sklearn-0.0.tar.gz: 2 vulnerabilities (highest severity is: 5.3) - autoclosed

[mend-bolt-for-github[bot]]

Vulnerable Library - sklearn-0.0.tar.gz

Path to dependency file: /pi_nexus/components/requirements.txt

Path to vulnerable library: /pi_nexus/components/requirements.txt,/blockchain_integration/pi_network/pi_network_university/ai_course_recommendations/requirements.txt

Found in HEAD commit: 011e5f9d5ce310049a1a68c19f7df65be4f88caf

Vulnerabilities

CVE	Severity	CVSS	Dependency	Type	Fixed in (sklearn version)	Remediation Possible**
CVE-2021-34141	Medium	5.3	numpy-1.19.5-cp37-cp37m-manylinux2010_x86_64.whl	Transitive	0.0.post1	❌
CVE-2021-33430	Medium	5.3	numpy-1.19.5-cp37-cp37m-manylinux2010_x86_64.whl	Transitive	0.0.post1	❌

**In some cases, Remediation PR cannot be created automatically for a vulnerability despite the availability of remediation

Details

CVE-2021-34141

### Vulnerable Library - numpy-1.19.5-cp37-cp37m-manylinux2010_x86_64.whl

Fundamental package for array computing in Python

Library home page: https://files.pythonhosted.org/packages/08/d6/a6aaa29fea945bc6c61d11f6e0697b325ff7446de5ffd62c2fa02f627048/numpy-1.19.5-cp37-cp37m-manylinux2010_x86_64.whl

Path to dependency file: /pi_nexus/components/requirements.txt

Path to vulnerable library: /pi_nexus/components/requirements.txt,/blockchain_integration/pi_network/pi_network_university/ai_course_recommendations/requirements.txt

Dependency Hierarchy: - sklearn-0.0.tar.gz (Root Library) - scikit_learn-1.0.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl - :x: **numpy-1.19.5-cp37-cp37m-manylinux2010_x86_64.whl** (Vulnerable Library)

Found in HEAD commit: 011e5f9d5ce310049a1a68c19f7df65be4f88caf

Found in base branch: main

### Vulnerability Details

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

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 Fix

Type: Upgrade version

Origin: https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-34141

Release Date: 2021-12-17

Fix Resolution (numpy): 1.22.0

Direct dependency fix Resolution (sklearn): 0.0.post1

Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)

CVE-2021-33430

### Vulnerable Library - numpy-1.19.5-cp37-cp37m-manylinux2010_x86_64.whl

Fundamental package for array computing in Python

Library home page: https://files.pythonhosted.org/packages/08/d6/a6aaa29fea945bc6c61d11f6e0697b325ff7446de5ffd62c2fa02f627048/numpy-1.19.5-cp37-cp37m-manylinux2010_x86_64.whl

Path to dependency file: /pi_nexus/components/requirements.txt

Path to vulnerable library: /pi_nexus/components/requirements.txt,/blockchain_integration/pi_network/pi_network_university/ai_course_recommendations/requirements.txt

Dependency Hierarchy: - sklearn-0.0.tar.gz (Root Library) - scikit_learn-1.0.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl - :x: **numpy-1.19.5-cp37-cp37m-manylinux2010_x86_64.whl** (Vulnerable Library)

Found in HEAD commit: 011e5f9d5ce310049a1a68c19f7df65be4f88caf

Found in base branch: main

### Vulnerability Details

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

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 Fix

Type: Upgrade version

Origin: https://nvd.nist.gov/vuln/detail/CVE-2021-33430

Release Date: 2021-12-17

Fix Resolution (numpy): 1.21.0

Direct dependency fix Resolution (sklearn): 0.0.post1

Step up your Open Source Security Game with Mend [here](https://www.whitesourcesoftware.com/full_solution_bolt_github)

[github-actions[bot]]

Stale issue message

[mend-bolt-for-github[bot]]

:heavy_check_mark: This issue was automatically closed by Mend because the vulnerable library in the specific branch(es) was either marked as ignored or it is no longer part of the Mend inventory.