Account Takeover Prevention: How to Detect and Stop ATO Attacks

Account takeover (ATO) attacks are surging. Veriff’s Fraud Industry Pulse Survey 2026  identified ATO attacks as a top ten fraud type, with respondents reporting ATO attacks as one of the “most feared” in 2026.

ATO attackers use techniques such as credential stuffing, phishing, Man-in-the-Middle (MitM) attacks, and malware to hijack customer accounts. AI-assisted attacks are also on the rise. In our 2026 Identity Fraud Report, we documented a 300X increase in digitally presented media that was either entirely AI-generated or otherwise altered. 

What’s shifted recently is where attackers spend their effort. In the last quarter, our fraud team has seen a measurable shift from credential-stuffing-led ATO toward ‘magic-link’ interception and verification-step attacks — attackers manipulating the identity verification moment itself rather than trying to brute-force their way past it. The signal is clear: as account login flows have hardened (MFA, device binding, passkeys), the IDV moment has become the weakest single link in an otherwise well-defended account lifecycle. That’s the part of the problem this article focuses on.

ATO attacks indicate an identity verification gap within the organization. This article explores the tactics, techniques, and procedures (TTPs) behind ATO attacks, the signals of an ATO, and best practices for account takeover prevention.

Summary of key concepts in account takeover prevention

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Common ATO attack paths

Cybercriminals use innovative approaches to exploit customer accounts, including using AI.

Common ATO attack paths: How cybercriminals hijack customer accounts

Credential stuffing and botnets

Username and password combinations are easily accessible to cybercriminals through data breaches or the purchase of stolen credentials. They use automated tools, such as Atlantis All-In-One (AIO), to test credentials across multiple websites simultaneously to determine which sets provide access. With over 26 billion credentials exposed in data breaches to date, the raw material for these attacks is effectively unlimited.

Secondary mechanisms to prevent automation bots from using credential stuffing to gain unauthorized access are increasingly circumvented. Some tools include CAPTCHA-bypass capabilities. Some tools may exploit poorly configured multi-factor authentication (MFA). For example, by intercepting SMS-based OTPs using real-time phishing proxies or by exploiting weak recovery flows that fall back to email verification. 

Credential stuffing tools are designed to anonymize attacks and prevent detection. The tools use Tor, VPNs, and Proxies to evade detection. Veriffs Fraud Intelligence analyses device, network, and behavioural signals at the moment of verification: datacentre and proxy IP flagging, mobile-vs-desktop fingerprint coherence, sensor and hardware attestation, and timing patterns that distinguish a human attempt from an automated one. But the harder problem with credential stuffing isn’t catching a single attempt — it’s recognizing the campaign. A residential-proxy-fronted attempt against one customer looks like a noisy false positive in isolation. The same device fingerprint surfacing across three customers in two industries within 48 hours is unambiguous.

This is where CrossLinks does work no single-tenant vendor can replicate. By linking sessions across our entire customer network through document, device, biometric, and network signals, we surface the campaign view — fraud rings recycle the same compromised devices and credentials across our customers, and CrossLinks turns that recycling into our signal advantage. Catching the first attempt at customer A means the second, third, and four-hundredth attempt at customer B is already on a watchlist. Session hijacking

Session hijacking is a technique that intercepts a user’s active session token, thereby bypassing authentication. The attacker doesn’t need a password. Instead, they inherit a session that allows them to appear to be a legitimate user who has logged in.

Common session hijacking techniques include:

• Cross-site scripting (XSS) steals session cookies.
• Man-in-the-Browser (MitB) uses malware to intercept tokens in real time.
• Session fixation:  An attacker sets a known session ID before the victim logs in.
• Network-level interception is used on unsecured Wi-Fi networks.

What makes session hijacking particularly dangerous is that, from the platform’s perspective, the session looks entirely legitimate. The IP, device, and browser may all match the original user’s profile. Detection requires behavioral anomaly analysis, i.e., changes in navigation patterns, transaction velocity, or geographic shifts mid-session, combined with continuous device fingerprint validation. Veriff’s Device Intelligence includes behavioral anomaly analysis beyond pure session-based authentication.

