BlackTreeCVE Intelligencemlflow · mlflow/mlflow
Critical technical impact with a remotely reachable, unauthenticated path and a public exploit reference; no CISA KEV confirmation is currently recorded. Verified remediation exists for at least one product or source, but 1 structured product or package state remain unresolved. Apply remediation only to the exact product branch confirmed by its source.
Verified remediation exists for at least one product or source, but 1 structured product or package state remain unresolved. Apply remediation only to the exact product branch confirmed by its source.
These OSV and GitHub advisory ranges apply only to the named package and ecosystem. A listed fixed version is not a universal product patch or proof that an update is installed.
| Ecosystem and package | Affected range | First fixed version | Evidence |
|---|---|---|---|
| PyPImlflow | ECOSYSTEM: introduced 0; fixed 3.8.1 | 3.8.1 | OSV record ↗aggregator derived · 10 Sep 2026 |
| pipmlflow | < 3.8.1 | 3.8.1 | GitHub advisory ↗github reviewed aggregator · 1 Apr 2026 |
Structured product status and remediation from the issuing vendor. Product-state explanations are always visible; large lists can be searched or downloaded.
The vendor explicitly identifies these products as affected by this CVE.
Critical technical impact with a remotely reachable, unauthenticated path and a public exploit reference; no CISA KEV confirmation is currently recorded. Verified remediation exists for at least one product or source, but 1 structured product or package state remain unresolved. Apply remediation only to the exact product branch confirmed by its source.
Fix availability varies by productA command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact's `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.
A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact's `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.
Untrusted input reaches a command interpreter without sufficient validation or separation from command syntax.
An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact's `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.
Untrusted input reaches a command interpreter without sufficient validation or separation from command syntax.
An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.
No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.
A structured CVE source labels at least one public reference as exploit material. BlackTree has not independently validated that it is safe, reliable or weaponised.
CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection'). The product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended command when it is sent to a downstream component.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:HCommon Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.
Operational remediation based on structured source evidence.
Published 30 Mar 2026 · Last source change 7 Sept 2026, 12:05 UTC · CWE-77 · Improper Neutralization of Special Elements used in a Command ('Command Injection')
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