Spectra Assure

failIncident: Malware

Scanned:

somepentest-test-package

Artifact:

latest

removed

malicious

Research

DO NOT INSTALL

License: Permissive (MIT)

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

2 suspicious application behaviors

Malware

1 supply chain attack artifacts

INCIDENTS FOR THIS VERSION:

malware

Reported By: Community (kam193)

More info

malware

Reported By: Community (OpenSSF)

More info

removal

Reported By: Community

malware

Reported By: ReversingLabs (Researcher)

Learn more about malware detection

malware

Reported By: ReversingLabs (Automated)

Learn more about malware detection

Popularity

145

Total Downloads

Contributors

Declared Dependencies

Dependents

Top issues

See all issues

Problem

Potentially unwanted applications (PUAs) can be considered a risk by some software users. This threat type typically collects private user data, or in more extreme cases, tampers with system security settings. Most threat prevention solutions detect and block PUAs. Software packages that trigger security solution detections also tend to increase the number of support calls and open tickets from users.

Prevalence in PyPI community

0 packages

found in

Top 100

3 packages

found in

Top 1k

54 packages

found in

Top 10k

1.75k packages

in community

Next steps

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

Problem

Proprietary ReversingLabs malware detection algorithms have determined that the software package contains one or more malicious components. The detection was made by either a static byte signature, software component identity, or a complete file hash. This malware detection method is considered highly accurate, and can typically attribute malware to previously discovered software supply chain attacks. It is common to have multiple supply chain attack artifacts that relate to a single malware incident.

Prevalence in PyPI community

0 packages

found in

Top 100

0 packages

found in

Top 1k

11 packages

found in

Top 10k

14.01k packages

in community

Next steps

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

Avoid using this software package.

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. Open source projects are the intellectual property of their respective authors. At any time, the authors may choose to completely remove the software component from a public repository. This often occurs when a software project reaches its end-of-life stage, or when the software authors lose interest in maintaining the project. This kind of removal frees up the software package name, its unique software identifier in the public repository, for other developers to use. However, new software project owners might have malicious intent. Threat actors are continuously monitoring popular package names in case their unique identifiers suddenly become available for hijacking. Once the software projects falls under new ownership, the new maintainers may opt to use the project popularity to spread malware to unsuspecting users.

Prevalence in PyPI community

0 packages

found in

Top 100

1 packages

found in

Top 1k

20 packages

found in

Top 10k

83.87k packages

in community

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 that their versions are pinned.

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 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.

Top behaviors

See all behaviors

Prevalence in PyPI community

Behavior often found in this community (Common)

36 packages

found in

Top 100

281 packages

found in

Top 1k

1802 packages

found in

Top 10k

66.4k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

44 packages

found in

Top 100

286 packages

found in

Top 1k

1787 packages

found in

Top 10k

48.75k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

31 packages

found in

Top 100

291 packages

found in

Top 1k

2158 packages

found in

Top 10k

142.17k packages

in community

Prevalence in PyPI community

Behavior commonly used by malicious software (Important)

Behavior uncommon for this community (Uncommon)

0 packages

found in

Top 100

2 packages

found in

Top 1k

3 packages

found in

Top 10k

673 packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

70 packages

found in

Top 100

472 packages

found in

Top 1k

4207 packages

found in

Top 10k

413.79k packages

in community

Top vulnerabilities

No vulnerabilities found.

FAQ for somepentest-test-package

What is somepentest-test-package?

DO NOT INSTALL.

Is somepentest-test-package malicious or is it safe to use?

The Python package somepentest-test-package has been removed from registry. It was scanned for malware, software tampering, risky behaviors, exposed secrets and known vulnerabilities. Malware or tampering has been detected, making it unsafe to use. 2 other issues and risky behaviors were found. The package contains risks, and the analysis results should be reviewed before it is used. Visit the Issues and Behaviors sections of the analysis for more details. All versions of the somepentest-test-package package were malicious.

