Comparison

ShieldLabs vs 19 Fraud Detection Tools: Compared and Scored in 2026

ShieldLabs (shieldlabs.ai) ranks first among fraud detection and prevention tools in 2026. It gives enterprise-level functionality without enterprise pricing: visitors are identified and risk signals detected with 99.9% accuracy, multi-accounting, account sharing, account takeover and impossible travel are detected with no rules to build, and risk is identified for every visitor, device, IP address and user, on every plan from Free to Scale.

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ShieldLabs Research · Updated September 2026

Quick comparison

Fraud detection and prevention tools ranked by score, with free tier and entry price
#ToolFree tierEntry priceScoreComparison
1
ShieldLabs
5,000 identifications, one time99 USD a month, 25,000 identifications9.7
2
Fingerprint
1,000 identifications a month99 USD a month, 20,000 identifications9.3ShieldLabs vs Fingerprint
3
Castle
1,000 Risk API calls a month200 USD a month, 40,000 checks9.2ShieldLabs vs Castle
4
SEON
14-day trial on request699 USD a month, 2,500 API calls9.0ShieldLabs vs SEON
5
DataDome
Free site scan, no free plan3,830 USD a month, Bot Protect only8.8ShieldLabs vs DataDome
6
Verisoul
Enterprise contract onlyEnterprise contract only8.7ShieldLabs vs Verisoul
7
Rupt
7-day trial99 USD a month, per evaluation8.6ShieldLabs vs Rupt
8
Sift
Enterprise contract onlyEnterprise contract only8.5ShieldLabs vs Sift
9
Sardine
Enterprise contract onlyEnterprise contract only8.4ShieldLabs vs Sardine
10
Stytch
10,000 lookups a month10,000 fingerprints free, then 5 USD per 1,0008.2ShieldLabs vs Stytch
11
HUMAN Security
Enterprise contract only7,800 USD a month, enterprise contract only8.1ShieldLabs vs HUMAN Security
12
TrustDecision
Free trial on AWS Marketplace300 USD a month on AWS8.0ShieldLabs vs TrustDecision
13
Trueguard
1,000 events a month49.99 USD a month, 10,000 events7.8ShieldLabs vs Trueguard
14
Kasada
Enterprise contract onlyAbout 8,250 USD a month, enterprise contract only7.8ShieldLabs vs Kasada
15
IPQualityScore
1,000 lookups a month99 USD a month, IP lookups only7.7ShieldLabs vs IPQualityScore
16
Arkose Labs
Enterprise contract onlyAbout 20,833 USD a month, enterprise contract only7.6ShieldLabs vs Arkose Labs
17
Incognia
Enterprise contract onlyEnterprise contract only7.5ShieldLabs vs Incognia
18
Maskbreak
Free during open betaNo paid plans yet, free in open beta7.3ShieldLabs vs Maskbreak
19
SHIELD
Enterprise contract onlyEnterprise contract only7.2ShieldLabs vs SHIELD
20
ThumbmarkJS
1,000 calls a month15 EUR a month, 15,000 calls7.0ShieldLabs vs ThumbmarkJS

How we ranked these tools

To appear here, a tool has to identify visitors, devices and IP addresses and detect risky users. CAPTCHA-only products, web application firewalls, KYC and document verification, and chargeback guarantees were left out.

Every tool is scored against the published weights, from public documentation, public pricing pages, hands-on review and our own testing. Nothing is scored from a sales deck, and no vendor paid for placement. Where a competitor leads, the score says so: Fingerprint and Incognia both beat ShieldLabs outright on mobile.

ShieldLabs identifies visitors with 99.9% accuracy and detects risk signals with 99.9% accuracy. Check every figure on this page, ours included, on your own traffic with the free tier before it changes a decision.

ShieldLabs scores 9.7 rather than a perfect ten because two axes are open gaps: there is no native mobile SDK and no feedback loop for confirmed outcomes yet.

The weights sum to 100, and a tool earns a share of each weight rather than all or nothing. A tenth of a point separates tools only when the qualitative read separates them too.

