Compare Centinel vs. ShieldLabs

Centinel serves as a protective solution for websites and applications, functioning as both a bot and AI crawler defense platform that authenticates genuine search and AI crawlers while identifying scrapers and automated traffic that mimic actual users. By assessing requests in conjunction with various factors such as browser, connection, and session data, it goes beyond merely relying on a single indicator, effectively differentiating between legitimate crawlers, basic scripts, browser automation tools, faked browsers, and commercial scraping APIs. Organizations can implement a tailored access policy that dictates whether specific traffic should be permitted, challenged, or entirely blocked based on the comprehensive evidence gathered by Centinel. This system operates seamlessly alongside existing infrastructures, with a CDN, reverse proxy, or application consulting Centinel to analyze each request prior to delivering the web page or API response. Notably, Centinel is compatible with environments utilizing Cloudflare, CloudFront, Akamai, Fastly, and other similar edge platforms, which means teams can enhance their security without overhauling their current technological stack. Additionally, this adaptability enables organizations to maintain their operational efficiency while safeguarding against unwanted automation.

ShieldLabs specializes in detecting and preventing fraud while also evaluating traffic quality through sophisticated scoring methods. It effectively combats issues such as multi-accounting, account sharing, account takeovers, fake signups, and ad fraud. By employing a single JavaScript snippet, it gathers over 100 distinct device and network signals during every visit, allowing for comprehensive cross-verification that reveals sophisticated masking techniques and achieves an impressive detection accuracy of up to 99%. Returning users are identified seamlessly, even when using cleared cookies, incognito browsing, or different IP addresses, while linked users can be tracked across multiple accounts and devices. Various elements such as VPNs, proxies, Tor, Apple Private Relay, datacenter IPs, anti-detect browsers, browser automation tools, bots, and AI agents are all categorized as specific signals instead of being reduced to a simple binary flag. Each visitor, user, device, and IP is assigned a unique risk score, and predefined patterns address common fraud scenarios like multi-accounting, account sharing, account takeovers, and impossible travel incidents, with traffic quality evaluated based on its source, channel, and campaign. Integrating the solution takes just five minutes and includes client and server SDKs, a public API, and signed webhooks, making it accessible for businesses looking to enhance their security measures rapidly. As a result, organizations can swiftly implement robust defenses against fraud while maintaining a seamless user experience.