stanford CVE Vulnerabilities & Metrics

Focus on stanford vulnerabilities and metrics.

Last updated: 13 Jul 2026, 22:25 UTC

About stanford Security Exposure

This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with stanford. 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 stanford CVEs: 8
Earliest CVE date: 15 Sep 2009, 22:30 UTC
Latest CVE date: 08 Jul 2026, 23:16 UTC

Latest CVE reference: CVE-2026-54499

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 stanford CVEs (CVSS ≥ 9) Over 20 Years

CVSS Stats

Average CVSS: 4.73

Max CVSS: 7.5

Critical CVEs (≥9): 0

CVSS Range vs. Count

Range Count
0.0-3.9 2
4.0-6.9 4
7.0-8.9 3
9.0-10.0 0

CVSS Distribution Chart

Top 5 Highest CVSS stanford CVEs

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

All CVEs for stanford

CVE-2026-54499 stanford vulnerability CVSS: 0 08 Jul 2026, 23:16 UTC

Stanza is a Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages. Prior to 1.12.2, Stanza model loaders such as stanza.models.common.pretrain.Pretrain.load() attempt torch.load(..., weights_only=True) but fall back to torch.load(..., weights_only=False) on attacker-controllable pickle.UnpicklingError, allowing a malicious .pt pretrain or model file to execute arbitrary pickle code when a Stanza NLP pipeline loads it. This issue is fixed in version 1.12.2.

CVE-2023-39020 stanford vulnerability CVSS: 0 28 Jul 2023, 15:15 UTC

stanford-parser v3.9.2 and below was discovered to contain a code injection vulnerability in the component edu.stanford.nlp.io.getBZip2PipedInputStream. This vulnerability is exploited via passing an unchecked argument.

CVE-2021-44550 stanford vulnerability CVSS: 7.5 24 Feb 2022, 15:15 UTC

An Incorrect Access Control vulnerability exists in CoreNLP 4.3.2 via the classifier in NERServlet.java (lines 158 and 159).

CVE-2022-0239 stanford vulnerability CVSS: 7.5 17 Jan 2022, 07:15 UTC

corenlp is vulnerable to Improper Restriction of XML External Entity Reference

CVE-2022-0198 stanford vulnerability CVSS: 5.8 13 Jan 2022, 07:15 UTC

corenlp is vulnerable to Improper Restriction of XML External Entity Reference

CVE-2021-3869 stanford vulnerability CVSS: 5.0 19 Oct 2021, 13:15 UTC

corenlp is vulnerable to Improper Restriction of XML External Entity Reference

CVE-2021-3878 stanford vulnerability CVSS: 7.5 15 Oct 2021, 14:15 UTC

corenlp is vulnerable to Improper Restriction of XML External Entity Reference

CVE-2013-2106 stanford vulnerability CVSS: 5.0 03 Dec 2019, 14:15 UTC

webauth before 4.6.1 has authentication credential disclosure

CVE-2009-2945 stanford vulnerability CVSS: 4.3 15 Sep 2009, 22:30 UTC

weblogin/login.fcgi (aka the WebLogin login script) in Stanford University WebAuth 3.5.5, 3.6.0, and 3.6.1 places passwords in URLs in certain circumstances involving conversion of a POST request to a GET request, which allows context-dependent attackers to discover passwords by reading (1) web-server access logs, (2) web-server Referer logs, or (3) the browser history.