NIST Deprioritizes Pre-2018 CVEs Amid Backlog and New Threats

Article Highlights
Off On

The US National Institute of Standards and Technology (NIST) recently made a significant decision affecting the cybersecurity landscape by marking all Common Vulnerabilities and Exposures (CVEs) published before January 1, 2018, as “Deferred” in the National Vulnerability Database (NVD). This move impacts over 20,000 entries and potentially up to 100,000, signaling that these CVEs will no longer be prioritized for further enrichment data updates unless they appear in the Cybersecurity and Infrastructure Security Agency’s (CISA) Known Exploited Vulnerabilities (KEV) catalog. NIST’s decision comes in response to an ongoing struggle with a growing backlog in processing vulnerability data, exacerbated by a 32% surge in submissions in the past year.

An Overwhelming Backlog and Strategic Reprioritization

NIST’s challenges in processing and enriching the vast amount of incoming data have delayed its goal of clearing the backlog by the end of fiscal year 2024. In response, NIST is developing new systems to handle these issues more efficiently. Industry experts consider this move practical given the complexities of managing vulnerabilities at scale. Ken Dunham from Qualys describes it as an evolution in the face of changing cyber threats. Meanwhile, Jason Soroko from Sectigo interprets this as a strategic reprioritization, with resources redirected towards addressing emerging threats, assuming that legacy issues have been mitigated through routine patch management practices. The responsibility for managing deferred CVEs now shifts more heavily onto organizations. For security teams, this means identifying and monitoring legacy systems, prioritizing the patching of deferred vulnerabilities, and hardening or segmenting outdated infrastructure. Using real-time threat intelligence to detect attempts at exploiting these vulnerabilities becomes crucial. This shift highlights a broader trend where organizations must adopt proactive risk management strategies due to the increasing volume of CVEs and limited resources available to handle them.

Embracing Advanced Technology for Improved Efficiency

In addressing its backlog, NIST is also exploring the potential use of artificial intelligence (AI) and machine learning to streamline the processing of vulnerability data. This move reflects an ongoing trend in the cybersecurity industry toward leveraging advanced technologies for more efficient management of vulnerabilities. By incorporating AI and machine learning, NIST aims to ensure that both older and newer vulnerabilities receive appropriate attention within the constraints of available resources. This nuanced approach to cybersecurity management underscores the need for a balance between addressing legacy vulnerabilities and staying ahead of emerging threats. Organizations are encouraged to adopt similar strategies, using technology to enhance their cybersecurity efforts and ensure comprehensive coverage of potential vulnerabilities. This shift in focus not only addresses immediate backlog issues but also sets the stage for more sustainable and scalable vulnerability management practices in the future.

New Paradigm for Cybersecurity Management

The US National Institute of Standards and Technology (NIST) has recently made a crucial decision that impacts the cybersecurity domain by designating all Common Vulnerabilities and Exposures (CVEs) published before January 1, 2018, as “Deferred” in the National Vulnerability Database (NVD). This adjustment affects over 20,000 entries and potentially up to 100,000, indicating that these CVEs will no longer receive prioritized updates for enrichment data unless they are listed in the Cybersecurity and Infrastructure Security Agency’s (CISA) Known Exploited Vulnerabilities (KEV) catalog. NIST’s decision is a response to an ongoing challenge with a growing accumulation of vulnerability data, which has been aggravated by a 32% increase in submissions over the past year. This strategic shift aims to address the backlog more effectively and allocate resources more efficiently, ensuring newer and more critical vulnerabilities receive the attention they require for maintaining robust cybersecurity measures.

Explore more

What Businesses Need to Know About Customer Identity Verification

Modern verification toolkits have expanded beyond simple photo ID inspections to include facial biometrics, liveness detection, and automated identity APIs. This shift occurs at a time when digital interactions represent the primary touchpoint between companies and their clientele. In an era where many customers never physically enter a store or meet a representative, the pressure to establish trust is immense.

Is AI the End of Current Blockchain Cryptography?

Current Ethereum and Bitcoin addresses that have broadcast a transaction are more vulnerable because their public keys are already visible on the ledger. This revelation has sent ripples through the cryptographic community, challenging the long-held assumption that decentralized networks would have decades to prepare for the advent of quantum-scale attacks. Instead of waiting for a physically realized quantum computer, researchers

How Is Google Cloud Redefining Legacy IT With AI?

The ability to generate business cases for cloud migration in minutes is replacing the manual spreadsheet modeling that previously slowed down IT departments. This shift marks a fundamental change in how large-scale infrastructure overhauls are perceived by the executive suite, moving away from purely technical discussions to strategic business narratives. In the current landscape of 2026, the rapid adoption of

Top Data Classification Tools and Strategies for 2026

Relying solely on automated machine learning without providing clear policy guidance often results in over-classification, making the entire security system difficult for employees to use. In the current digital landscape of 2026, data classification has transcended its origins as a back-office administrative chore to become a critical pillar of modern cybersecurity and global regulatory compliance. As enterprises manage vast petabytes

Google Updates View-Through Conversion Logic for Demand Gen

The quest for absolute clarity in digital attribution has long been the holy grail for modern marketers seeking to justify their visual media spend across expansive digital ecosystems. The change to a one-pixel threshold moves view-through metrics further away from proving active engagement and closer to measuring mere exposure. This technical adjustment, arriving as part of a broader overhaul of