The National Cyber Security Centre (NCSC) has issued advice on how cybersecurity professionals can adopt agentic AI to help automate security tasks and manage risks.
Using AI automation for defense isn't generally about overcoming technical challenges, according to Dave Chismon, NCSC CTO for architecture, but more of a question of organizational politics, meaning that defenders can't simply put AI to work in the same way attackers can.
"This is an inconvenient truth, as it suggests that the threat from AI-enabled cyber attacks will grow, whilst autonomous / agentic cyber defense might struggle to keep up unless we approach things differently," he said.
"Rather than trying to mimic attackers’ use of agentic tooling (and risk breaking things), defenders need to solve the problem by explicitly considering the constraints."
Notably, the NCSC said automation can involve offensive techniques being applied defensively, such as penetration testing and vulnerability research or discovery.
This generally happens in a way that minimizes risks to the business; applications are tested before they go live, and vulnerabilities are handed to development teams to fix.
Elsewhere, technical and dynamic approaches can be used for cyber defence - but also need evaluating from a business point of view.
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"Establishing a SOC is also typically a lengthy (and often expensive) process. Legal aspects and policies need to be agreed, and data then exported from live systems to a new platform where malicious activity can be detected and triaged before the team takes action," said Chismon.
Both mean doing a lot of work up front to show that vulnerability detection or missing patches won't harm the business.
A new framework for agentic AI adoption
To help with this, the NCSC has outlined a framework for estimating the 'riskiness' of a defensive action and identifying the lowest-risk actions that can be automated – these are often tasks that involve advising a human, rather than affecting a system directly.
Some of this will be covered by the government's planned Cyber Shield, a national-scale agentic cyber defence ecosystem, with its ‘AI for Cyber Defence’ problem book expected soon.
However, Chismon warned that more research is needed on agentic AI, particularly in terms of how to deterministically prove that ‘low risk’ actions really are low risk.
Examples include using AI to help analyse traffic logs and show conclusively that the organization does know all the routes clients connect by, or establishing whether AI can reverse engineer or otherwise assess a system and its binaries to show exactly which network calls it could ever make.
"Answering these questions will give us, and the organizations we protect, the confidence to take automated defensive actions. Furthermore, it opens up the chance to automate the hardening of systems and reduce attack surfaces and exposure, which will be crucial in combating AI-enabled cyber attacks," said Chismon.
"All these efforts will take time, effort, and research. Organizations cannot risk just waiting for agentic defence to roll in and protect them; they also need to be focussing on improving their security the traditional way."