Intelligent Cyber Threat
Management

Keeping Out Of
The Crosshairs

Mobility and collaboration has led to a greater risk of cyber attacks. As more elaborate novel threats continue to occur, the sharing of threat intel among your technologies is becoming critical to staying ahead of the curve.

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AI Cybersecurity Reality

Artificial intelligence is really a catalyst for cybersecurity. According to Forbes cybersecurity trends for 2023, everything you do is based on the threat horizon. You need to know what is in your system, and who may be doing things that are anomalies. Automated cybersecurity tools of threat detection, information assurance, and resilience can be the glues that will enable business to optimally utilize emerging technologies to operate safely in a world of converged sensors and algorithms in 2023.

A combination of technology and services to protect critical digital assets and data from external threats, and enable attack surface reduction. Visibility into the open (surface) web, social media, dark web and deep web sources to identify potential threats to critical assets and provide contextual information on threat actors, their tactics and processes for conducting malicious activities.

The processes, technology and managed services deployed to discover internet-facing enterprise assets and systems with their associated risks involving vulnerabilities, expired certificates, open ports, amongst many other factors.

A simulated cyber attack against your environment to check for exploitable vulnerabilities.

Services used to prepare for, detect, contain, and recover from a data breach.

Allows enterprises to gain better visibility on their security posture weak spots by automating the test of threat vectors such as external and insider, lateral movement, and data exfiltration. BAS complements, but cannot fully replace, red teaming or penetration testing. BAS validates the security posture of organizations by testing its ability to detect a portfolio of simulated attacks run from SaaS platforms, software agents and virtual machines.

An emerging technology area focused on enabling security teams to overcome asset visibility and exposure challenges. It enables organizations to see all assets (internal and external), primarily through API integrations with existing tools, query consolidated data, identify the scope of vulnerabilities and gaps in security controls, and remediate issues.

Practice of testing the security of an organization’s systems by emulating a malicious actor and hacking into secure systems or data.

Independent assessments of an organization’s externally observable safety and security profile based on publicly available information.

Automates the collection, aggregation, and reconciliation of external threat data, providing security teams with the most recent threat insights to reduce threat risks relevant for their organization.

An emerging approach for architecting composable, distributed security controls that improve overall security effectiveness. Addresses include; centralized policy management and threat databases, a coordinated approach to detection methodology, threat correlation and response, and an increase in the efficiency of cross-tool collaboration.

Traditionally a reactive security function, with sophisticated tooling and advanced technology, such as artificial intelligence (AI) and machine learning (ML). Some organizations leverage DFIR activity to influence and inform preventative measures, thus using as a proactive security strategy.