Signal Sciences

概述
总部
美国
|
成立年份
2014
|
公司类型
私营公司
|
收入
< $10m
|
员工人数
51 - 200
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网站
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公司介绍
Signal Sciences 是全球发展最快的网络应用安全公司。凭借其屡获殊荣的下一代 WAF 和 RASP 解决方案,Signal Sciences 每月保护超过 40,000 个应用程序和超过一万亿个生产请求。 Signal Sciences 的专利架构为在现代开发环境中工作的组织提供全面且可扩展的威胁防护和安全可见性。
物联网解决方案
主要客户
安德玛、Aflac、WeWork、星巴克
物联网应用简介
技术栈
Signal Sciences的技术栈描绘了Signal Sciences在分析与建模, 网络安全和隐私, 和 网络与连接等物联网技术方面的实践。
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设备层
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边缘层
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云层
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应用层
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配套技术
技术能力:
无
弱
中等
强
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实例探究.

Case Study
Centralizing Visibility While Reducing Operational Cost
Legacy WAFs provided high operational costs and response times, especially during critical traffic spikes.As the company continued to expand its offerings and provide great digital experiences for its customers, DeNA knew it needed to scale its web security posture to match. But their legacy hardware WAF was causing the team multiple issues and made it difficult to operate efficiently.It was impossible for the DeNA team to reroute customer page requests if their WAF was not performing correctly.The legacy WAF performance, combined with the high price of scaling hardware investments, made it clear to DeNA that they needed a new solution that can perform under pressure.

Case Study
Scaling Attack Detections with Immediate Impact
Lack of visibility into production traffic and new merger and acquisition activity highlighted a need for attack detection modernization.Vimeo is scaling fast but remains highly focused on ensuring the creators and viewers have a seamless experience on their site.To support the company’s recent growth, the Vimeo team knew they had to strengthen their current application security program to prevent prevalent attacks like XSS, SQLi, API abuse, and account takeover.Additionally, they needed a solution that would work seamlessly with their newly built AWS infrastructure without extensive tooling and upkeep. Finally, all requirements had to be consolidated under a single vendor for ease of use across multiple teams.

Case Study
Strengthen Security Posture and PCI Compliance
Eventbrite had lost confidence in their security vulnerability scanner’s ability to identify malicious code or backdoors attackers could leverage and needed a comprehensive solution to protect their global sites and M&A properties.Additionally, Eventbrite was building its security strategy for securing acquired properties. They needed a vendor that could install it easily, provide security coverage quickly, and provide effective web layer security for any future merger or acquisition activity with a single solution.Eventbrite had never utilized a web application firewall (WAF) as part of their security stack: the team was hesitant about the performance, tuning, and maintenance issues that are common with legacy WAFs. But they reached a breaking point with vulnerability scanners and needed a vendor that would restore confidence in their security posture.

Case Study
Leading HR Platform Prioritizes Innovative Security Partnership
As Namely continues to grow its customer base, so does its responsibility to manage web defenses (detection, prevention, and response).Cloud-first, all-in-one HR platform Namely is experiencing rapid growth, which naturally is driving the prioritization of its web defense.Namely looking for production web defense with clear returns on investment. Core criteria included technical alignment, ease of use, best-in-class security functionality, and total cost of ownership.

Case Study
Scaling Security Where Performance is Critical with Signal Sciences
Datadog is a monitoring and security platform service for cloud applications. Thousands of customers rely on Datadog to see metrics and events from software across their DevOps stack, such as cloud and security monitoring, alerts, logs, and more. Founded in 2010, the company rapidly scaled to serve its global customers by embracing the value of modern engineering and architecture practices.As the organization continued to grow, Datadog’s security team knew that their homegrown application security tools would not scale at the rate required to support a rapidly growing customer base. Adopting a WAF was the next move, but Datadog required one that provided flexibility in modern cloud architectures, supported a rapid CI/CD pipeline’s code changes and deployments without extensive tuning, and didn’t unnecessarily consume resources across security, SRE, and development teams.