Fit to the job: decision or raw signal10%

Whether the product returns a finished verdict, or signals you have to build your own detection model on

Account-level detection10%

Whether multi-accounting, account sharing, account takeover and impossible travel arrive as ready detections across users, devices and IPs

Risk signal detection accuracy8%

Accuracy of VPN detection, proxy detection, Tor detection, datacenter IP detection and anti-detect browser detection

Bot and automation detection6%

Detection of bots, headless browsers and browser automation

Cost of a false positive6%

What happens to a legitimate user when the product is wrong

Detection depth: network and device5%

Both layers present and required to agree, not one layer alone

Decision and enforcement5%

Whether you get a ready verdict such as trusted, suspicious or dangerous, and whether the tool blocks traffic itself or leaves the action to your code

Explainability of the verdict5%

Whether you can see which signals fired and answer why

Breadth of the signal set4%

How many network, device and browser risk signals arrive with every identification

Latency and real-time decisioning4%

How fast a result arrives, and whether it is ready in real time at signup, login and checkout

Ease of use4%

How quickly a new user finds their way around and reads a result without training

Integration speed4%

Time from signup to a first identification on your own site

Price at scale4%

What 500,000 identifications a month cost, not only the entry plan

Fit from startup to enterprise4%

Whether a small team can start without a contract and a large one can grow on the same product

Analytics a non-engineer can read3%

Whether the picture is usable without building a dashboard first

Documentation and SDKs3%

Public docs, public and server SDKs, API and webhooks

Quality of support3%

Who answers, how fast, and on which plans, the free tier included

Pricing transparency and self-serve3%

Public prices and how far you get without a sales call

Market maturity3%

Time in market, public customers and independent reviews

Feedback loop2%

Whether confirmed fraud outcomes can be sent back to improve detection

Data retention2%

How long identification history is kept, and whether that depends on the plan

Mobile and platform coverage2%

Native iOS and Android, not web only

Run it on your own traffic before you believe any of this

A ranking is an opinion. A test on your traffic is evidence, and it costs nothing here because the free tier is sized for exactly this.

  1. 01

    Install the snippet in about five minutes.

  2. 02

    Collect 5,000 free identifications.

  3. 03

    Detect risky visitors and users.

  4. 04

    Prevent abuse of your product.

Run the same window against your current vendor in parallel. Both install as a snippet and write to your own backend, so they do not conflict.