Is somepentest-test-package popular?

The Python package somepentest-test-package is not widely used. It has 145 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 somepentest-test-package once it is in my app?

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

145

Total Downloads

Contributors

Declared Dependencies

Dependents

Top issues

See all issues

Problem

Prevalence in PyPI community

0 packages

found in

Top 100

3 packages

found in

Top 1k

54 packages

found in

Top 10k

1.75k packages

in community

Next steps

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

Problem

Prevalence in PyPI community

0 packages

found in

Top 100

0 packages

found in

Top 1k

11 packages

found in

Top 10k

14.01k packages

in community

Next steps

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

Avoid using this software package.

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

Prevalence in PyPI community

0 packages

found in

Top 100

1 packages

found in

Top 1k

20 packages

found in

Top 10k

83.87k packages

in community

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 that their versions are pinned.

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 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.

Top behaviors

See all behaviors

Prevalence in PyPI community

Behavior often found in this community (Common)

36 packages

found in

Top 100

281 packages

found in

Top 1k

1802 packages

found in

Top 10k

66.4k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

44 packages

found in

Top 100

286 packages

found in

Top 1k

1787 packages

found in

Top 10k

48.75k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

31 packages

found in

Top 100

291 packages

found in

Top 1k

2158 packages

found in

Top 10k

142.17k packages

in community

Prevalence in PyPI community

Behavior commonly used by malicious software (Important)

Behavior uncommon for this community (Uncommon)

0 packages

found in

Top 100

2 packages

found in

Top 1k

3 packages

found in

Top 10k

673 packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

70 packages

found in

Top 100

472 packages

found in

Top 1k

4207 packages

found in

Top 10k

413.79k packages

in community

Top vulnerabilities

No vulnerabilities found.

somepentest-test-package

SAFE Assessment

Compliance

Security

Threats

IMPORTANT: All versions of this package have been maliciousLatest version with malware incident detected: about 2 months agoVersion: 1.0.0

INCIDENTS FOR THIS VERSION:

Popularity

Top issues

SQ30103Detected presence of potentially unwanted applications.Causes risk: undesirable applications foundthreats

Problem

Prevalence in PyPI community

Next steps

SQ30105Detected presence of known software supply chain attack artifacts.Causes risk: supply chain attack artifactsthreats

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

TH30103Detected presence of software components that were removed from the public package repository.Causes risk: components prone to hijackinghunting

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

Top behaviors

Encodes data using the Base64 algorithm.packer

Prevalence in PyPI community

Enumerates system information.search

Prevalence in PyPI community

Makes HTTP GET requests.network

Prevalence in PyPI community

Contains domains related to OAST (out-of-band application security testing) tools.network

Prevalence in PyPI community

The software package does not declare any source code repository.anomaly

Prevalence in PyPI community

Top vulnerabilities

FAQ for somepentest-test-package

What is somepentest-test-package?

Is somepentest-test-package malicious or is it safe to use?

Is somepentest-test-package popular?

How do I secure somepentest-test-package once it is in my app?

Did you know...

Popularity

Top issues

SQ30103Detected presence of potentially unwanted applications.Causes risk: undesirable applications foundthreats

Problem

Prevalence in PyPI community

Next steps

SQ30105Detected presence of known software supply chain attack artifacts.Causes risk: supply chain attack artifactsthreats

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

TH30103Detected presence of software components that were removed from the public package repository.Causes risk: components prone to hijackinghunting

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

Top behaviors

Encodes data using the Base64 algorithm.packer

Prevalence in PyPI community

Enumerates system information.search

Prevalence in PyPI community

Makes HTTP GET requests.network

Prevalence in PyPI community

Contains domains related to OAST (out-of-band application security testing) tools.network

Prevalence in PyPI community

The software package does not declare any source code repository.anomaly

Prevalence in PyPI community