SIM swap

SIM swap fraud exploits mobile carrier processes. The attacker convinces or bribes a carrier employee to transfer the victim’s phone number to a new SIM card. Once they control the number, they can intercept SMS-based OTPs and reset passwords on any account that uses phone-based verification. A SIM swap attack makes an authentication flow that relies on SMS as a second factor redundant. 

In 2025, the FCC strengthened SIM swap rules in the US; however, enforcement remains inconsistent. 

Ensure that any authentication reset or step-up flow includes a biometric identity check that can’t be intercepted over a phone network. Veriff’s Biometric Authentication product includes selfie-to-selfie matching against an enrolled identity, bound to the person rather than to a device or phone number.

Social engineering and phishing campaigns

Phishing remains the second most prolific ATO vector because it is easy to scale. Modern phishing campaigns use AI-generated content to produce near-perfect replicas of legitimate communications. Real-time phishing proxies now act as transparent reverse proxies between the victim and the real login page, capturing credentials and session tokens simultaneously, bypassing even MFA.

One of the most dangerous phishing variants for identity verification platforms is the ‘magic link’ interception attack. The attack exploits a legitimate verification URL using social engineering or malware. The ruse redirects the target to authenticate a session. The victim unknowingly completes identity verification on the fraudster’s behalf. What makes this attack genre uniquely difficult is that every individual signal looks correct. The document is real. The face matches the document. The liveness check is genuine. The selfie isn’t a deepfake or an injection — it’s a person, biometrically present, voluntarily completing the flow. Most fraud controls in the IDV industry are designed to answer the question “is this the right person?” — and the honest answer in a magic-link interception is yes. The attacker has weaponized that ‘yes.’

The defensive shift this requires is conceptual, not just technical: identity verification has to evolve from confirming who to confirming who, doing what, with what intent.

Veriff is actively building defenses against this vector, including behavioral checks that verify not just an individual’s identity but also capture the intent to authorize a specific action. 

GenAI bots

First-gen malicious AIs, such as WormGPT, FraudGPT, along with newer candidates, HackerGPT, Xanthorox, are expected to become a central aspect of many ATO attacks, making detection and prevention more complex. The Veriff Fraud Industry Pulse Survey 2026 found that over 78% of businesses expect to see more AI-powered fraud in 2026.

In the Dark Side of GenAI report, a prompt-injection contest was held to find ways to trick a chatbot into revealing a password. The results found that 88% of the contestants could use a chatbot to reveal passwords. 

Survey results show that most businesses expect more AI and deepfake-powered fraud in 2026 (source)

Emulators in ATO attacks

Emulator tools are used legitimately by software testers to make testing applications across multiple devices and operating systems easier. However, in the hands of cybercriminals, an emulator becomes an effective weapon for account takeover. 

During an ATO attack, an emulator is used to replicate a user session, thereby bypassing security measures and making it difficult to detect an ATO in progress. Advanced ATO toolkits combine emulators with residential proxies to mimic the victim’s typical device profile and geographic location. Emulators also allow fraudsters to scale their attacks. 

Emulators and spoofing are one of the hardest evasion techniques to detect with traditional methods. Veriff’s Device Intelligence analyzes low-level device signals to flag emulated environments, even when the emulator is configured to replicate a specific device model and OS version. Combined with our CrossLinks technology, which links sessions by device, document, face, and network signals across our entire verification network, we can identify patterns invisible to any single customer view.

Blind spots and warning signs

ATO is challenging to detect. However, some unusual account behaviors

point to a customer account that may be under attack. Identifying these indicators of an ATO attack is an essential element of protecting customers and controlling fraud.

Multiple logins from different geo-locations

Login attempts to a single account from multiple IP addresses and geo-locations could be a sign of an ATO event. Customers tend to use one or two familiar locations to log in to an account.

Multiple failed logins

Repeated failure to present the correct credentials at login could indicate an ongoing ATO. However, this is becoming less common as cybercriminals shift from brute-force attacks to more successful phishing campaigns, SIM swap attacks, and session hijacking.

