
You probably don’t need anyone to tell you that, today, infosec and cybersecurity are challenging and fast-paced endeavors. In the last five years alone, we’ve seen a myriad of industry altering developments — from an ever expanding universe of privacy compliance legislation and the permanent entrenchment of hybrid and remote work, to growth in the size and scope of data breaches — the world of security has proven ever complex and ever-shifting.

As businesses and health organizations seek to strengthen cybersecurity, they’re turning frequently to compliance frameworks to help prioritize, guide, and improve decision-making and implementation. Two of the more popular compliance frameworks are the NIST CSF and the ISO 27001.

Observability (logs, traces, metrics) is a core tenet to building strong software systems. Logs are used to debug issues and check on system activity, traces provide valuable insights into system performance and architecture, and metrics allow engineering teams to closely track business metrics within their systems.

Data exfiltration, quite simply, is the risk of your data ending up somewhere it doesn’t belong. Though this definition might seem simple, understanding this risk is quite complicated — especially as companies migrate their data into the cloud. Companies that work remotely using cloud platforms like Google Drive, AWS, or Jira often struggle to maintain the visibility needed to ensure their data remains secure. This increases the risk of data exfiltration, which can often go undetected for weeks, if not longer.

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.

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.

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.

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. Watch the following clips to learn 5 important lessons about Slack and SaaS security that are worth keeping in mind this year.

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.

The Nightfall blog is a knowledge base for cybersecurity professionals with news and insights from the world of cloud security. Each week, we’re publishing new content to help you stay up-to-date on cybersecurity topics and to prepare you for the issues and threats that occur every day on the job.

This year, Nightfall will be at Dreamforce! With Nightfall for Salesforce, our AppExchange app nearly ready to launch, we’re going to Dreamforce to discuss managing data compliance challenges in Salesforce and best practices that can mitigate compliance violations with regulations like HIPAA, PCI, and GDPR.

Data errors and inconsistencies cost companies millions of dollars a year. Businesses that aren’t able to implement the tools, strategies, and training required often find big data to be more of an obstacle than an advantage. Until business leaders invest in strong data hygiene practices, big data’s promise will continue to remain elusive.

We're excited to announce that Nightfall will be attending Black Hat 2022 conference in Las Vegas this year. Join us if you’re there and interested to learn how you can guarantee continuous cloud data security across all of your environments with Nightfall's ready-to-use SaaS integrations (Slack, Confluence, GitHub, Jira, and more).

The Nightfall platform is a SaaS data protection platform already known for its high accuracy findings and analytics. Now, thanks to new features baked into the Nightfall Console, users will have enhanced analytics functionality through an elegant and easy to navigate dashboard interface.

By one estimate, the average company has a whopping 254 SaaS apps (with enterprises averaging 364 apps). Employees may not be using all 250+ SaaS platforms regularly; this leaves dozens of apps with unchecked access to the business’ IT environment — a big security risk.

There are many types of solutions available to organizations that seek to secure their data in the cloud. From cloud DLP to Cloud Access Security Brokers (CASBs) to Cloud Workload Protection Platforms (CWPPs). But, how can you tell which approach to cloud security is right for your business?

“PII” stands for personally identifiable information. Hackers often target personally identifiable information for a variety of reasons: to steal a customer’s identity, take over an account, launch a phishing attack, or damage an organization. As a result, there is a multitude of regulations concerning PII protection.

Ransomware, phishing, and malware are persistent and ever-evolving threats that today’s remote workspaces need to consider. The shift to a remote-first office, which for many has become permanent, has meant that companies need to be better equipped to protect their data in the cloud.

Third-party risk has always been a concern for organizations, but since COVID and the rise of remote work, we’ve seen a dramatic acceleration in campaigns leveraging software supply chain attacks. Not just through open source vulnerabilities, but through closed source applications and services as well

We recently hosted a live discussion covering emerging trends within the cloud security space, primarily reflecting on how organizations could adopt a posture of continuous security and compliance across their SaaS applications. Continue on below to view the highlights from this discussion.

Healthcare organizations require an effective way to scale HIPAA compliance enforcement across their cloud applications without excessive time and resource commitment. This requires a high-accuracy solution capable of parsing context to identify PHI violations as they are defined by HIPAA
Data loss prevention (DLP) is an important part of data security and compliance in the cloud, especially for organizations regulated by HIPAA. Furthermore, healthcare teams using Slack must follow specific guidelines laid out in Slack’s Business Associate Agreement (BAA).
Data loss prevention (DLP) is an important part of data security and compliance in the cloud, especially for organizations using SaaS applications that store high volumes of data. Companies turn to DLP solutions to discover, classify, and protect their sensitive data in environments like Jira, and maintain compliance with regimes like GDPR, CCPA, PCI, and more.
Data loss prevention (DLP) is an important part of data security and compliance in the cloud, especially for organizations using SaaS applications that store high volumes of data. Companies turn to DLP solutions to discover, classify, and protect their sensitive data in environments like Google Drive, and maintain compliance with regimes like GDPR, CCPA, PCI, and more.

As a result of growing data breaches governments across the world are beginning to implement compliance regimes which require organizations to understand the quantity and nature of that data they’re ingesting. The Nightfall developer platform is designed to help organizations accomplish this with APIs that allow developers to stream data to our machine learning detectors for classification.
As organizations continue to rapidly adopt SaaS and cloud infrastructure, IT and security teams are becoming stretched. The expanding universe of business-critical cloud applications creates increased risk for the exposure of sensitive data like PII, PHI, as well as secrets and credentials. Cloud data protection is essential to ensuring employees follow best practices for handling sensitive data and that systems are configured in a manner that prevents unauthorized access.

