Written by Pieter Danhieux
Security risks are rising as AI coding tools become routine, leaving many firms unable to track how machine-generated code reaches production.
As AI tools spread through software teams, rising security flaws and shadow AI use are forcing leaders to tighten guardrails fast.
Agentic AI promises rapid software gains, but a recent Claude Code cyberattack shows how “double agents” can outpace unprepared developers.
AI tools boost software development speed, but security flaws in code pose serious risks to organisations, urging leaders to manage AI use carefully.
By understanding the security implications of AI, security teams will be well-placed to avoid the negative side effects that the technology could deliver.
It's important not to lose sight of the need to keep secure coding practices front and centre in software development - even when deploying AI tooling.
With policymakers aligned on issues of security accountability, the focus must now turn to the practicalities of implementation.
Developers prioritize new features over security, with just 14% considering it when coding, according to a report by Evans Data.
Cybercriminals have tended to focus on acquiring user credentials to maximise their ability to traverse targeted IT infrastructures.
