The market for penetration testing is expected to reach $3.1 billion by 2027, rising at a market growth of 12% CAGR during this time. Fueled by the rising number of mega-breaches and more sophisticated attacks, IT teams are taking a more proactive approach, using penetration testing to validate and improve their security configurations. As more organizations do business on SaaS and cloud programs, penetration testing is becoming an important complement to cloud data loss prevention tools.

Here at Nightfall we ensure that we are always using the most appropriate technology and tools while building services. Our architecture involves serverless functions, relational and NoSQL databases, Redis caches, Kafka and microservices written in Golang and deployed in a Kubernetes cluster. To effectively monitor and easily troubleshoot our services, we use distributed tracing across our services.

Mega-breaches, or reported breach incidents that impact more than one million records, have increased dramatically. Our analysis shows that, on average, mega-breaches increased 36% year over year since 2016. In total, mega-breach incidents that we analyzed cost at minimum a combined $8.8 billion and exposed 51 billion records.

Jira and Confluence house high volumes of customer information, tickets, notes, wiki articles, and more. To scan Jira and Confluence Data Center or Server editions, you can use Nightfall’s APIs to scan data at-rest in these silos. In this article, we’ll walk through how you can run a full historical scan on your Jira and Confluence data to discover sensitive data, like API keys and PII. The output will be a report detailing the sensitive findings discovered in your environment.

Data leaks are a type of data loss threat that often fly under the radar — making them potentially more damaging than a malware or ransomware attack. Compared to data breaches, data leaks put customer information at risk accidentally. Data leaks can lead to credit card fraud, extortion, stolen IP, and further attacks by cybercriminals who seek to take advantage of security misconfigurations.

Last month, on December 8, we hosted a webinar alongside Bluecore CISO Brent Lassi to discuss data security risks facing high-growth organizations like his on SaaS systems like Slack. With 2022 just beginning, we wanted to share 5 important lessons about Slack and SaaS security that are worth keeping in mind this year.

DLP ensures confidential or sensitive information (like credit card numbers, PII, and API keys) isn’t shared outside of Slack by scanning for content within messages and files that break predefined policies. DLP is important for both security and compliance reasons. With DLP in place, you’ll be able to.

Salesforce houses high volumes of customer information, support tickets, quotes and files, synced emails, tasks & notes, and much more. This data can often be accessed by teams across the company who may leverage Salesforce to provide prospects and customers with a great customer experience. However, allowing sensitive data like PII and credit card numbers to live within Salesforce can pose security & compliance risks.

Some of the most damaging data leaks have resulted from poor database security. In March 2020, 10.88 billion records were stolen from adult video streaming website CAM4’s cloud storage servers. In March 2018, 1.1 billion people were the victim of a breach of the world’s largest biometric database, Aadhaar. And, in April 2021, 533 million users had their information compromised when a Facebook database was leaked on the dark web for free.