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failRisk: Vulnerabilities
Scanned: 4 days ago

azureml-training-tabular

Artifact:
latest
Top 10k
Contains ML models, featurizers and scoring code which can either be used with AutoML or standalone.
License: unknown
Published: 7 months ago
See on PyPI

SAFE Assessment

Compliance

Licenses
No license compliance issues
Secrets
No sensitive information found

Security

Vulnerabilities
1 severe vulnerabilities exploited
Hardening
No application hardening issues

Threats

Tampering
No evidence of software tampering
Malware
No evidence of malware inclusion

Popularity

3.3M
Total Downloads
1
Contributor
24
Declared Dependencies
1
Dependents

Top issues

See all issues

Problem

Software composition analysis has identified a component with one or more known severe vulnerabilities. Available threat intelligence telemetry has confirmed that the reported high or critical severity vulnerabilities are actively being exploited by malicious actors.

Prevalence in PyPI community

38 packages
found in
Top 100
303 packages
found in
Top 1k
2611 packages
found in
Top 10k
103184 packages
in community

Next steps

We strongly advise updating the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.

Problem

Software composition analysis has identified a component with one or more known vulnerabilities. Based on the CVSS scoring, these vulnerabilities have been marked as critical severity.

Prevalence in PyPI community

25 packages
found in
Top 100
212 packages
found in
Top 1k
1951 packages
found in
Top 10k
77976 packages
in community

Next steps

Perform impact analysis for the reported CVEs.
We strongly advise updating the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.

Problem

Software composition analysis has identified a component with one or more known vulnerabilities. Based on the CVSS scoring, these vulnerabilities have been marked as medium severity.

Prevalence in PyPI community

48 packages
found in
Top 100
311 packages
found in
Top 1k
2806 packages
found in
Top 10k
142146 packages
in community

Next steps

Perform impact analysis for the reported CVEs.
Update the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.

Problem

Software developers use programming and design knowledge to build reusable software components. Software components are the basic building blocks for modern applications. Software consumed by an enterprise consists of hundreds, and sometimes even thousands of open source components. Software developers publish components they have authored to public repositories. While a new software project is a welcome addition to the open source community. it is not always prudent to indiscriminately use the latest components when building a commercial application. Irrespective of the software quality, the danger of using components that are rarely used to build applications lies in the fact that the software component may contain novel, currently undetected malicious code. Therefore, it is prudent to review software component behaviors and even try out software component in a sandbox, an environment meant for testing untrusted code.

Prevalence in PyPI community

No prevalence information at this time

Next steps

Check the software component behaviors for anomalies.
Consider exploratory software component testing within a sandbox environment.
Consider replacing the software component with a more widely used alternative.
Avoid using this software package until it is vetted as safe.

Problem

Software developers use programming and design knowledge to build reusable software components. Software components are the basic building blocks for modern applications. Software consumed by an enterprise consists of hundreds, and sometimes even thousands of open source components. Open source communities depend on the work of thousands of software developers that volunteer their time to maintain software components. Software developers build up the reputation of their open source projects by developing in public. Modern source code repositories have many social features that allow software developers to handle bug reports, have discussions with their users, and convey reaching significant project milestones. It is uncommon to find open source projects that omit linking their component to a publicly accessible source code repository.

Prevalence in PyPI community

No prevalence information at this time

Next steps

Check the software component behaviors for anomalies.
Consider exploratory software component testing within a sandbox environment.
Consider replacing the software component with a more widely used alternative.
Avoid using this software package until it is vetted as safe.

Top behaviors

See all behaviors

Prevalence in PyPI community

Behavior often found in this community (Common)
75 packages
found in
Top 100
451 packages
found in
Top 1k
3488 packages
found in
Top 10k
109392 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
68 packages
found in
Top 100
508 packages
found in
Top 1k
3570 packages
found in
Top 10k
165477 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
67 packages
found in
Top 100
520 packages
found in
Top 1k
3993 packages
found in
Top 10k
158349 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
68 packages
found in
Top 100
540 packages
found in
Top 1k
3644 packages
found in
Top 10k
154572 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
70 packages
found in
Top 100
534 packages
found in
Top 1k
3771 packages
found in
Top 10k
146071 packages
in community

Top vulnerabilities

See all vulnerabilities
Vulnerability Exploitation Lifecycle
(2 Active Vulnerabilities)
None
2 (1 Fixable)
CVE-2020-13092c
CVE-2025-50181m
None
None
Exploits Unknown
Exploits Exist
Exploited by Malware
Patching Mandated

FAQ for azureml-training-tabular

What is azureml-training-tabular?

Contains ML models, featurizers and scoring code which can either be used with AutoML or standalone. For more information about this package, visit its homepage.

Is azureml-training-tabular malicious or is it safe to use?

The Python package azureml-training-tabular was scanned for malware, software tampering, risky behaviors, exposed secrets and known vulnerabilities. The package contains risks, and the analysis results should be reviewed before it is downloaded and used. Visit the Issues and Behaviors sections of the analysis for more details.

Is azureml-training-tabular popular?

The Python package azureml-training-tabular ranks among the top 10000 projects in this community. It has 3M recorded downloads. A package's popularity is not a good indicator of its safety, visit the SAFE Assessment section to see the full analysis of package deployment risk categories.

How do I secure azureml-training-tabular once it is in my app?

Since we can't know when or where malicious attacks will happen, we recommend tracking how azureml-training-tabular behaviors change over multiple software releases. By adopting differential analysis in your release process, you can detect unexpected changes to a azureml-training-tabular version, which can prevent advanced software supply chain attacks. Read how our technology can help prevent future attacks similar to SolarWinds and 3CX.

Did you know...

... that you can use ReversingLabs’ Spectra Assure platform to perform regular risk assessments of packages you develop in-house?

We recommend continuous software safeness monitoring through CI/CD integrations and pre-release/deployment checks. In addition to basic package information found on this page our platform offers rich reports for developers and DevSecOps that help them remediate all reported issues.