Multiple accounts accessed from the same device

This signal could be multiple users in the same household using a shared computer. However, it may also be a sign of an ATO. Cybercriminals are likely to access multiple accounts (sometimes hundreds or thousands) from the same device. Our recent research on fraud rings revealed that their operations are rarely limited to one-off attacks; they routinely adapt tactics and leverage insider knowledge to avoid detection. 

Unexpected account changes and patterns of behavior

People tend to form habits in their account usage and buying patterns. If a customer makes changes to their personal data, especially email address, home address, and phone number, along with other unusual behavior such as logging in from a new device, this is likely an indicator of an ATO attack.

Multiple accounts containing similar data

After a successful ATO, fraudsters will change information such as mobile numbers and email addresses. Look for signs of multiple accounts changing personal details, such as mobile numbers and email addresses, as this could indicate an ATO.

Multiple unusual activity signals

Look for unusual activity, such as logging in from different locations in a short time and using a new device. 

This includes shifts in typical user behavior, such as a sudden high volume of transactions, an unusually large purchase, or changes to typical navigation paths within the application. These anomalies can be an indicator that the account is being controlled by a fraudster who is unfamiliar with the legitimate user’s routines. 

Best practices for ATO prevention

The following best practices ensure your customer accounts receive the highest level of security.

Perform a risk assessment

The risk assessment of potential account takeover (ATO) attacks is a formal review that gathers intelligence from across IT systems and human operators to identify vulnerabilities in customer accounts. 

The review process should cover the entire lifecycle of an identity account, from initial registration through to usage patterns and account closure. Catalog all aspects of identity security, including people, apps, devices, and sensitive data. Include early-stage or new accounts used by cybercriminals to create ‘placeholder’ or ‘sleeper’ accounts, ready to be exploited at the right time. 

The assessment should also evaluate the impact of an ATO attack on customer accounts. For example, there may be financial and liability implications if customer accounts are hijacked.

Systems that do not use robust verification during registration are at risk of early-stage identity fraud. Help with structuring your risk assessment can be found in the National Institute of Standards and Technology (NIST) Cybersecurity Framework and the International Organization for Standardization (ISO) 27001. 

Identify account assessment

An assessment of ATO risk begins with cataloging all aspects of identity security, including people, apps, devices, and sensitive data. The account lifecycle areas and account types that must be covered include early-stage or new accounts used by cybercriminals to create ‘placeholder’ or ‘sleeper’ accounts, ready to be exploited at the right time. Systems that do not use robust verification during registration are at risk of early-stage identity fraud.

The assessment should evaluate the impact of an ATO attack on customer accounts. For example, there may be financial and liability implications if customer accounts are hijacked.

Use assessment data to establish areas of weakness and inform security policies

The intelligence gathered during the identity account assessment stage informs identity security measures. Identity verification is one measure for mitigating risk.

Other security measures, such as robust authentication and behavioral biometrics, must be evaluated for inclusion in security policies. Developing the priorities for measures is the next step in the ATO risk assessment exercise.

Perform a mapping exercise to identify appropriate measures

Determining the most appropriate measures to mitigate the risk of account takeover attacks is essential in optimizing your cybersecurity approach to ATO.  Once you have gathered your threat analysis intelligence, create a risk assessment table that displays the risk, a description, and the level. Use this table to generate a risk mitigation and measures table.

Risk assessment table example

Risk mitigation and measures table example

Determine identity verification policies

Identity verification reduces the risk of ATO by establishing an assured identity account from the outset. Re-verification can then take place if ATO is suspected or when rules, such as a transaction over a certain amount, are triggered. 

According to Veriff’s Identity Fraud Report 2026, 4.18% of all verification attempts were fraudulent in 2025 – meaning one in every 25 verification attempts we encountered in the last 12 months was someone pretending to be someone else. 

Digitally presented media was 300% more likely to be either entirely AI-generated or otherwise altered. Impersonation fraud amounted to more than 85% of all fraud attacks we encountered this year, making it by far the most common type of online fraud. 

