Forget malware - new research from Carbon Black says that non-malware attacks are the biggest risk for businesses right now.
The latest report, titled ‘Beyond the Hype', polled 410 leading cybersecurity researchers. 93% said that non-malware attacks pose more of a business risk than commodity malware attacks.
64% of those polled said they've seen an increase in non-malware attacks since the start of 2016. These attacks are going after native system tools such as PowerShell and WMI to conduct the attacks.
“Non-malware attacks will become so widespread and target even the smallest business that users will become familiar with them. Most users seem to be familiar with the idea that their computer or network may have accidentally become infected with a virus, but rarely consider a person who is actually attacking them in a more proactive and targeted manner,” one researcher says.
Non-malware attacks are getting more creative. Affecting satellite transmissions, impersonating CSOs, login spoofing systems and other social engineering methods were popular.
Respondents also said that data attackers are also mostly looking for customer data (62%), corporate IP (53%), service disruption (51%), credentials (42%) and financial data (41%).
47% of respondents said their legacy AV system missed malware, or weren't sure if it had missed any.
The survey also found that while AI might be a popular phenomenon right now, it's still in the early stages and can't replace human decision making. Researchers are concerned that giving computers more power may not be a good idea.
87% believed that it will take more than three years before AI could make cybersecurity decisions in a trustworthy way.
74% said AI security solutions are flawed and 70% said machine learning security solutions can be bypassed for attackers. 30% said they can be ‘easily' bypassed.
“Based on how cybersecurity researchers perceive current AI-driven security solutions, cybersecurity is still very much a ‘human vs. human' battle, even with the increased levels of automation seen on both the offensive and defensive sides of the battlefield,” explains Michael Viscuso, Carbon Black's co-founder and CTO.
“And, the fault with machine learning exists in how much emphasis organisations may be placing on it and how they are using it. Static, analysis-based approaches relying exclusively on files have historically been popular, but they have not proven sufficient for reliably detecting new attacks. Rather, the most resilient ML approaches involve dynamic analysis - evaluating programs based on the actions they take,” he concludes.