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Modern organisations are increasingly deploying generative artificial intelligence (GenAI)-enabled tools like Microsoft Copilot to reimagine their business models, all in the name of innovation. Unfortunately, this has contributed to the alarming spike in the frequency, severity and diversity of cyber attacks, writes Chris Fisher, regional director for ANZ at Vectra AI.
According to recent reports, 75 per cent of cyber security professionals have seen an increase in AI-powered cyber attacks over the past year, with 85 per cent attributing it to threat actors weaponising AI.
When large language models (LLMs) are given access to proprietary corporate data and equipped with the ability to make decisions and take actions, new attack surfaces are introduced that enable surprising new attack techniques. And oftentimes, cyber security defences become an afterthought.
As businesses continue to digitise their operations, traditional security measures may no longer suffice and the need for more robust cyber security measures become more pressing. How does digital innovation leave businesses susceptible to cyber attacks?
Third-party access leads to rapid rise in identity-based attacks
As enterprises modernise their IT infrastructure with GenAI technologies and methodologies, they are integrating not just AI and machine learning (ML) but also with third-party applications, contractors and outside services. Maintaining strict access control to sensitive networks, services, and applications becomes more challenging as more third-party partners, contractors and suppliers are used, increasing the risk of identity-based attacks. For example, attackers can use Microsoft identities to gain access to connected Microsoft applications and federated SaaS applications like Microsoft Entra ID (formerly Azure ID).
Despite the estimated AU$7.3 billion spent on security and risk management products this year, 90 per cent of organisations have experienced identity attacks. With GenAI further providing new opportunities for adversaries to exploit vulnerabilities in identity-related systems to perpetrate ransomware, scams and business email compromise (BEC), organisations will continue to be targeted. It’s clear that current preventive security controls are not enough to fight GenAI-driven attacks. Companies need to consider alternate options like threat detection and response to close the widening exposure gap.
Lateral movement exposes hybrid cloud vulnerabilities
With hybrid attacks on the rise, the complexity of managing security in hybrid environments is daunting. Malicious actors are not just looking at social engineering traps but also vulnerabilities and misconfigurations. The biggest issue in the cloud is credential theft through repositories like GitHub or Bitbucket – when a developer mistakenly uploads the credentials, or if the cloud’s complexity leads to misconfigurations being used or abused.
Lateral movement in the hybrid world further amplifies the problem as threat actors “live off the land” using available tools and infrastructure to disguise themselves as legitimate users to obtain the necessary credentials to access sensitive data. Identity-based attacks correlate with lateral movement when new identities continue to be compromised as the attacker moves around a network. Monitoring how an identity has been compromised and maintaining visibility and a consistency of risk and control is critical. More so when most identities are contained in federated domains that don’t fully integrate with one another, creating blind spots for attackers to hide. GenAI tools can be abused to increase the speed of lateral movements. In the past, ransomware attacks used to take between eight to 14 days, but with Microsoft Copilot, this reconnaissance could take minutes instead of days.
Fighting AI threats with AI
Despite these challenges, GenAI presents an exciting opportunity to use AI technology to aid in the fight against cyber attacks. If businesses go back to basics, leverage proven security expertise, and create a robust foundation of security measures, they are well placed for innovation without the potential fallout. Key factors to consider include:
As organisations get more innovative, so do attackers
The potential of GenAI to transform workforce productivity and boost innovation is more than just hype. As GenAI capabilities continue to evolve, it will advance security tools, improve threat intelligence and transform security operations centres. Security leaders must adopt AI as part of their defence and response strategies to ensure they remain resilient, agile and one step ahead of cyber attackers.
About the author: Chris Fisher is the regional director for Australia and New Zealand at Vectra AI.
Responsible for leading business growth for Vectra AI across Australia and New Zealand, Chris is focused on ensuring Vectra’s customers have the security foundation required to embrace new technology and lines of business, allowing them to digitally transform while reducing business risk and improving their security posture. Chris has more than 20 years of cyber security experience from practitioner through to strategic adviser for large organisations.