Path to dependency file: /samples/core/ai_platform/training
Path to vulnerable library: /samples/core/ai_platform/training,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/components/arena/python,/contrib/components/openvino/predict/containers/requirements.txt,/components/aws/sagemaker/requirements.txt,/test/sample-test/requirements.txt,/sdk/python,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/samples/core/ai_platform/training,/backend/requirements.txt,/components/kubeflow/dnntrainer/src,/samples/core/ai_platform/training/requirements.txt,/backend/src/apiserver/visualization/requirements.txt,/contrib/components/openvino/ovms-deployer/containers/requirements.txt
Path to dependency file: /samples/core/ai_platform/training
Path to vulnerable library: /samples/core/ai_platform/training,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/components/arena/python,/contrib/components/openvino/predict/containers/requirements.txt,/components/aws/sagemaker/requirements.txt,/test/sample-test/requirements.txt,/sdk/python,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/samples/core/ai_platform/training,/backend/requirements.txt,/components/kubeflow/dnntrainer/src,/samples/core/ai_platform/training/requirements.txt,/backend/src/apiserver/visualization/requirements.txt,/contrib/components/openvino/ovms-deployer/containers/requirements.txt
Buffer overflow in the array_from_pyobj function of fortranobject.c in NumPy < 1.19, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally)
Mend Note: After conducting further research, Mend has determined that numpy versions before 1.22.0 are vulnerable to CVE-2021-41496
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: Low
- Privileges Required: Low
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)
CVE-2021-34141
### Vulnerable Library - numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl
Path to dependency file: /samples/core/ai_platform/training
Path to vulnerable library: /samples/core/ai_platform/training,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/components/arena/python,/contrib/components/openvino/predict/containers/requirements.txt,/components/aws/sagemaker/requirements.txt,/test/sample-test/requirements.txt,/sdk/python,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/samples/core/ai_platform/training,/backend/requirements.txt,/components/kubeflow/dnntrainer/src,/samples/core/ai_platform/training/requirements.txt,/backend/src/apiserver/visualization/requirements.txt,/contrib/components/openvino/ovms-deployer/containers/requirements.txt
An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless."
Mend Note: After conducting further research, Mend has determined that versions 1.12.0 through 1.21.6 of numpy are vulnerable to CVE-2021-34141
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)
CVE-2021-33430
### Vulnerable Library - numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl
Path to dependency file: /samples/core/ai_platform/training
Path to vulnerable library: /samples/core/ai_platform/training,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/components/arena/python,/contrib/components/openvino/predict/containers/requirements.txt,/components/aws/sagemaker/requirements.txt,/test/sample-test/requirements.txt,/sdk/python,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/samples/core/ai_platform/training,/backend/requirements.txt,/components/kubeflow/dnntrainer/src,/samples/core/ai_platform/training/requirements.txt,/backend/src/apiserver/visualization/requirements.txt,/contrib/components/openvino/ovms-deployer/containers/requirements.txt
A Buffer Overflow vulnerability exists in NumPy 1.9.x in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulneraility; In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user
Mend Note: After conducting further research, Mend has determined that numpy versions before 1.21.0 are vulnerable to CVE-2021-33430
Vulnerable Library - numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl
Fundamental package for array computing in Python
Library home page: https://files.pythonhosted.org/packages/3a/5f/47e578b3ae79e2624e205445ab77a1848acdaa2929a00eeef6b16eaaeb20/numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl
Path to dependency file: /samples/core/ai_platform/training
Path to vulnerable library: /samples/core/ai_platform/training,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/components/arena/python,/contrib/components/openvino/predict/containers/requirements.txt,/components/aws/sagemaker/requirements.txt,/test/sample-test/requirements.txt,/sdk/python,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/samples/core/ai_platform/training,/backend/requirements.txt,/components/kubeflow/dnntrainer/src,/samples/core/ai_platform/training/requirements.txt,/backend/src/apiserver/visualization/requirements.txt,/contrib/components/openvino/ovms-deployer/containers/requirements.txt
Vulnerabilities
**In some cases, Remediation PR cannot be created automatically for a vulnerability despite the availability of remediation
Details
CVE-2021-41496
### Vulnerable Library - numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whlFundamental package for array computing in Python
Library home page: https://files.pythonhosted.org/packages/3a/5f/47e578b3ae79e2624e205445ab77a1848acdaa2929a00eeef6b16eaaeb20/numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl
Path to dependency file: /samples/core/ai_platform/training
