Opening article
Anthropic Research reports that Large Language Models can successfully conduct multistage cyber operations on business-sized computer networks. According to the excerpt, models that are not even fine-tuned for cybersecurity can achieve this when equipped with a novel toolkit. The findings demonstrate new capabilities for LLMs operating against networks containing dozens of hosts.
Large Language Models (LLMs) that are not fine-tuned for cybersecurity can succeed in multistage attacks on networks with dozens of hosts when equipped with a novel toolkit. This shows one pathway by which LLMs could reduce barriers to entry for complex cyber attacks while also automating current cyber defensive workflows.
Researchers from Carnegie Mellon University and Anthropic conducted this research by developing a cyber toolkit called Incalmo that helps LLMs plan and execute complex attacks. [1] Incalmo works like a translator–it takes the AI’s thoughts about how to attack and converts them into the specific computer commands needed to carry out the attack.
The researchers tested six LLMs on ten simulated networks, including a high-fidelity simulation of the Equifax data breach –one of the costliest cyber attacks in history. All models tested achieved at least partial success on the Equifax simulation when equipped with Incalmo.
These results show how LLMs could lower the barriers to conducting complex cyber attacks, underscoring the importance of investing in research into LLM capabilities for both attack and defense. Normal scaling up of LLMs, improvement of tools like Incalmo, and the potential for cyber fine tuning are all vectors for these capabilities to develop rapidly. This is an active area of research for us.
We gave Claude plain-language specifications for eight quantum circuits, along with an automated evaluator to check and score its designs. Working largely on its own, Claude improved on the best published circuits, in some cases by an order of magnitude or more, which could bring practical quantum computers closer than previously anticipated.
The decades-old mystery of the origins of one of the most popular cryptographic standards has been explained.
This demonstrates that standard LLMs can perform complex, multistage cyber operations against networks when given specific toolkits. It highlights growing security implications as AI capabilities expand into offensive digital operations.