What is account takeover?

Account takeover (ATO) is unauthorized access to and use of an existing user account, where someone logs in as the real account owner using stolen credentials. Unlike account creation fraud, no new account is involved, the existing user relationship is exploited. Entry method: stolen credentials, phishing, or session hijacking.; Goal: unauthorized transactions, data theft, or reselling access.; Difference vs. account creation fraud: the account already exists and belongs to a real user. ShieldLabs surfaces a pattern indicating a possible ATO attempt by flagging when a login comes from an unrecognized device or connection type, regardless of whether valid credentials are used.

What is account takeover fraud?

Account takeover fraud is account takeover carried out for financial gain, turning unauthorized account access into money or resaleable data. It is one of the most common forms of online fraud and costs platforms on two fronts. Direct cost: unauthorized purchases, fund transfers, and chargebacks.; Indirect cost: loss of user trust and reputation damage.; Typical outcomes: data theft, resale of account access, fraudulent transactions. ShieldLabs scores every visitor and user with anonymity signals and a 0–100 Risk Score, and flags suspicious access before the session is established.

What are the red flags for account takeover?

The clearest red flags for account takeover are a login from an unfamiliar device or connection paired with anomalies the real owner wouldn't produce. Most ATO attempts show one or more of the following. Login from a device or browser never previously associated with the account.; Access through a VPN, proxy, or other anonymized connection.; OS or browser fingerprint inconsistencies (a cross-layer mismatch).; Logins from geographically impossible locations within a short window.; Bulk credential testing from the same IP or egress range. ShieldLabs surfaces all of these through 100+ signals analyzed on every login attempt, plus pre-built Patterns indicating account takeover.

How does ShieldLabs detect account takeover?

ShieldLabs detects account takeover by assigning a persistent identifier to every visitor and user, then flagging logins that come from a device or connection never previously tied to that account. The identifier survives cookie clearing and IP changes, so a returning fraudster can't look like a fresh user. Persistent identification: VisitorID and DeviceID link the session to the real account history.; Pattern match: a login from an unrecognized device or connection type triggers a Pattern indicating possible account takeover.; Signal layer: 100+ signals check for VPN, proxy, anti-detect browsers, timezone mismatch, and other anonymity indicators on every login. ShieldLabs delivers the resulting Risk Score and signal breakdown via dashboard, API, and Webhooks so your code can decide what happens next.

What is credential stuffing?

Credential stuffing is an automated method where stolen username and password pairs from data breaches are tested against a target platform at scale. It works because people reuse the same passwords across multiple services, so a fraction of stolen pairs unlock accounts on the target. Source: leaked credential lists from unrelated data breaches.; Method: high-volume automated login attempts, often from rotating IPs.; Why it works: password reuse across different services. ShieldLabs surfaces patterns indicating credential stuffing through Patterns and anonymity signals, flagging the bulk login attempts and anonymized connections that distinguish it from genuine logins.

Will ShieldLabs automatically block suspicious logins?

No, ShieldLabs does not block anything automatically. It returns a Risk Score and a breakdown of anonymity signals on every login, and your code decides what to do with that data. You set the thresholds: for example, require 2FA above a chosen score, deny the session at a higher one.; You own the action: step up authentication, challenge, allow, or block, entirely in your code.; You can tune first: the free tier includes 5,000 identifications to test thresholds on real traffic before enabling rules in your own code. ShieldLabs gives you the signal and the score; the enforcement decision always stays on your side.

How is this different from MFA?

MFA and ShieldLabs solve different parts of the login problem: MFA verifies the person holds a second factor, while ShieldLabs assesses whether the login attempt itself looks suspicious. They are complementary, not alternatives. MFA: confirms possession of a second factor (code, app, key) after credentials are entered.; ShieldLabs: scores the device, connection, and session context on every login, before authentication.; Together: ShieldLabs flags high-risk attempts so you can trigger MFA only when context warrants it. ShieldLabs decides when to trigger MFA, rather than replacing it, keeping low-risk logins frictionless and reserving the extra step for sessions that need it.

What are examples of account takeover?

Common account takeover examples are credential stuffing, phishing, session hijacking, and SIM swapping, each ending with a login from a device or connection the real owner never used. The mechanics differ but the outcome is the same: someone other than the owner gains access. Credential stuffing: breached password lists tested at scale against banking or e-commerce logins.; Phishing: users redirected to fake login pages that harvest their credentials.; Session hijacking: a valid authentication token stolen and reused after login.; SIM swapping: porting a phone number to bypass SMS-based 2FA. ShieldLabs surfaces a pattern indicating these the same way regardless of method, by recognizing the unrecognized device or connection behind the login, often paired with fraudulent purchases or fund transfers right after access.