Path to vulnerable library: /samples/core/ai_platform/training,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/components/arena/python,/contrib/components/openvino/predict/containers/requirements.txt,/components/aws/sagemaker/requirements.txt,/test/sample-test/requirements.txt,/sdk/python,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/samples/core/ai_platform/training,/backend/requirements.txt,/components/kubeflow/dnntrainer/src,/samples/core/ai_platform/training/requirements.txt,/backend/src/apiserver/visualization/requirements.txt,/contrib/components/openvino/ovms-deployer/containers/requirements.txt
Dependency Hierarchy: - :x: **numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl** (Vulnerable Library)
Found in base branch: master
### Vulnerability DetailsBuffer overflow in the array_from_pyobj function of fortranobject.c in NumPy < 1.19, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally) Mend Note: After conducting further research, Mend has determined that numpy versions before 1.22.0 are vulnerable to CVE-2021-41496
Publish Date: 2021-12-17
URL: CVE-2021-41496
### CVSS 3 Score Details (5.5)Base Score Metrics: - Exploitability Metrics: - Attack Vector: Local - Attack Complexity: Low - Privileges Required: Low - User Interaction: None - Scope: Unchanged - Impact Metrics: - Confidentiality Impact: None - Integrity Impact: None - Availability Impact: High
For more information on CVSS3 Scores, click here. Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)CVE-2021-34141
### Vulnerable Library - numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whlFundamental package for array computing in Python
Library home page: https://files.pythonhosted.org/packages/3a/5f/47e578b3ae79e2624e205445ab77a1848acdaa2929a00eeef6b16eaaeb20/numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl
Path to dependency file: /samples/core/ai_platform/training
Path to vulnerable library: /samples/core/ai_platform/training,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/components/arena/python,/contrib/components/openvino/predict/containers/requirements.txt,/components/aws/sagemaker/requirements.txt,/test/sample-test/requirements.txt,/sdk/python,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/samples/core/ai_platform/training,/backend/requirements.txt,/components/kubeflow/dnntrainer/src,/samples/core/ai_platform/training/requirements.txt,/backend/src/apiserver/visualization/requirements.txt,/contrib/components/openvino/ovms-deployer/containers/requirements.txt
Dependency Hierarchy: - :x: **numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl** (Vulnerable Library)
Found in base branch: master
### Vulnerability DetailsAn incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." Mend Note: After conducting further research, Mend has determined that versions 1.12.0 through 1.21.6 of numpy are vulnerable to CVE-2021-34141
Publish Date: 2021-12-17
URL: CVE-2021-34141
### CVSS 3 Score Details (5.3)Base Score Metrics: - Exploitability Metrics: - Attack Vector: Network - Attack Complexity: Low - Privileges Required: None - User Interaction: None - Scope: Unchanged - Impact Metrics: - Confidentiality Impact: None - Integrity Impact: None - Availability Impact: Low
For more information on CVSS3 Scores, click here. ### Suggested FixType: Upgrade version
Origin: https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-34141
Release Date: 2021-12-17
Fix Resolution: 1.22.0
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)CVE-2021-33430
### Vulnerable Library - numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whlFundamental package for array computing in Python
Library home page: https://files.pythonhosted.org/packages/3a/5f/47e578b3ae79e2624e205445ab77a1848acdaa2929a00eeef6b16eaaeb20/numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl
Path to dependency file: /samples/core/ai_platform/training
Path to vulnerable library: /samples/core/ai_platform/training,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/components/arena/python,/contrib/components/openvino/predict/containers/requirements.txt,/components/aws/sagemaker/requirements.txt,/test/sample-test/requirements.txt,/sdk/python,/samples/contrib/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/requirements.txt,/samples/core/ai_platform/training,/backend/requirements.txt,/components/kubeflow/dnntrainer/src,/samples/core/ai_platform/training/requirements.txt,/backend/src/apiserver/visualization/requirements.txt,/contrib/components/openvino/ovms-deployer/containers/requirements.txt
Dependency Hierarchy: - :x: **numpy-1.16.6-cp27-cp27mu-manylinux1_x86_64.whl** (Vulnerable Library)
Found in base branch: master
### Vulnerability DetailsA Buffer Overflow vulnerability exists in NumPy 1.9.x in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulneraility; In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user Mend Note: After conducting further research, Mend has determined that numpy versions before 1.21.0 are vulnerable to CVE-2021-33430
Publish Date: 2021-12-17
URL: CVE-2021-33430
### CVSS 3 Score Details (5.3)Base Score Metrics: - Exploitability Metrics: - Attack Vector: Network - Attack Complexity: High - Privileges Required: Low - User Interaction: None - Scope: Unchanged - Impact Metrics: - Confidentiality Impact: None - Integrity Impact: None - Availability Impact: High
For more information on CVSS3 Scores, click here. ### Suggested FixType: Upgrade version
Origin: https://nvd.nist.gov/vuln/detail/CVE-2021-33430
Release Date: 2021-12-17
Fix Resolution: 1.21.0
Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)