Veriff combines AI with a high-resolution facial biometric system to quickly identify an individual while reducing the likelihood of streamed or pre-recorded videos, synthetic or manipulated images, and AI-generated deepfakes. 

Establish initial verification policies

An identity verification (IDV) process involves using various elements to uniquely and securely identify that individual. 

For example, the person may be required to provide identity documents (e.g., a passport) during registration, have facial biometrics captured, and undergo name and address checks. 

IDV checks should be aligned to various local and global regulations, such as KYC (Know Your Customer) and AML (anti-money laundering). 

Develop rules and events that trigger re-verification

Re-verification will take the user through a process to re-check their identity. Re-verification rules are triggered, e.g., when a high-value transaction occurs.  

If a fraudster hijacks an account and attempts to use it for financial transactions, a re-verification check is likely to hinder the attempt.

Map policies to local and global regulations

Mapping the verification and reverification policies to local and global regulations is an essential exercise. When deciding on the type of verification required, a business must double-check that the requirements meet regulatory requirements such as AML and KYC. Verifying an individual involves handling personal and sensitive data, so the business must balance the need to verify with privacy regulations such as the GDPR. Regulations such as the EU AML Regulation (AMLR/AMLA) require that entities conduct ongoing monitoring and risk-based reverification.

Define verification and authorization policies and measures

Robust authentication and authorization policies help reduce the risk of ATO. The following measures are likely to be part of your risk assessment outcomes:

Implement a zero-trust environment

Zero trust is based on network segmentation to contain breaches and on continuous monitoring to prevent them or quickly detect potential security events. Underpinning Zero trust is robust verification. In this case, customers must be authenticated for access requests and granted only the access privileges necessary to perform a task (the principle of least privilege, or POLP). Continuous monitoring is essential.

Ensure liveness detection is enabled

Identity verification itself is a target for ATO attackers. Facial biometrics has been shown to significantly reduce the likelihood of verification subversion, but the system must support liveness detection. Veriff liveness uses a mix of AI and a high-resolution facial biometric system to quickly identify an individual while reducing the likelihood of streamed or pre-recorded videos, synthetic or manipulated images, and AI-generated deepfakes. Customers have a streamlined experience using a selfie to complete verification.

Use biometric solutions that incorporate anti-spoofing technology

Cybercriminals use sophisticated techniques to spoof verification systems, including emulators and virtual cameras. A multi-layered defense must analyze the face, device, sensor, timestamp, and behavioral data to enable accurate spoofing detection.

Use behavioral adaptation technologies

Facial biometrics must use multiple anti-fraud signals to ensure an accurate match. Veriff, in addition to using real-time liveness detection, captures behavioral, device, and network risk signals to detect fraudulent activity.

Apply risk-based authentication

For high-value or highly sensitive transactions, customers can be taken through a step-up authentication and verification process. Step-up authentication and verification are driven by trigger points that prompt additional security measures, such as re-verification.

Deploy passwordless authentication

Massive data breaches that include compromised username-password combos, combined with MFA workarounds, are driving a passwordless future. A report from The FIDO Alliance (Fast Identity Online), an industry association Veriff is a member of, is behind the passwordless mechanism, passkeys, found that 87% of decision makers are deploying passkeys at their companies. Biometrics and passkeys can eliminate passwords and can be further combined with multi-factor authentication (MFA) for high-value or sensitive transactions.

Use biometric solutions that incorporate anti-spoofing technology

Cybercriminals use sophisticated techniques to spoof verification systems, including emulators and virtual cameras. A multi-layered defense must analyze the face, device, sensor, timestamp, and behavioral data to enable accurate spoofing detection.

Facial biometrics must leverage multiple anti-fraud signals to ensure accurate matches. The system must also support liveness detection.

