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and monitoring legacy systems, prioritizing the patching of deferred vulnerabilities, and hardening or segmenting outdated infrastructure.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

How Has the AI Prompt Become a New Economic Infrastructure?

In early 2026, the launch of advertising within conversational interfaces transformed the prompt into a primary unit of commercial inventory similar to search keywords. This fundamental shift marks the transition of the prompt from a simple user query into the backbone of a sophisticated digital economy. Unlike traditional search engines that index static web pages, modern large language models operate

Nasuni Acquires DryvIQ to Enhance Data Governance and AI Readiness

Nasuni is expanding its reach into the data intelligence layer to help enterprises discover and govern content that has not yet been migrated to the cloud. This strategic move addresses a critical bottleneck where IT departments manage petabytes of unstructured data without knowing exactly what resides within those files. For years, the industry focused on simply finding a place to

Anthropic Study Shows AI Outperforms Humans in Alignment Research

During a head-to-head deception benchmark, automated researchers successfully closed eighty-five percent of the safety gap while human experts only managed to close twenty percent. This startling discovery is the center of a new report detailing how artificial intelligence is moving beyond the role of a tool to become an active participant in its own development. By deploying the Claude series

How B2B Branded Content Builds Authority and Trust

Evaluating the success of a content program requires looking beyond traffic metrics to measure brand recognition, share of voice, and account engagement. In the professional landscape of 2026, the sheer volume of digital material has reached a saturation point, making it increasingly difficult for organizations to distinguish themselves through conventional advertising. This shift in behavior necessitates a transition from traditional

Ethereum Plans EIP-8394 to Secure Staking Against Quantum Threats

The Ethereum Foundation’s strategic roadmap aims for comprehensive network-wide quantum resistance by 2029 to stay ahead of advancements in quantum hardware capabilities. This proactive stance is essential because the cryptographic foundations that currently secure billions in digital assets face an existential threat from the eventual arrival of powerful quantum computers capable of executing Shor’s Algorithm. While traditional supercomputers would require