All Smart Risk Decisions Start With Powerful Detection
Despite significant investments in fraud and bot detection, attackers are more adept than ever at circumventing detection and costing businesses money. Powerful detection that starts at the top of the customer journey enables you to catch attacks faster, reduce false positives and false negatives, and determine the most effective response to sabotage attackers’ efforts.
DYNAMIC DECISION ENGINE
Improve Decisioning Confidence
Arkose Labs’ decision engine is uniquely designed to balance detection precision and recall, blending the transparency of rules with the accuracy of machine learning models. A dynamic risk score reduces the complexity of decisions, giving fraud teams clear and confident insight to respond faster to high-risk traffic.
- Powered by 150+ adaptive global rules
- Transparent risk scoring
- Correlates real-time, historic, customer-specific, and global data
- Customizable by attack target, industry vertical and use cases
Get 70+ Data Attributes for Your Data Models
A machine-given score without supporting data is no longer enough. Arkose Labs provides 70+ raw risk insights for greater visibility and intelligence that you can use to take action.
Get 35x More Data than reCAPTCHA to Enhance Risk Models
A machine-given score without supporting data is no longer enough. Arkose Labs provides 70+ raw risk insights for greater visibility and intelligence that you can use to take action.
Insights about risk degree and type. Followed by a more precise score and risk calculation factors
Transparency via details of what happened in the user session
Signatures based on, and data from, the browser and device attributes
Signatures based on and enriched data from IP and network attributes
How often IPs are seen over a given time period to detect high-volume and low-and-slow attacks
{
"session_risk": {
"risk_category": "BOT-STD",
"risk_band": "Medium",
"global"
{
"score": "15",
"telltales":[
{
"name": "g-h-cfp-1000000000",
"weight": "7"
}
{
"name": "g-os-impersonation-win",
"weight": "8"
}]
}
"custom"
{
"score": "15",
"telltales":[
{
"name": "outdated-browser-yandex-2",
"weight": "7"
}
{
"name": "outdated-os-yandex",
"weight": "8"
}]
}
},
"session_details": {
"solved": true,
"session": "22612c147bb418c8.2570749403",
"session_created": "2021-08-29T23:13:03+00:00",
"check_answer": "2021-08-29T23:13:16+00:00",
"verified": "2021-08-30T00:19:32+00:00",
"attempted": true,
"security_level": 30,
"session_is_legit": false,
"previously_verified": true,
"session_timed_out": true,
"suppress_limited": false,
"theme_arg_invalid": false,
"suppressed": false,
"punishable_actioned": false,
"telltale_user": "eng-1362-game3-py-0.",
"failed_low_sec_validation": false,
"lowsec_error": null,
"lowsec_level_denied": null,
"ua": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.159 Safari/537.36",
"ip_rep_list": null,
"game_number_limit_reached": false,
"user_language_shown": "en",
"telltale_list": [
"eng-1362",
"eng-1362-game3-py-0."
],
"optional": null
},
"fingerprint": {
"browser_characteristics": {
"browser_name": "Chrome",
"browser_version": "92.0.4515.159",
"color_depth": 24,
"session_storage": false,
"indexed_database": false,
"canvas_fingerprint": 1652956012
},
"device_characteristics": {
"operating_system": null,
"operating_system_version": null,
"screen_resolution": [
1920,
1080
],
"max_resolution_supported": [
1920,
1057
],
"behavior": false,
"cpu_class": "unknown",
"platform": "MacIntel",
"touch_support": false,
"hardware_concurrency": 8
},
"user_preferences": {
"timezone_offset": -600
}
},
"ip_intelligence": {
"user_ip": "10.211.121.196",
"is_tor": false,
"is_vpn": true,
"is_proxy": true,
"is_bot": true,
"country": "AU",
"region": "New South Wales",
"city": "Sydney",
"isp": "Amazon.com",
"public_access_point": false,
"connection_type": "Data Center",
"latitude": "-38.85120035",
"longitude": "106.21220398",
"timezone": "Australia/Sydney"
},
"aggregations": {
"ip":{
"short_term": {
"interval_minutes": 60,
"count": 22,
"threshold": 11
},
"long_term": {
"interval_minutes": 720,
"count": 22,
"threshold": 50
}
}
}
}
Data about risk degree and type.
{
"score": 0-100,
"reasons": [
enum (CLASSIFICATION_REASON_UNSPECIFIED, AUTOMATION, UNEXPECTED_ENVIRONMENT, TOO_MUCH_TRAFFIC, LOW_CONFIDENCE_SCORE)
]
}
24/7 SOC MONITORING & TUNING
Uncover More Threats With Dedicated SOC Support
Our 24/7 SOC works as an extension of your team to thwart attacks, fine-tune detection, and deliver actionable insights - without putting a strain on your internal resources.
- Emerging attack pattern analysis
- Supervised ML models
- Collaborative, ongoing tuning
- Under-attack and special event support
Powered by Cross-Industry Network Intelligence
Arkose Labs’ customers fight better together, thanks to 3B anonymized attack patterns uncovered each year across the Arkose Labs Global Network.