The old saying goes, “practice what you preach.” When Ivanti started its "Customer Zero" initiative, Bob Grazioli, Chief Information Officer, saw it as a perfect opportunity to test the products and services consumed by customers. For example, during Ivanti’s move to the cloud, Grazioli and the team experienced the same issues that customers would’ve experienced in their migration process. This first-hand experience allowed them to make improvements along the way.
The security of your organization’s network is paramount to its success. With the ever-changing landscape of cyber threats, it's important to take the necessary steps to ensure that your network is secure and compliant with industry regulations. Ensuring compliance requires you to know what’s on your network. But how can that be done when only 48% of leaders and security professionals say they run their asset discovery program at least once per week?
Increases in attack surface size lead to increased cybersecurity risk. Thus, logically, decreases in attack surface size lead to decreased cybersecurity risk. While some attack surface management solutions offer remediation capabilities that aid in this effort, remediation is reactive. As with all things related to security and risk management, being proactive is preferred. The good news is that ASM solutions aren't the only weapons security teams have in the attack surface fight.
Resistance to change is always present, especially if you think the processes you have in place are efficient and effective. Many organizations feel this way about their software management procedures until they have a security breach or incident and are left wondering where they went wrong. The reality is that most patch management programs are built on assumptions and recommendations, rather than facts about actively exploited vulnerabilities. Risk-based patch management is the answer to this issue.
There has been growing interest in the capabilities of generative AI since the release of tools like ChatGPT, Google Bard, Amazon Large Language Models and Microsoft Bing. With the hype comes concerns about privacy, PII, security and, even more importantly, accuracy. And rightly so. Organizations are treading cautiously with their acceptance of generative AI tools, despite seeing them as a game changer.