Nightfall vs. Fidelis Network

Discover, organize, and protect your confidential information with Nightfall™, a solution that uses machine learning to identify crucial business data like customer Personally Identifiable Information (PII) across your SaaS platforms, APIs, and data repositories, facilitating effective oversight and security measures. Its rapid integration capability via APIs allows for effortless data monitoring without the requirement for agents, providing a seamless experience. Nightfall’s advanced machine learning algorithms guarantee accurate categorization of sensitive data and PII, ensuring a thorough approach to data protection. You can establish automated workflows for actions such as quarantining, deleting, and alerting, which significantly improves efficiency and strengthens your organization’s security posture. Nightfall easily integrates with all your SaaS applications and data frameworks, making it a versatile tool. Initiate your journey with Nightfall’s APIs at no cost to achieve effective classification and safeguarding of sensitive data. Through the REST API, you can access structured results from Nightfall’s sophisticated deep learning detectors, which can pinpoint sensitive information like credit card numbers and API keys, all while requiring minimal coding efforts. This seamless integration of data classification into your applications and workflows using Nightfall's REST API lays a strong groundwork for effective data governance. By choosing Nightfall, you not only secure your data but also enhance your organization's compliance capabilities while fostering a culture of data responsibility. This comprehensive approach ensures that sensitive information remains protected in an increasingly regulated environment.

To successfully identify advanced threats, it is crucial to perform detailed inspections, extractions, and real-time analyses of all content moving through the network. Fidelis' network detection and response technology meticulously examines all ports and protocols in both directions, collecting extensive metadata that forms the basis for powerful machine-learning analytics. By employing sensors to monitor internal communications, email, web, and cloud interactions, organizations can achieve complete visibility and coverage across their networks. The tactics, techniques, and procedures (TTPs) used by detected attackers are mapped to the MITRE ATT&CK™ framework, empowering security teams to proactively combat potential threats. Although threats may try to avoid detection, they are ultimately unable to escape scrutiny. Organizations can also automatically profile and classify IT assets and services, which includes enterprise IoT devices, legacy systems, and shadow IT, thus constructing a comprehensive overview of their cybersecurity landscape. Additionally, when combined with Fidelis' endpoint detection and response capabilities, users gain an inventory of software assets linked to known vulnerabilities such as CVE and KB references, along with an evaluation of security hygiene pertaining to patches and endpoint statuses. This thorough and strategic approach provides organizations with the necessary tools to uphold a strong cybersecurity posture, ensuring ongoing protection against evolving threats. Ultimately, fostering a culture of continuous improvement in cybersecurity practices can further enhance resilience against future attacks.