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Quarantine

Scanned:

joule-sbx-poc

Artifact:

latest

SAP Joule utilities

License: unknown

New!

Published:

See on PyPI

SAFE Assessment

Compliance

Licenses

No license compliance issues

Secrets

No sensitive information found

Security

Vulnerabilities

No known vulnerabilities detected

Hardening

No application hardening issues

Threats

Tampering

1 dangerous install procedures

Malware

No evidence of malware inclusion

Overview issues7 vulnerabilities0 malware0 behaviors21 dependencies0 contributors1 versions1

Popularity

N/A

Total Downloads

Contributor

Declared Dependencies

Dependents

Top issues

See all issues

Problem

Most software applications use standardized installation formats for their distribution. Software installers are built from instructions written within installation scripts that act as blueprints for the distribution format assembly. Installation scripts declare the most important software properties, such as the default installation location, its external dependencies, and various actions that may occur during the installation process. Actions defined within the installation script are executed automatically during events such as software deployment, update, or removal. These events are used by software developers to set up the environment for nominal software use, or to perform cleanup upon software removal. It is unusual for certain types of software installers to execute commands that can collect sensitive system information. Attackers often abuse software installers to run commands that collect identifiable system information such as hostnames, user names, folder structures, and other data points that could help them understand the environment in which their malicious code was installed.

Prevalence in PyPI community

0 packages

found in

Top 100

1 packages

found in

Top 1k

3 packages

found in

Top 10k

706 packages

in community

Next steps

Investigate reported detections.

If the software intent does not relate to the reported behavior, investigate your build and release environment for software supply chain compromise.

You should delay the software release until the investigation is completed, or until the issue is risk accepted.

Consider rewriting the installation procedure without using the marked behaviors.

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. The ReversingLabs community package index may place software packages into quarantine during an ongoing security incident investigation. When a software project is placed into quarantine, it is typically unavailable for installation. Additionally, repository maintainers may also hide quarantined software projects from users that might stumble upon them using repository search functions. Quarantine is typically raised for software projects that were reported for unusual code changes or unexpected software behaviors.

Prevalence in PyPI community

No prevalence information at this time

Next steps

Inspect behaviors exhibited by the detected software components.

If the software behaviors differ from expected, investigate the build and release environment for software supply chain compromise.

Revise the use of components that raise these alarms. If you can't deprecate those components, make sure they are well-documented.

Avoid using this software package until it is vetted as safe.

Problem

Software components contain executable code that performs actions implemented during its development. These actions are called behaviors. In the analysis report, behaviors are presented as human-readable descriptions that best match the underlying code intent. Python Package Index (PyPI) repository is often abused by threat actors to publish software packages that exhibit malicious behaviors. Malware authors use numerous tactics to lure developers into including malicious PyPI packages in their software projects. Most malicious packages published on PyPI target developers and their workstations. However, some are designed to activate only when deployed in the end-user environment. Both types of Python malicious packages are detected by proprietary ReversingLabs threat hunting algorithms. This detection method is considered proactive, and it is based on Machine Learning (ML) algorithms that can detect novel malware. The detection is strongly influenced by behaviors that software components exhibit. Behaviors similar to previously discovered malware and software supply chain attacks may cause some otherwise benign software packages to be detected by this policy.

Prevalence in PyPI community

1 packages

found in

Top 100

18 packages

found in

Top 1k

104 packages

found in

Top 10k

16.5k packages

in community

Next steps

Investigate reported detections.

If the software intent does not relate to the reported behavior, investigate your build and release environment for software supply chain compromise.

You should delay the software release until the investigation is completed, or until the issue is risk accepted.

Consider rewriting the flagged code without using the marked behaviors.

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 being the first to try out a new project 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

0 packages

found in

Top 100

0 packages

found in

Top 1k

5 packages

found in

Top 10k

38.63k packages

in community

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. 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

1 packages

found in

Top 100

11 packages

found in

Top 1k

910 packages

found in

Top 10k

717.09k packages

in community

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 uncommon for this community (Uncommon)

0 packages

found in

Top 100

1 packages

found in

Top 1k

3 packages

found in

Top 10k

693 packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

69 packages

found in

Top 100

506 packages

found in

Top 1k

3612 packages

found in

Top 10k

163.85k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

35 packages

found in

Top 100

271 packages

found in

Top 1k

1741 packages

found in

Top 10k

61.42k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

67 packages

found in

Top 100

525 packages

found in

Top 1k

4055 packages

found in

Top 10k

154.83k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

34 packages

found in

Top 100

181 packages

found in

Top 1k

1324 packages

found in

Top 10k

54.83k packages

in community

Top vulnerabilities

No vulnerabilities found.

FAQ for joule-sbx-poc

What is joule-sbx-poc?

SAP Joule utilities.

Is joule-sbx-poc malicious or is it safe to use?

The Python package joule-sbx-poc was scanned for malware, software tampering, risky behaviors, exposed secrets and known vulnerabilities. Malware or tampering has been detected, making it unsafe to download and use. 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 joule-sbx-poc popular?

The Python package joule-sbx-poc is not widely used. 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 joule-sbx-poc once it is in my app?

