What is the CVSS score of CVE-2026-24123?

CVE-2026-24123 has a CVSS 3.1 base score of 7.4 (High). CVSS vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:N/A:N. EPSS exploitation probability: 0.0%.

Which versions of Python are affected by CVE-2026-24123?

A HIGH severity vulnerability (CVE-2026-24123) affects BentoML, a Python library used for AI model serving infrastructure.. A patch is available.

How to fix or mitigate CVE-2026-24123?

Within 24 hours: Identify all systems and applications using BentoML and assess their criticality and internet exposure. Within 7 days: Apply the available vendor patch to all affected BentoML instances, prioritizing production and customer-facing systems. Within 30 days: Conduct post-patch validation testing and update vulnerability management records to confirm remediation across the entire inventory.

Python CVE-2026-24123

HIGH

Path Traversal (CWE-22)

2026-01-26 security-advisories@github.com

GHSA-6r62-w2q3-48hf

Python Docker Path Traversal AI / ML Bentoml

7.4

CVSS 3.1 · GitHub Advisory

Severity by source

GitHub Advisory PRIMARY

7.4 HIGH

AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:N/A:N

Primary rating from GitHub Advisory · only source for this CVE.

CVSS VectorGitHub Advisory

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:N/A:N

Attack Vector

Network

Attack Complexity

Low

Privileges Required

None

User Interaction

Required

Scope

Changed

Confidentiality

High

Integrity

None

Availability

None

Lifecycle Timeline

Analysis Generated

Mar 12, 2026 - 22:00 vuln.today

Patch released

Feb 03, 2026 - 15:07 nvd

Patch available

CVE Published

Jan 26, 2026 - 23:16 nvd

HIGH 7.4

DescriptionGitHub Advisory

BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to version 1.4.34, BentoML's bentofile.yaml configuration allows path traversal attacks through multiple file path fields (description, docker.setup_script, docker.dockerfile_template, conda.environment_yml). An attacker can craft a malicious bentofile that, when built by a victim, exfiltrates arbitrary files from the filesystem into the bento archive. This enables supply chain attacks where sensitive files (SSH keys, credentials, environment variables) are silently embedded in bentos and exposed when pushed to registries or deployed. Version 1.4.34 contains a patch for the issue.

AnalysisAI

BentoML versions prior to 1.4.34 allow path traversal attacks through improperly validated file path fields in bentofile.yaml configurations, enabling attackers to embed arbitrary files from the victim's system into bento archives during the build process. This vulnerability can be exploited to exfiltrate sensitive data such as credentials, SSH keys, and environment variables into supply chain artifacts that may be pushed to registries or deployed in production environments. A patch is available in version 1.4.34.

Technical ContextAI

Classified as CWE-22 (Path Traversal). Affects Bentoml. BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to version 1.4.34, BentoML's bentofile.yaml configuration allows path traversal attacks through multiple file path fields (description, docker.setup_script, docker.dockerfile_template, conda.environment_yml). An attacker can craft a malicious bentofile that, when built by a victim, exfiltrates arbitrary files from the filesystem into the bento archive. This enables supply ch

RemediationAI

A vendor patch is available — apply it immediately. Validate and sanitize file path inputs. Use allowlists. Restrict network access to the affected service where possible.