dabeaz CVE Vulnerabilities & Metrics

Focus on dabeaz vulnerabilities and metrics.

Last updated: 15 Feb 2026, 23:25 UTC

About dabeaz Security Exposure

This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with dabeaz. We track both calendar-based metrics (using fixed periods) and rolling metrics (using gliding windows) to give you a comprehensive view of security trends and risk evolution. Use these insights to assess risk and plan your patching strategy.

For a broader perspective on cybersecurity threats, explore the comprehensive list of CVEs by vendor and product. Stay updated on critical vulnerabilities affecting major software and hardware providers.

Global CVE Overview

Total dabeaz CVEs: 1
Earliest CVE date: 20 Jan 2026, 19:15 UTC
Latest CVE date: 20 Jan 2026, 19:15 UTC

Latest CVE reference: CVE-2025-56005

Rolling Stats

30-day Count (Rolling): 1
365-day Count (Rolling): 1

Calendar-based Variation

Calendar-based Variation compares a fixed calendar period (e.g., this month versus the same month last year), while Rolling Growth Rate uses a continuous window (e.g., last 30 days versus the previous 30 days) to capture trends independent of calendar boundaries.

Variations & Growth

Month Variation (Calendar): 0%
Year Variation (Calendar): 0%

Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): 0.0%

Monthly CVE Trends (current vs previous Year)

Annual CVE Trends (Last 20 Years)

Critical dabeaz CVEs (CVSS ≥ 9) Over 20 Years

CVSS Stats

Average CVSS: 0.0

Max CVSS: 0

Critical CVEs (≥9): 0

CVSS Range vs. Count

Range Count
0.0-3.9 1
4.0-6.9 0
7.0-8.9 0
9.0-10.0 0

CVSS Distribution Chart

Top 5 Highest CVSS dabeaz CVEs

These are the five CVEs with the highest CVSS scores for dabeaz, sorted by severity first and recency.

All CVEs for dabeaz

CVE-2025-56005 dabeaz vulnerability CVSS: 0 20 Jan 2026, 19:15 UTC

An undocumented and unsafe feature in the PLY (Python Lex-Yacc) library 3.11 allows Remote Code Execution (RCE) via the `picklefile` parameter in the `yacc()` function. This parameter accepts a `.pkl` file that is deserialized with `pickle.load()` without validation. Because `pickle` allows execution of embedded code via `__reduce__()`, an attacker can achieve code execution by passing a malicious pickle file. The parameter is not mentioned in official documentation or the GitHub repository, yet it is active in the PyPI version. This introduces a stealthy backdoor and persistence risk. NOTE: A third-party states that this vulnerability should be rejected because the proof of concept does not demonstrate arbitrary code execution and fails to complete successfully.