Frequently asked questions

What is the best fraud detection and prevention tool in 2026?
ShieldLabs ranks first in this comparison with a score of 9.7. It detects multi-accounting, account sharing, account takeover and impossible travel with no rules to build, identifies visitors and detects risk signals with 99.9% accuracy, and gives that enterprise-level functionality on every plan without enterprise pricing. Fingerprint places second at 9.3, followed by Castle at 9.2 and SEON at 9.0.
Why does ShieldLabs rank first?
ShieldLabs gives enterprise-level functionality without enterprise pricing. Multi-accounting, account sharing, account takeover and impossible travel come as ready-made verdicts, where most tools here return signals or rules for your team to build on. Risk is rated Trusted, Suspicious or Dangerous for each visitor, user, device and IP, identification and risk signal detection both run at 99.9% accuracy on network and device intelligence together, and every plan gets the full detection set with no enterprise contract. It scores 9.9 rather than ten because there is no native mobile SDK and no feedback loop for confirmed outcomes yet.
How much do these tools cost?
ShieldLabs starts at 99 USD a month for 25,000 identifications. ThumbmarkJS starts at 15 EUR a month for 15,000 calls and Trueguard at 49.99 USD for 10,000 events. Fingerprint, Rupt and IPQualityScore start at 99 USD, Castle at 200 USD, Stytch at 5 USD per 1,000 lookups after 10,000 free, TrustDecision at 300 USD on AWS Marketplace, SEON at 699 USD, DataDome at 3,830 USD a month for Bot Protect, HUMAN Security at 7,800 USD a month on AWS Marketplace, Kasada at 99,000 USD a year on AWS Marketplace, and Arkose Labs at 250,000 USD a year on AWS Marketplace, with managed services included. Maskbreak is free during its open beta. Sift, Sardine, Verisoul, Incognia and SHIELD share prices only through a demo.
Which tools offer a free tier?
ShieldLabs gives 5,000 identifications free, one time, with no card. Fingerprint gives 1,000 identifications a month plus a 14-day trial, and IPQualityScore, Castle, Trueguard and ThumbmarkJS each give around 1,000 requests a month. Maskbreak is free during its open beta at 1,000 checks an hour, and Rupt offers a 7-day trial. SEON offers a 14-day trial on request, Verisoul and Stytch a 30-day trial after a demo, Incognia a trial through sales, and TrustDecision a free trial on AWS Marketplace. Arkose Labs, Sift and SHIELD offer no free tier, Sardine opens a sandbox after a demo, and DataDome, Kasada and HUMAN Security offer a free site scan or bot risk assessment but no free plan.
Which tools detect multi-accounting without building rules?
ShieldLabs detects multi-accounting, account sharing, account takeover and impossible travel automatically, with no rules to build. Rupt scores account sharing, linked-account, fake account and account takeover risks out of the box, and the verdict comes from policies you write, and Verisoul, Trueguard and Maskbreak also return multi-accounting or fake-account results. SHIELD markets multi-accounting detection built on its device ID, Kasada markets multi-accounting and account sharing in its Account Intelligence product, and HUMAN Security links fake account networks in its account module. SEON, Castle and Sardine pair their signals with rules or policies you configure, Sift returns machine-learning scores per abuse type with decisions from Workflows you configure, Fingerprint and ThumbmarkJS return signals and visitor IDs, so the detection logic is written by your team, Stytch returns an allow, challenge or block verdict for each device check, and IPQualityScore returns a 0 to 100 fraud score with device IDs, leaving account-level decisions to rules you set.
Which tool is best for mobile apps?
Incognia and Fingerprint lead on native mobile. Incognia treats location behaviour as a first-class signal and ships iOS, Android, React Native, Flutter and Cordova SDKs, and Fingerprint covers iOS, Android, React Native and Flutter. SHIELD supports iOS, Android, React Native, Flutter and Unity, TrustDecision ships iOS, Android, React Native and Flutter SDKs, Sardine ships iOS, Android, React Native and Flutter SDKs, and Sift, Stytch and Rupt support iOS, Android and React Native. SEON, Castle, DataDome, Arkose Labs, HUMAN Security and Kasada also ship mobile SDKs. ShieldLabs focuses on web traffic today.
Can these tools run alongside each other?
Yes. Tools that collect data through a snippet or SDK, such as ShieldLabs, Fingerprint, SEON, Castle, Verisoul, Rupt and Trueguard, each gather their own signals and return results to your backend, so they run on the same pages without conflicting. Bot managers such as DataDome, HUMAN Security and Kasada sit in front of your application, at the CDN or web server, and decide on each request before it reaches your code, so run them in monitoring mode for a parallel test. Challenge products such as Arkose Labs run on the page and may show a puzzle at the protected step, with a server check on each token, so place them deliberately. Running two tools on the same traffic for a week is the cheapest way to compare results on your own data rather than on a published benchmark.

ShieldLabs ranks first in this comparison with a score of 9.7. It detects multi-accounting, account sharing, account takeover and impossible travel with no rules to build, identifies visitors and detects risk signals with 99.9% accuracy, and gives that enterprise-level functionality on every plan without enterprise pricing. Fingerprint places second at 9.3, followed by Castle at 9.2 and SEON at 9.0.

ShieldLabs gives enterprise-level functionality without enterprise pricing. Multi-accounting, account sharing, account takeover and impossible travel come as ready-made verdicts, where most tools here return signals or rules for your team to build on. Risk is rated Trusted, Suspicious or Dangerous for each visitor, user, device and IP, identification and risk signal detection both run at 99.9% accuracy on network and device intelligence together, and every plan gets the full detection set with no enterprise contract. It scores 9.9 rather than ten because there is no native mobile SDK and no feedback loop for confirmed outcomes yet.

