How AI is addressing the blind spot in file security

AI is shaping the future of cybersecurity, and the industry is deeply invested in finding new ways to apply the technology against future threats. However, AI technology also plays a critical role in addressing one of the oldest risks still plaguing many organisations: malicious files. 

Hiding malware inside a seemingly benign file is one of the oldest tricks in the cybercriminal playbook, and that’s because it works. Research found that 61% of organisations have suffered at least one file-related breach in the past two years, at an average cost of $2.7 million per incident.  

The root of these incidents is usually a lack of visibility. With so many files moving between systems, applications, and users, many escape inspection altogether. Even enterprises with a mature cybersecurity programme have blind spots in their file security stack, despite multiple layers of defence. Blind spots like these are where the speed and accuracy of AI have the greatest potential. 

Why existing tools can’t keep up 

Traditional file security often still relies on static, signature-based tools. While these defences are effective against known malware families, they were built for a different era and are increasingly outfoxed by the latest threats. 

Modern file formats are layered with embedded elements, such as macros, hyperlinks, scripts, and password-protected content, that enrich the user experience but also provide more opportunities for attackers to hide. 

Research found that macro-based malware is the malicious content with the highest concern among security leaders, with zero-day malware a close second. 

I often see security and IT teams banning macros and assuming the problem is solved, but that only removes a small fraction of the risk. Threat actors now employ far subtler techniques, embedding malicious links or scripts that most antivirus tools fail to detect.  

Traditional systems also struggle to keep up with the sheer volume of data moving through an organisation each day. Additionally, it’s common for business emails to have multiple links to web and social media embedded in their signatures, all of which adds even more strain for hyperlink analysis and sandboxing tools.  

How AI restores visibility and speed 

AI has two powerful traits that make it an ideal tool for dealing with this challenge. First is its incredible speed, rapidly analysing those millions of interactions in real time. 

Alongside this is AI’s immense capacity for pattern recognition. This enables it to identify anomalies and classify new file behaviours to counter the new threats that static defences miss.  

By combining machine learning with contextual awareness, it can flag suspicious activity long before a threat fully materialises. It also helps reduce the human workload by automating repetitive scanning and correlation tasks that consume so much of a security team’s time. 

There are signs that organisations are beginning to see its value: one in three organisations are already using AI within their file security strategy, and a further 29% plan to adopt it by 2026. The benefits are clear: 50% report reduced risk and 41% see measurable cost savings.  

Crucially, AI doesn’t replace human oversight but rather amplifies our ability to act at the speed that modern threats demand. This is critical to turning what was once an overwhelming visibility gap into a manageable, data-driven process. 

Integrating AI into a defence-in-depth strategy 

AI delivers the best results when it’s part of a wider, layered security approach – not treated as a standalone fix. No single tool can catch every threat on its own.  

True resilience comes from combining multiple technologies and processes that reinforce one another, such as pairing AI’s intelligence with proven methods like multiscanning, sandboxing, and Content Disarm and Reconstruction (CDR). 

In file security, CDR plays a vital role by rebuilding clean versions of incoming files and stripping out hidden threats like macros, scripts, or embedded objects.  

AI adds another dimension by continuously learning from every disarmed file, refining its models, and improving detection accuracy over time. Together, they create a feedback loop that strengthens protection and reduces reliance on static signatures or manual intervention. 

AI also helps orchestrate the layers of defence. By quickly identifying which files present the greatest risk, it ensures that sandboxing and scanning resources are focused where they’re needed most.  

The outcome is a security system that’s not only more efficient but also more adaptive — capable of guarding against known threats while preparing for those yet to emerge. 

The emerging risks of unmanaged AI adoption 

These advantages come with a caveat: while AI is transforming how organisations detect and respond to threats, its rapid adoption is also creating new vulnerabilities. Research found that only one in four organisations have a formal governance policy for AI use. The rest are moving fast without clear guardrails, leaving themselves open to mistakes and manipulation. 

Poorly managed AI can expose companies to several risks. Attackers are already experimenting with ways to plant malicious prompts inside macros or exploit AI parsers to reveal hidden or redacted data.  

Meanwhile, employees often upload sensitive information to generative AI tools without realising how that data might later be stored, shared, or used by the model. These lapses don’t stem from the technology itself, but from a lack of visibility and control around how it’s deployed. 

Every organisation wants to move quickly to harness AI’s benefits, but they also need to pause to consider the governance it requires. Without clear policies defining how models are trained, validated, and accessed, AI can just as easily widen the attack surface as help secure it. 

AI is already reshaping how we think about file security, giving defenders the speed and visibility that have long been missing. But its value, ultimately, depends on how intelligently it’s applied. When integrated into a layered defence and guided by strong governance, AI has the potential to make file inspection faster, more accurate, and more scalable than ever before.