Cybersecurity Solution Providers

Your starting point will depend on your security framework and goals. Start with visibility and a risk assessment, as it is essential to understanding the assets you need to protect and where your vulnerabilities lie. This foundation will help you improve your organization’s cyber posture over time. Next, implement basic protections such as firewalls and data backups to defend against ransomware and most external malware threats. Afterward, consider adding layers of security by deploying endpoint protection, identity management, network detection, insider threat monitoring and SIEM/SOAR solutions. If your organization uses cloud or AI technologies, choose security tools designed for these environments, such as those that support cloud security or DevSecOps.

No single product can tell you whether you are fully protected against modern cybersecurity threats. Cybersecurity is a layered approach that protects your users, identities, endpoints, networks, applications, cloud environments and data while enabling you to detect, respond to and recover from an attack. The goal is to understand your current architecture, identify gaps and overlaps, prioritize risk and then choose the right combination of technologies and services to meet those requirements.

There are several ways to secure your environment from threats. One way is to adopt a Zero Trust framework or a similar compliance framework to assess your organization. AI tools can be used to automatically map your agency to these frameworks. From there, you can conduct traditional penetration testing and comprehensive table-top or purple team exercises to identify and mitigate potential breaches or threats.

Implementing a Zero Trust Architecture is not achieved by installing a single product. Instead, it is an ongoing security approach that continuously verifies who or what is trying to access your systems and grants access on a need-to-know basis. Adopting Zero Trust happens in multiple phases: 

Phase 1: Start by discovering and listing everything in your environment, including identities, devices, applications, data and networks. 

Phase 2: Strengthen identity controls with tools like multi-factor authentication, single sign-on and conditional access. Be sure to include all types of users, including privileged users, service accounts, machine identities, contractors and third parties. 

Phase 3: Replace network-based trust and set up authorization controls to ensure users can access only the applications they need for their work.  

Phase 4: Secure your devices by ensuring endpoints are encrypted and managed properly. 

Phase 5: Protect your applications and data with DevSecOps tools and data access controls. 

Phase 6: Set up continuous monitoring to spot and respond to suspicious activity across your entire environment. 

Start by implementing data discovery and data tagging processes, typically available through a Data Security Posture Management (DSPM) solution. DSPM tools help you accurately identify and track AI applications within your organization. Additionally, use AI discovery applications to assess cloud risks and monitor AI application access. Lastly, establish a data observability pipeline that funnels all data requests through a central application, allowing you to monitor the AI prompts employees submit and gain better visibility into overall AI usage across your agency.

Protect your account credentials by implementing a Privileged Access Management (PAM) solution that works alongside your cloud identity engine. Security tools can also help identify and remediate Active Directory (AD) misconfigurations, and deception honeypot technology can protect stored credentials. Additionally, implement Single Sign-On (SSO) with Multi-Factor Authentication (MFA) to provide an extra layer of security for your accounts.  

Establishing strong guardrails around AI usage involves several key steps. First, implement thorough data tagging to support your data access policies. Next, use application access management and Data Loss Prevention (DLP) controls to restrict and monitor sensitive information. Specialized tools can also track and control the prompts employees enter into large language models (LLMs). Data tagging helps strengthen existing policies for managing data access. 

Knowing where your data is stored helps you create better access-control policies through cloud gateways, such as CASB (Cloud Access Security Broker) or ZTNA (Zero Trust Network Access), identity management, and DLP solutions. In addition, AI prompt security solutions can monitor and block employees from entering company information or sensitive keywords into AI systems to protect organizational integrity. These protections are enforced through desktop agents or browser extensions, which can also educate the user once an issue is detected. 

Protect production-level applications with lightweight, low-code solutions that operate in real time. Protecting your organization’s most valuable assets requires continuous and dynamic security measures, sometimes at the execution or even the agent layer. Adopting agentic security is essential to safeguard AI access and automate security across your enterprise tools.

Operational Technology (OT) networks present unique challenges as they are highly sensitive, difficult to update, and often cannot be taken offline. 

The first step in securing OT networks is to use passive monitoring solutions that can identify OT-specific protocols and network traffic, then analyze them for vulnerabilities or signs of attack. Next, separate OT devices from IT networks to ensure connections are made only in secure, controlled ways. Carahsoft provides secure remote access solutions that let remote operators connect to OT systems through encrypted channels and segmented networks. These solutions can record each session, making it easier to detect and respond to any abnormal activity.