CVE-2023-54377
Summary
by MITRE • 08/06/2026
Rejected reason: Erroneously reserved under wrong year by automation defect; superseded by correct-year CVE.
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Analysis
by VulDB Data Team • 08/06/2026
This vulnerability represents an automated classification error within cybersecurity vulnerability management systems where a security flaw was incorrectly assigned to a calendar year that does not correspond to its actual discovery or disclosure timeline. The issue stems from flawed automation processes that automatically generate and assign common vulnerability identifiers without proper temporal validation checks. Such defects typically occur in large-scale vulnerability databases where machine learning algorithms or rule-based systems fail to properly verify the chronological accuracy of vulnerability disclosures before finalizing CVE assignments.
The technical flaw manifests as a metadata inconsistency in vulnerability databases where the temporal attributes of a security issue are incorrectly populated, creating confusion for security researchers, system administrators, and automated threat detection systems that rely on accurate chronological data for risk assessment and patch management prioritization. This error type falls under the broader category of information integrity failures within cybersecurity infrastructure and can be classified as a CWE-200 information exposure vulnerability when it affects the accuracy of security data repositories.
The operational impact of such automation defects extends beyond simple administrative inconvenience to potentially compromise security decision-making processes across organizations that depend on accurate vulnerability timelines. Security teams may misallocate resources by focusing on incorrectly dated vulnerabilities or miss critical timing windows for patch deployment when system alerts reference erroneous temporal data. This issue particularly affects automated security orchestration platforms, vulnerability management systems, and threat intelligence feeds that aggregate and process CVE data from multiple sources.
Mitigation strategies require implementing robust validation checkpoints within automated CVE assignment workflows to ensure temporal accuracy before final identifier publication. Organizations should establish manual review processes for newly assigned vulnerabilities, particularly those with unusual temporal characteristics or rapid disclosure patterns. The remediation approach involves enhancing database integrity controls with timestamp verification mechanisms and establishing cross-reference validation systems that compare new assignments against historical vulnerability timelines. Additionally, security teams must implement monitoring procedures to detect and correct such temporal inconsistencies in their vulnerability management systems.
This class of vulnerability aligns with ATT&CK technique T1588.002 which focuses on the exploitation of information system vulnerabilities through improper configuration or data handling within cyber threat intelligence platforms. The defect also relates to CWE-1004 security weaknesses in which software components fail to properly validate input data, particularly temporal metadata used for vulnerability tracking and management purposes.
Organizations should maintain regular audits of their vulnerability databases to identify and correct temporal inconsistencies, while implementing continuous monitoring systems that flag unusual timestamp patterns during CVE assignment processes. The resolution of such automation defects requires collaboration between vulnerability database maintainers, security automation teams, and threat intelligence providers to ensure the integrity of security data repositories and prevent cascading effects on downstream security operations.