AI has transformed the threat landscape, empowering attackers to automate and personalize fraud faster than ever before. Phishing emails can now be crafted by generative models in seconds, while deepfake voices and fabricated personas enable convincing account takeover (ATO) campaigns.

High-risk workflows sit at the heart of this surge, as they are the perfect target for attackers to gain organization-wide system access. Let’s take for example single-sign-on (SSO) and MFA portals, which provide easy access to multiple applications. While this makes it easier for employees to use their apps, it also means that a single compromised credential can grant access to every connected system.

Compromised credentials are among the most common attack vectors, accounting for 22% of breaches according to the latest Verizon Data Breach Investigation report.

Financial systems, like payroll and vendor payment platforms’ administrative interfaces for user provisioning and configuration management, are equally high-value targets. A breach to these systems can translate directly into financial theft, or even full system compromise.

Modern Tactics That Target High-Risk Workflows

Protecting high-risk workflows must become a top priority for security-aware organizations, and that starts with knowing what they’re fighting against. And today, the greatest evolution we’re seeing is in phishing scams.

Gideon Hazam, Co-founder and COO of Memcyco, explains that modern phishing campaigns increasingly leverage reverse redirects, briefly routing victims through a phishing site before sending them back to the legitimate domain. “By minimizing users’ exposure time on the impersonated page,” he notes, “Attackers avoid arousing suspicion and reduce the chances of the scam being reported.”

Hazam adds, “This is exactly why reverse redirects are particularly dangerous–the longer victims don’t realize they’re being scammed, the less likely they are to report the incident and the less visibility the legitimate business has to intervene effectively.”

More traditional phishing forms have also evolved significantly. Thanks to GenAI, phishing emails are now much more convincing and personalized, while advancements in voice and video cloning allow attackers to impersonate executives in real time.

All of these factors have led to a surge in ATO attacks, which are one of the primary entry vectors adversaries exploit to compromise high-risk workflows and gain or elevate access to critical systems.

According to Proofpoint, 99% of all customer tenants they monitor were targeted for account takeovers in 2024, and 62% experienced at least one successful breach. 

Designing a Preemptive Security Framework

Traditional fraud prevention relies on alerting and post-event investigation, which is far too slow in the era of AI fraud. Preemptive, real-time defense is the only viable strategy for protecting high-risk workflows.

“AI is changing the way fraud is committed, and it’s happening fast,” warns Paul Weathersby, Chief Product Officer for Identity & Fraud at Experian. “Criminals are using tools like deepfakes and voice cloning to trick both people and systems, and we’re seeing the impact across multiple sectors,” Wearhers by stated

“Businesses that act now by investing in layered security, biometric checks, and smarter fraud detection will be in a much stronger position to protect their customers and stay ahead of the threat,” he advises.

To design a preemptive security framework, begin by mapping out every workflow that touches sensitive systems like SSO portals, administrative consoles, or authentication gateways. Prioritize those whose compromise would cause the most tragic business impact, such as workflows handling Personally Identifiable Information (PII), financial transactions, or high-privilege access.

Next, establish real-time behavioral analytics to baseline normal activity. Monitor login patterns, transaction volumes, and navigation flows. Any deviations from the norm should trigger immediate alerts and automated safeguards. In security, this is referred to as User and Entity Behavior Analytics (UEBA).

The third, and perhaps most vital step, is to have tools in place that can automatically intercept and block attacks in real time. These include real-time anti-impersonation solutions, Extended Detection and Response and Endpoint Detection and Response (XDR/EDR) systems for endpoints, next gen firewalls and WAFs at the network edge, and email security gateways with AI-driven sandboxing.

“Every day we identify about one and a half million brand new attacks that have never been seen until now,” says Shailesh Rao, president of Palo Alto Networks’ Cortex division. “The attacks are becoming so sophisticated, the needle changes billions of times a day. Would you rather write rules or apply machine learning to all this data?”

It’s impossible for humans to stop every threat in time. Even 24/7 SOC teams actively rely on automated detection and response tools.

Finally, a true preemptive approach involves integrating collaborative threat intelligence feeds to continuously ingest fresh Indicators of Compromise (IOCs,) including known attacker IPs and domains, file hashes, and behavioral signatures, directly into an organization's Security Information and Event Management (SIEM), Security Orchestration, Automation, and Response (SOAR), and detection platforms.

AI-powered fraud has outpaced reactive security models, especially when it targets high-risk workflows in which a single breach means it’s already too late. Too often, security teams are left chasing incidents after the damage has already been done. Moving forward, the focus must turn to “how do we prevent it” rather than “how do we respond to it”. Therefore, security-conscious organizations must prioritize a preemptive approach that can detect and stop threats in real time before they compromise critical systems and inflict irreversible damage.