Veriff liveness uses a mix of AI and a high-resolution facial biometric system to quickly identify an individual while reducing the likelihood of streamed or pre-recorded videos, synthetic or manipulated images, and AI-generated deepfakes. Customers have a streamlined experience using a selfie to complete verification. It has been found to reduce ATO by 80% – 90%, providing the following benefits:

• Lower fraud risk – Passive liveness and fraud detection via face blocklisting and device fingerprinting
• Faster logins – Less than 1 second response time
• Seamless experience – No need to leave the user journey for OTPs
• Enhanced security – Biometrics are unique, hard to spoof, and cannot be shared
• Reduced human error – No passwords to type or manage

Implement ATO real-time threat intelligence

New threats, such as AI-assisted attacks, change the metrics of response. An essential aspect of ATO threat mitigation is ongoing threat monitoring. It identifies unusual activity centered on actions such as:

• Account activity monitoring and user profiling.
• Account access activity, such as unusual logon events (e.g., from a new location), as well as unusual data exfiltration. 
• Unusual email activity, such as changing forwarding rules.
• Analysis of IP addresses used during account login.
• Device security monitoring to prevent SIM swap.

Educate customers on ATO tactics and signs

Account takeover threats often use social engineering to initiate the attack. Customers are at risk from attacks that contain a social element, such as phishing. To help prevent ATO attacks, it is important to educate customers on how to identify potential phishing attempts and other cyber threats. Organizations can offer education through a blog post campaign explaining how cybercriminals use social engineering to access customer accounts. Other channels, such as email newsletters and social media, can also help customers remain vigilant about the dangers of an ATO.

Document incident response plans

The response plan is essential for quickly restoring business operations and mitigating the impact of an ATO incident. NIST provides best practice guidance, based on four steps:

1.     Preparation
2.     Detection and Analysis
3.     Containment, Eradication, and Recovery
4.     Post-Incident Activity

The four-step best practices in creating a response plan can be applied to ATO attacks, for example:

1.     Preparation: Perform a risk assessment to understand key risk areas and priorities.
2.     Detection and Analysis: Implement real-time ATO threat intelligence.
3.     Containment, Eradication, and Recovery: Deploy measures such as email security and secure backups. Recovery will involve processes that close any affected identity accounts.
4.     Post-Incident Activity: Implement employee security awareness training programs, revisit your verification and authentication options, and audit and review your responses to ATO attacks.

 Four stages of incident response for account takeover events (source)

Since preparation, detection and analysis, and post-incident review are covered elsewhere in this article, the most relevant part to focus on here is containment, eradication, and recovery. In an account takeover scenario, this means quickly securing affected accounts, terminating suspicious sessions, blocking further unauthorized access, reversing fraudulent changes where possible, and restoring control to the legitimate user. It can also involve credential resets, reverification, linked-account investigation, and monitoring for follow-on fraud attempts. The insights gained during this stage should then feed back into future preparation and improvement. 

Audit and review response to ATO attacks

Important to maintain effective ATO attack detection and prevention.

•   Perform regular security audits
•   Check the veracity of authentication
•   Validate consistent application of authentication and authorization policies
•   Are current incident response guidelines still appropriate?
•   Simulate breach scenarios and test responsiveness

Conclusion

The FBI Internet Crime Complaint Center (IC3) received approximately 4,700 public complaints in 2025 about consumer ATO, with attacks resulting in $359.7 million in losses. ATO attackers are using increasingly sophisticated techniques and tactics to exploit customer accounts. Login is no longer the primary battleground as Passkeys, device binding, and phishing-resistant MFA close the entry points. FIDO’s 2026 data shows 75% of consumers globally have enabled a passkey on at least one account, and nearly half use them regularly. Attackers know this, so their energy is now moving to the moments that gate the account rather than the moments that open it— account recovery flows, step-up verification at high-value transactions, new device enrollment, and payout authorization. Anywhere a re-verification or magic-link sits between an attacker and an outcome, that’s the new attack surface. However, the era of credential stuffing is not over, with attackers operating upstream of the password and downstream of the login. 

A mix of solutions must be deployed to detect and prevent this most insidious and damaging of cyberattacks. Measures such as verification and authentication are at the forefront of ATO attack prevention. However, solutions must balance customer experience with security. Passwordless authentication, biometric liveness, and risk-based reverification are no longer optional extras; they are becoming core requirements for effective account takeover prevention.”