Undefined Behavior in mlflow

A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service DoS as an authenticated user might not be able to use the intended model, as it will open a different model each time...

PYSEC-2026-1645 Undefined Behavior in mlflow

A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service DoS as an authenticated user might not be able to use the intended model, as it will open a different model each time...

MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.9.0 or newer, enabling a maliciously uploaded PyFunc model to run arbitrary code on an end user’s system when interacted with...

MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.23.0 or newer, enabling a maliciously uploaded LightGBM scikit-learn model to run arbitrary code on an end user’s system when interacted with...

MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.24.0 or newer, enabling a maliciously uploaded pmdarima model to run arbitrary code on an end user’s system when interacted with...

MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with...

MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.5.0 or newer, enabling a maliciously uploaded Langchain AgentExecutor model to run arbitrary code on an end user’s system when interacted with...

PYSEC-2026-1644 MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.23.0 or newer, enabling a maliciously uploaded LightGBM scikit-learn model to run arbitrary code on an end user’s system when interacted with...

PYSEC-2026-1651 MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.9.0 or newer, enabling a maliciously uploaded PyFunc model to run arbitrary code on an end user’s system when interacted with...

PYSEC-2026-1643 MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with...

Wagtail has permission check bypass when editing a model with per-field restrictions through `wagtail.contrib.settings` or `ModelViewSet`

ImpactIf a model has been made available for editing through the wagtail.contrib.settings module or ModelViewSet, and the permission argument on FieldPanel has been used to further restrict access to one or more fields of the model, a user with edit permission over the model but not the specific...

mlflow vulnerable to Path Traversal

A path traversal vulnerability exists in the createmodelversion function within server/handlers.py of the mlflow/mlflow repository, due to improper validation of the source parameter. Attackers can exploit this vulnerability by crafting a source parameter that bypasses the...

PYSEC-2026-1653 mlflow vulnerable to Path Traversal

A path traversal vulnerability exists in the createmodelversion function within server/handlers.py of the mlflow/mlflow repository, due to improper validation of the source parameter. Attackers can exploit this vulnerability by crafting a source parameter that bypasses the...

Microsoft Common Data Model SDK Denial of Service Vulnerability

Microsoft Common Data Model SDK Denial of Service Vulnerability...

PYSEC-2026-1261 Microsoft Common Data Model SDK Denial of Service Vulnerability

Microsoft Common Data Model SDK Denial of Service Vulnerability...

c4v-py (>=0.1.0.dev1, <=0.1.0.dev202107081840), cifar-10-model (7.4.0) +17 more potentially affected by CVE-2023-25661 via tensorflow-cpu (>=2.1.0, <=2.11.0)

tensorflow-cpu PYPI version =2.1.0, =0.1.0.dev1, =0.1.0b1, =0.1.2, =1.0.0, =0.0.4, =1.5.0, =0.1.3, =0.5.1, =0.102.0.dev0, =0.208.0.post1 and more Source cves: CVE-2023-25661 Source advisory: OSV:PYSEC-2026-1952...

arekit (>=0.21.0, <=0.22.1), arenets (>=0.23.0, <=0.23.1) +19 more potentially affected by CVE-2023-25660 via tensorflow-gpu (1.14.0)

tensorflow-gpu PYPI version 1.14.0 is affected by a known vulnerability. The following packages have a transitive dependency on tensorflow-gpu and may be impacted: - arekit =0.21.0, =0.23.0, =1.0.0, =0.0.1, =0.1.6, =0.1.0, =0.0.6, =1.0.1, =1.0.2 - ocrd-anybaseocr 0.0.1 and more Source cves:...

arekit (>=0.21.0, <=0.22.1), arenets (>=0.23.0, <=0.23.1) +19 more potentially affected by CVE-2023-25673 via tensorflow-gpu (1.14.0)

tensorflow-gpu PYPI version 1.14.0 is affected by a known vulnerability. The following packages have a transitive dependency on tensorflow-gpu and may be impacted: - arekit =0.21.0, =0.23.0, =1.0.0, =0.0.1, =0.1.6, =0.1.0, =0.0.6, =1.0.1, =1.0.2 - ocrd-anybaseocr 0.0.1 and more Source cves:...

arekit (>=0.21.0, <=0.22.1), arenets (>=0.23.0, <=0.23.1) +19 more potentially affected by CVE-2022-35963 via tensorflow-gpu (1.14.0)

tensorflow-gpu PYPI version 1.14.0 is affected by a known vulnerability. The following packages have a transitive dependency on tensorflow-gpu and may be impacted: - arekit =0.21.0, =0.23.0, =1.0.0, =0.0.1, =0.1.6, =0.1.0, =0.0.6, =1.0.1, =1.0.2 - ocrd-anybaseocr 0.0.1 and more Source cves:...

PYSEC-2026-965 TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions

Impact When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. python import tensorflow as tf class QuantConv2DTransposedtf.keras.layers.Layer: def buildself, inputshape: self.kernel = self.addweight"kernel", 3, 3,...