How AI is Fueling ATOs & Fake Account Creation—And Why Bot Detection Needs to Evolve

Artificial intelligence is reshaping the cyberfraud landscape, enabling attackers to scale operations, refine their tactics, and bypass security measures with unprecedented efficiency. AI isn’t simply enhancing cyberattacks, it’s becoming a core part of botnets themselves. Fraudsters are embedding AI into the very architecture of modern botnets. These AI-powered botnets can dynamically adapt their behavior, make decisions autonomously, and respond in real time to changing defenses—automating reconnaissance, refining social engineering, and evading detection more effectively than ever before.

Nowhere is this more apparent than in account takeover (ATO) fraud and fake account creation. As AI advances, traditional fraud detection methods are struggling to keep up, making real-time, adaptive protection more critical than ever.

AI-powered ATOs: Faster, smarter, & harder to detect

Account takeover fraud has existed for years, but AI is pushing these attacks to a new level of sophistication. Fraudsters are using AI to refine brute-force attacks, automate authentication bypass tactics, and evade security measures in ways that are nearly indistinguishable from legitimate users.

Brute-force attacks are getting smarter

In the past, brute-force attacks relied on sheer volume—throwing thousands of password guesses at login pages until one worked. AI, however, makes these attacks far more efficient. Advanced AI techniques—including natural language processing (NLP), reinforcement learning, and deep learning—can analyze login patterns, identify common password structures, and even generate likely variations based on leaked credentials. This allows fraudsters to prioritize their attacks, reducing detection risks while increasing their success rates.

AI also enables real-time adaptation. Attackers can analyze the responses they receive from login attempts and adjust their approach on the fly. Suppose a particular set of login credentials triggers security protections. In that case, AI-driven bots can quickly adjust their attack strategies, such as switching IP addresses, altering input patterns, or adapting timing and sequencing of requests, to evade detection by security systems. 

AI-fueled fake account creation is exploding

Fake account creation has long been a challenge, but generative AI is amplifying the problem. Fraudsters can now generate thousands of fake accounts at scale, fueling financial fraud, spam, misinformation campaigns, and illicit transactions.

AI is powering hyper-realistic fake identities

Fraudsters are no longer relying on obvious bot accounts. AI now enables them to create synthetic identities that pass verification checks:

• Deepfake profile pictures make fraudulent accounts look real.
• AI-generated bios and activity patterns mimic legitimate users.
• Human-like engagement patterns allow bots to blend into platforms undetected.

Large-scale fake account creation facilitates fraud, distorts online interactions, and erodes platform integrity. Companies that fail to prevent fake accounts face not only financial losses but also increasing regulatory scrutiny and increasing risks of abuse, including promo code fraud and so-called “friendly fraud.” Fraudsters leverage AI-generated fake accounts to exploit promotional offers, repeatedly claiming discounts or rewards at scale. Additionally, friendly fraud—where real users dispute legitimate transactions—can be enhanced by AI-driven automation, making it easier for bad actors to generate fraudulent claims that appear authentic., as many jurisdictions are beginning to hold platforms accountable for inadequate fraud prevention.

As AI-driven fake identities become harder to distinguish from real users, traditional detection methods, such as basic identity verification, are no longer enough.

Why bot & cyberfraud detection must adapt in real time

AI-driven fraud continues to grow more sophisticated, which means organizations must shift from reactive defenses to proactive, adaptive strategies. Static rules and traditional blacklists can’t keep pace with adversaries using AI to scale attacks, mimic human behavior, and bypass security measures.

The key to effective protection lies in understanding behavior and intent—not just identifying bots versus humans, but determining what each actor is trying to do. To do this effectively, modern fraud detection must:

• Detect threats in real time, without relying on pre-defined rules
• Continuously learn from evolving attack patterns
• Identify behavioral anomalies that hint at automation or suspicious behavior
• Analyze the intent behind each interaction—whether it’s credential stuffing, scraping, or fake account creation

Sophisticated fraud attempts often imitate human behavior, but there are still subtle signs that give them away. Advanced detection systems evaluate:

• Micro-movements, typing cadence, and gesture patterns
• Browser fingerprinting and session behavior
• Deviations from expected context, like unusual sequences or speed

This level of analysis requires AI at the edge, capable of making instant decisions without relying on pre-defined rules alone. DataDome’s multi-layered AI detection engine enhances this capability by combining multiple layers of analysis—behavioral fingerprinting, anomaly detection, machine learning-driven pattern recognition, and intent-based analysis. 

Instead of simply blocking bots, this approach differentiates between malicious automation, legitimate bots, and human users based on behavioral and contextual signals. By leveraging multiple layers of AI-powered detection, DataDome ensures that evolving AI-driven fraud tactics are neutralized in real time without adding unnecessary friction for legitimate users.

How DataDome stays ahead of AI-powered fraud

AI-driven fraud is evolving at an unprecedented pace, making traditional security measures obsolete. Fraudsters are using AI to scale attacks, bypass authentication, and mimic human behavior with increasing sophistication. Businesses need real-time, AI-powered fraud detection that can keep up with these threats—before they cause damage.

DataDome’s AI-powered protection: Stopping ATOs & fake accounts in real time

DataDome takes a proactive, AI-driven approach to stopping fraud at every stage. DataDome Account Protect and Bot Protect work together to detect and block AI-enhanced account takeovers, fake account creation, and automated fraud attempts before they impact your business.

• DataDome Account Protect: Stops ATO attacks, credential stuffing, and fraudsters using AI-driven automation to compromise accounts. By leveraging advanced behavioral analysis and machine learning, it differentiates between legitimate users and malicious bots in real time, ensuring security without disrupting the customer experience.
• DataDome Bot Protect: Prevents AI-driven bots from executing fraud at scale, whether it’s fake account creation, web scraping, payment fraud, or CAPTCHA bypass attempts. Powered by machine learning at the edge, it analyzes 5 trillion signals per day to identify even the most advanced threats.

The future of fraud prevention is AI vs. AI. With fraudsters using AI to outmaneuver traditional security, businesses can’t afford to rely on static, rule-based defenses. That’s why DataDome continuously evolves alongside emerging threats, ensuring real-time, automated fraud detection that keeps AI-powered attackers one step behind.

Want to know where your defenses stand? Take our Bot Vulnerability Assessment or request a live demo to see how DataDome stops AI-driven fraud in real time.