17–$46 with GPT-6-Sol.
- The shift may be here already: Gated access may no longer delay advanced hacking capabilities—so defenders need to prepare now.
The capability gap is shrinking
Open-weight AI models are closing in on their most advanced, restricted rivals. In tests on simulated company networks, DeepSeek completed 73% of assigned objectives on average. OpenAI’s restricted Daybreak model completed 81%. The models tied on some tasks.
Still, these were mock networks, not real companies. The results show what models can do in controlled tests. They do not prove that either model can reliably break into live systems.
Lower costs widen access
Open-weight models let users download and run the software on their own hardware. That can cut costs sharply. Vals estimated that an attack simulation cost $2 to $3 with DeepSeek, compared with $17 to $46 with GPT-6-Sol.
As a result, advanced cyber skills may spread beyond a small group of approved users. Access limits at major AI labs may slow that spread, but they cannot stop people from using capable open models.
Defenders can benefit, too
The same tools could help security teams test their networks and find weak spots sooner. Lower costs may also give smaller organizations more ways to prepare. However, attackers can use the models as well.
So, organizations should strengthen basic defenses: patch software, limit access to sensitive systems and rehearse response plans. Open AI models offer useful new tools. They also raise the stakes for teams that fall behind.
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