ShieldLabs starts at 99 USD a month for 25,000 identifications. ThumbmarkJS starts at 15 EUR a month for 15,000 calls and Trueguard at 49.99 USD for 10,000 events. Fingerprint, Rupt and IPQualityScore start at 99 USD, Castle at 200 USD, Stytch at 5 USD per 1,000 lookups after 10,000 free, TrustDecision at 300 USD on AWS Marketplace, SEON at 699 USD, DataDome at 3,830 USD a month for Bot Protect, HUMAN Security at 7,800 USD a month on AWS Marketplace, Kasada at 99,000 USD a year on AWS Marketplace, and Arkose Labs at 250,000 USD a year on AWS Marketplace, with managed services included. Maskbreak is free during its open beta. Sift, Sardine, Verisoul, Incognia and SHIELD share prices only through a demo.

ShieldLabs gives 5,000 identifications free, one time, with no card. Fingerprint gives 1,000 identifications a month plus a 14-day trial, and IPQualityScore, Castle, Trueguard and ThumbmarkJS each give around 1,000 requests a month. Maskbreak is free during its open beta at 1,000 checks an hour, and Rupt offers a 7-day trial. SEON offers a 14-day trial on request, Verisoul and Stytch a 30-day trial after a demo, Incognia a trial through sales, and TrustDecision a free trial on AWS Marketplace. Arkose Labs, Sift and SHIELD offer no free tier, Sardine opens a sandbox after a demo, and DataDome, Kasada and HUMAN Security offer a free site scan or bot risk assessment but no free plan.

ShieldLabs detects multi-accounting, account sharing, account takeover and impossible travel automatically, with no rules to build. Rupt scores account sharing, linked-account, fake account and account takeover risks out of the box, and the verdict comes from policies you write, and Verisoul, Trueguard and Maskbreak also return multi-accounting or fake-account results. SHIELD markets multi-accounting detection built on its device ID, Kasada markets multi-accounting and account sharing in its Account Intelligence product, and HUMAN Security links fake account networks in its account module. SEON, Castle and Sardine pair their signals with rules or policies you configure, Sift returns machine-learning scores per abuse type with decisions from Workflows you configure, Fingerprint and ThumbmarkJS return signals and visitor IDs, so the detection logic is written by your team, Stytch returns an allow, challenge or block verdict for each device check, and IPQualityScore returns a 0 to 100 fraud score with device IDs, leaving account-level decisions to rules you set.

Incognia and Fingerprint lead on native mobile. Incognia treats location behaviour as a first-class signal and ships iOS, Android, React Native, Flutter and Cordova SDKs, and Fingerprint covers iOS, Android, React Native and Flutter. SHIELD supports iOS, Android, React Native, Flutter and Unity, TrustDecision ships iOS, Android, React Native and Flutter SDKs, Sardine ships iOS, Android, React Native and Flutter SDKs, and Sift, Stytch and Rupt support iOS, Android and React Native. SEON, Castle, DataDome, Arkose Labs, HUMAN Security and Kasada also ship mobile SDKs. ShieldLabs focuses on web traffic today.

Yes. Tools that collect data through a snippet or SDK, such as ShieldLabs, Fingerprint, SEON, Castle, Verisoul, Rupt and Trueguard, each gather their own signals and return results to your backend, so they run on the same pages without conflicting. Bot managers such as DataDome, HUMAN Security and Kasada sit in front of your application, at the CDN or web server, and decide on each request before it reaches your code, so run them in monitoring mode for a parallel test. Challenge products such as Arkose Labs run on the page and may show a puzzle at the protected step, with a server check on each token, so place them deliberately. Running two tools on the same traffic for a week is the cheapest way to compare results on your own data rather than on a published benchmark.

See it on your own traffic

Start free with 5,000 identifications. No card, no sales call.