Since we can't know when or where malicious attacks will happen, we recommend tracking how joule-sbx-poc behaviors change over multiple software releases. By adopting differential analysis in your release process, you can detect unexpected changes to a joule-sbx-poc 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.

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Popularity

N/A

Total Downloads

Contributor

Declared Dependencies

Dependents

Top issues

See all issues

Problem

Prevalence in PyPI community

0 packages

found in

Top 100

1 packages

found in

Top 1k

3 packages

found in

Top 10k

706 packages

in community

Next steps

Investigate reported detections.

If the software intent does not relate to the reported behavior, investigate your build and release environment for software supply chain compromise.

You should delay the software release until the investigation is completed, or until the issue is risk accepted.

Consider rewriting the installation procedure without using the marked behaviors.

Problem

Prevalence in PyPI community

No prevalence information at this time

Next steps

Inspect behaviors exhibited by the detected software components.

If the software behaviors differ from expected, investigate the build and release environment for software supply chain compromise.

Revise the use of components that raise these alarms. If you can't deprecate those components, make sure they are well-documented.

Avoid using this software package until it is vetted as safe.

Problem

Prevalence in PyPI community

1 packages

found in

Top 100

18 packages

found in

Top 1k

104 packages

found in

Top 10k

16.5k packages

in community

Next steps

Investigate reported detections.

If the software intent does not relate to the reported behavior, investigate your build and release environment for software supply chain compromise.

You should delay the software release until the investigation is completed, or until the issue is risk accepted.

Consider rewriting the flagged code without using the marked behaviors.

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 being the first to try out a new project 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

0 packages

found in

Top 100

0 packages

found in

Top 1k

5 packages

found in

Top 10k

38.63k packages

in community

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. 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

1 packages

found in

Top 100

11 packages

found in

Top 1k

910 packages

found in

Top 10k

717.09k packages

in community

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 uncommon for this community (Uncommon)

0 packages

found in

Top 100

1 packages

found in

Top 1k

3 packages

found in

Top 10k

693 packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

69 packages

found in

Top 100

506 packages

found in

Top 1k

3612 packages

found in

Top 10k

163.85k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

35 packages

found in

Top 100

271 packages

found in

Top 1k

1741 packages

found in

Top 10k

61.42k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

67 packages

found in

Top 100

525 packages

found in

Top 1k

4055 packages

found in

Top 10k

154.83k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

34 packages

found in

Top 100

181 packages

found in

Top 1k

1324 packages

found in

Top 10k

54.83k packages

in community

Top vulnerabilities

No vulnerabilities found.

joule-sbx-poc

SAFE Assessment

Compliance

Security

Threats

Popularity

Top issues

TH16604Detected presence of software installers that can collect sensitive system information.Causes risk: dangerous install procedureshunting

Problem

Prevalence in PyPI community

Next steps

TH30102Detected presence of software components that are quarantined in the community package index.Causes risk: quarantined components foundhunting

Problem

Prevalence in PyPI community

Next steps

TH15501Detected presence of files with behaviors similar to malicious packages published on PyPI.Causes risk: suspicious application behaviorshunting

Problem

Prevalence in PyPI community

Next steps

TH30105Detected presence of software components that were recently published to the public package repository.hunting

Problem

Prevalence in PyPI community

Next steps

TH30107Detected presence of software components that are rarely included by other public software packages.hunting

Problem

Prevalence in PyPI community

Next steps

Top behaviors

Queries the host name of the computer during the package installation process.search

Prevalence in PyPI community

Creates a process.execution

Prevalence in PyPI community

Contains URLs that use non-standard ports.network

Prevalence in PyPI community

Contains IP addresses.network

Prevalence in PyPI community

Executes a file.execution

Prevalence in PyPI community

Top vulnerabilities

FAQ for joule-sbx-poc

What is joule-sbx-poc?

Is joule-sbx-poc malicious or is it safe to use?

Is joule-sbx-poc popular?

How do I secure joule-sbx-poc once it is in my app?

Did you know...

Popularity

Top issues

TH16604Detected presence of software installers that can collect sensitive system information.Causes risk: dangerous install procedureshunting

Problem

Prevalence in PyPI community

Next steps

TH30102Detected presence of software components that are quarantined in the community package index.Causes risk: quarantined components foundhunting

Problem

Prevalence in PyPI community

Next steps

TH15501Detected presence of files with behaviors similar to malicious packages published on PyPI.Causes risk: suspicious application behaviorshunting

Problem

Prevalence in PyPI community

Next steps

TH30105Detected presence of software components that were recently published to the public package repository.hunting

Problem

Prevalence in PyPI community

Next steps

TH30107Detected presence of software components that are rarely included by other public software packages.hunting

Problem

Prevalence in PyPI community

Next steps

Top behaviors

Queries the host name of the computer during the package installation process.search

Prevalence in PyPI community

Creates a process.execution

Prevalence in PyPI community

Contains URLs that use non-standard ports.network

Prevalence in PyPI community

Contains IP addresses.network

Prevalence in PyPI community

Executes a file.execution

Prevalence in PyPI community

Top vulnerabilities