What is account compromise detection?

Account compromise detection is the practice of identifying when a legitimate account is being used by someone other than its owner. Unlike fraudulent-transaction detection, it operates at the login level rather than waiting for a payment to go wrong. Device recognition: is this a device the account has used before?; Connection analysis: VPN, proxy, anti-detect browser, or residential ISP egress IP.; Session context: timezone, OS, and browser consistency against the account's history. ShieldLabs surfaces patterns that may indicate account compromise on every login by analyzing 100+ device, OS, browser, IP, and network signals and flagging sessions that deviate from the account's established identity.

What are the statistics of account takeover fraud?

Account takeover losses reached 15.6 billion USD in the US in 2024, with 2025 projections near 17 billion USD, making ATO one of the fastest-growing categories of online fraud. The trend lines all point in the same direction. Losses: 15.6B USD (2024) → ~17B USD projected (2025).; Incidence: suspected ATO fraud rates rose 37% from 2024 to 2025.; Credential stuffing: volume grew 148% year-over-year through Q4 2025.; Prevalence: ATO has surpassed ransomware as the top enterprise security concern, with 83% of organizations reporting at least one incident. ShieldLabs works at the device and signal level, surfacing the login anomalies that credential-only defenses miss.

What is ATO prevention?

ATO prevention is the set of technical measures that keep unauthorized users out of existing accounts, and it sits within broader account fraud prevention. The defining trait is that it works at the login level, not after a transaction. Beyond credentials: evaluates the device, connection, and session context of every login.; Continuous: applied to each login attempt, not just at account creation.; Risk-based: lets you reserve friction (like 2FA) for attempts that look anomalous. ShieldLabs implements ATO prevention by assigning persistent identification to every visitor and scoring 100+ signals on every login, flagging suspicious access on the first visit.

What is account takeover protection?

Account takeover protection is the ongoing capability to detect unauthorized account access across all login attempts, so suspicious logins can be challenged or denied. It differs from one-time verification by monitoring every login continuously, not just at account creation. Continuous: every login is evaluated, not only the first one.; Identity-aware: compares each attempt against the user's established device and connection history.; Actionable: returns a Risk Score and signal breakdown your code can act on. ShieldLabs provides account takeover protection by scoring every login from 0 to 100 and surfacing patterns indicating account takeover when an attempt deviates from the user's established identity.

Account Takeover Prevention

Stop account takeover fraud before access is granted

Prevent unauthorized logins, credential stuffing, and suspicious device access without adding friction for real users, through persistent identification and real-time risk scoring on every login

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Account Takeover Prevention illustration

Prevent credential stuffing attacks

Detect automated login attempts exploiting stolen credentials

Detect suspicious logins

Identify logins from unfamiliar connections before access is granted

Protect revenue and brand reputation

Prevent financial losses, protect brand reputation, and build trust with customers and partners

Keep legitimate logins friction-free

Trigger step-up authentication only for high-risk logins, leaving legitimate users unaffected

How ShieldLabs prevents account takeover

ShieldLabs recognizes the real visitor behind every anonymous session, so your team can flag unauthorized access in real time

Accurate Identification

Identify returning visitors and users across sessions, cleared cookies, rotated IP and incognito mode

Anonymity Signals

Detection of VPN, proxy, Tor, anti-detect browser, geolocation spoofing, IP reputation and other anonymity signals on every visit, with up to 99% accuracy

Risk Score

A ready-to-use score reflecting the risk of each visit, with the weight of every signal behind it

Ready-Made Patterns

Pre-built patterns indicating account takeover attempts, impossible travel, credential stuffing and other patterns

Real-Time Analytics

See how much of your traffic is masked, with an overall quality score and a breakdown of the sources sending your visits

Account takeover protection for every attack vector

Stop account takeover fraud before it triggers chargebacks, exposes user data, or damages platform trust

Detect logins from new devices

Accurate Identification helps prevent unauthorized account access before fraudulent activity begins

Surface account takeover patterns

In-depth pattern analytics help identify suspicious login patterns and ATO indicators automatically

Investigate suspicious logins

Per-session signal breakdowns and active patterns give you the data to triage high-risk logins

Keep legitimate users friction-free

Ready risk score helps apply step-up authentication only to suspicious logins

Start preventing account takeover in 5 minutes

Easily integrate into any login or authentication flow

1
Create your account
Get 5,000 free identifications
2
Add the snippet
It identifies every visitor and returns their anonymity signals and a risk score
3
Check your traffic quality
See how much of your traffic is masked, with an overall traffic score
4
Use the API and Webhooks
Apply the risk score and anonymity signals in your rules to stop fraud and abuse