DEVOPSdigest

Cybersecurity environments have seen nonstop evolution, driven by increasingly sophisticated attack techniques, the expansion of complex cloud-native architecture, and the rise of AI-powered threats that outpace traditional defense strategies. At the same time, development timelines have accelerated, pushing security teams to keep pace without becoming a bottleneck. Faster software release cycles mean security findings must be addressed quickly, making effective prioritization and automation essential to ensuring that security doesn’t slow down innovation but instead becomes an enabler of rapid, secure development.

While innovation thrives, security and development teams are left overwhelmed. According to Seemplicity’s 2024 Year in Review Report, organizations are juggling an average of 8 testing solutions, yet less than 2% of identified risks are truly business-critical, indicating an excessive volume of alert noise. This is leading to alert fatigue, delayed risk reduction, and growing burnout among teams that contribute to remediation efforts.

To address these challenges, organizations must streamline remediation processes by adopting a prioritization-first approach — one that moves beyond static risk scores and incorporates real-world exploitability, business context and operational feasibility. Prioritization ensures that security efforts help development teams focus on fixing the right issues rather than drowning in thousands of findings. When security findings are prioritized effectively, development teams can quickly address the most critical risks and then get back to their core work — building software. This requires integrating automation, Continuous Threat Exposure Management (CTEM), and AI-driven exposure assessment platforms (EAPs). By implementing these methods to cut through alert noise, security teams can proactively identify and mitigate the most significant risks, reducing burnout while strengthening overall resilience.

The Growing Challenge of Vulnerability Management

The National Vulnerability Database (NVD)(link is external) shows a continued rise in reported vulnerabilities. By the end of 2024, the NVD documented over 39,997 vulnerabilities, marking a 39% increase compared to 2023. However, not all vulnerabilities require immediate action, and a lack of effective prioritization can overwhelm security and development teams.

Sticking with traditional remediation processes that don’t meet today’s needs is overwhelming developers, leading to bottlenecks and burnout.

Security professionals are facing high levels of vulnerability noise, inundating teams with alerts, many of which lack definitive risk signals. According to the 2024 Remediation Operations Report, 85% of respondents say noise slows down risk reduction, delaying responses to actual threats. While 95% of organizations are actively looking for ways to reduce this alert noise, recognizing that without proper filtering, teams waste time on low-impact vulnerabilities instead of addressing critical risks.

Leveraging Automation to Streamline Risk Reduction

As security teams struggle with both rising external threats and internal inefficiencies, automation and AI are becoming essential tools for prioritizing findings, reducing manual workloads, and accelerating remediation.

The cybersecurity industry is shifting toward a prioritization-first approach, recognizing that not all vulnerabilities are created equally. The majority of security teams are embracing automation, with 97% of organizations leveraging it in some capacity to streamline vulnerability and exposure management. For instance:

■ 65% use automation for vulnerability scanning, improving detection accuracy. Manual scanning is slow and error-prone, leading to missed vulnerabilities or false positives that overwhelm security teams. Automation ensures continuous, scalable scanning, reducing human error and enhancing the precision of vulnerability detection.

■ 53% use automation for vulnerability prioritization, ensuring critical threats are addressed first. Without automation, security teams are overwhelmed by an unmanageable volume of findings. Sifting through thousands of vulnerabilities to determine which truly matter is a time-consuming and inefficient process. Automated prioritization eliminates this burden by rapidly analyzing massive data sets and surfacing only the vulnerabilities that pose legitimate risk in order of criticality.

■ 41% apply automation to remediation implementation, reducing manual intervention. Traditionally, once remediation tasks are assigned, developers must interpret and prioritize them, and patches must be applied manually — an inefficient process. By automating remediation, organizations can directly implement patches, configuration changes, or mitigation steps without requiring constant human intervention. This eliminates delays caused by ticketing backlogs, miscommunication, or slow handoffs between teams.

Nonetheless, while teams are aware of how automated prioritization and AI-driven security operations are essential, there is still a wide gap to be filled and buy-in needed from leadership teams. 44% of cybersecurity pros still rely on manual processes in some areas of vulnerability management, indicating barriers to full automation, such as complexity in implementation or lack of trust in automated decision-making. Implementing automation isn’t just about deploying a tool — it requires rethinking workflows, integrating with existing systems, and a cultural shift. It’s a daunting and intimidating task that requires sufficient time and attention. Moreover, adopting automation means ensuring that security and development teams trust the outputs. Many organizations struggle with this transition because automation tools, if not properly configured, can generate inaccuracies or miss critical context. Security teams fear losing control over decision-making, while developers worry about receiving even more noise if automation isn’t fine-tuned. Without transparency in how automated systems prioritize risks, skepticism remains a roadblock to adoption.

As AI-powered cyber threats grow more sophisticated, security teams must adopt equally advanced defense strategies. Attackers are already leveraging AI to exploit vulnerabilities rapidly, while security teams often rely on static and manual processes that have no chance of keeping up. AI-enabled EAPs help teams proactively identify and mitigate vulnerabilities before adversaries can exploit them. By automating exposure assessments, organizations can shrink the reconnaissance window available to attackers, limiting their ability to target common vulnerabilities and exposures (CVEs), security misconfigurations, software flaws, and other weaknesses. This proactive approach ensures that security teams stay ahead of evolving threats rather than reacting to breaches after they occur.

Key Takeaways for Security Leaders

To build a more resilient cybersecurity strategy, organizations must move beyond reactive approaches and embrace automated risk prioritization.By cutting through alert noise and focusing on the most critical security findings, security and development teams can allocate resources efficiently and accelerate risk reduction.

Streamlining remediation workflows through automation reduces bottlenecks and accelerates response times without overburdening developers. AI-driven risk analysis further enhances accuracy, helping teams identify patterns and refine prioritization strategies for long-term security improvements.

Adopting strategies like Continuous Threat Exposure Management (CTEM) ensures a proactive approach to identifying and addressing security gaps. By focusing on prioritization, automation, and AI-driven decision-making, organizations can transform cybersecurity from a reactive burden into a strategic advantage — improving protection, operational efficiency, and team well-being.