Spectra Assure

failIncident: Malware

Scanned:

hardixx-code

Artifact:

latest

removed

malicious

Research

Advanced Free Fire packet analysis, decryption, and reverse engineering library

License: Permissive (MIT)

Published:

Visit GitHub

See on PyPI

SAFE Assessment

Compliance

Licenses

1 software distribution restrictions

Secrets

No sensitive information found

Security

Vulnerabilities

1 medium severity vulnerabilities

Hardening

No application hardening issues

Threats

Tampering

1 components prone to hijacking

Malware

3 supply chain attack artifacts

INCIDENTS FOR THIS VERSION:

malware

Reported By: Community (OpenSSF)

More info

malware

Reported By: ReversingLabs (Researcher)

Learn more about malware detection

removal

Reported By: Community

malware

N/AReported By: Community (Badpackages)

More info

List of software quality issues with the number of affected components.

Policies

Info

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

Threat researchers have manually inspected the software package and determined that it contains one or more malicious files. The detection was made by a hash-based file reputation lookup. This malware detection method is considered highly accurate, and can typically identify the malware family by name.

Prevalence in PyPI community

0 packages

found in

Top 100

0 packages

found in

Top 1k

10 packages

found in

Top 10k

14.02k packages

in community

Next steps

Investigate the build and release environment for software supply chain compromise.

Avoid using this software package.

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.

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

1 packages

found in

Top 100

13 packages

found in

Top 1k

37 packages

found in

Top 10k

443.06k 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 license is a legal instrument that governs the use and distribution of software source code and its binary representation. Software publishers have the freedom to choose any commonly used or purposefully written license to publish their work under. While some licenses are liberal and allow almost any kind of distribution, with or without code modification, other licenses are more restrictive and impose rules for their inclusion in other software projects. Some software licenses place restrictions on software distribution of the code they apply to. These restrictions may extend to the services built upon the code licensed under such restrictive licenses. Some restrictive licenses explicitly state that the licensee may not provide the software to third parties as a hosted or managed service, where the service provides users with access to any substantial set of the features or functionality of the licensed software. When building commercial applications, this is typically undesirable. Therefore, the inclusion of any code that may impose limits on software distribution is commonly avoided or even prohibited by the organization policy.

Prevalence in PyPI community

7 packages

found in

Top 100

82 packages

found in

Top 1k

1208 packages

found in

Top 10k

109.57k packages

in community

Next steps

Confirm that the software package references a component or a dependency with a restrictive license.

Consider replacing the software component with an alternative that offers a license compatible with organization policy.

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

36 packages

found in

Top 100

209 packages

found in

Top 1k

1750 packages

found in

Top 10k

81.53k 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

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.

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.

This website uses cookies to ensure the best website experience. By continuing to use this website you are giving your consent to cookies being used. Detailed information about our use of cookies is here.

List of software quality issues with the number of affected components.

Policies

Info

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

0 packages

found in

Top 100

0 packages

found in

Top 1k

10 packages

found in

Top 10k

14.02k packages

in community

Next steps

Investigate the build and release environment for software supply chain compromise.

Avoid using this software package.

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.

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

1 packages

found in

Top 100

13 packages

found in

Top 1k

37 packages

found in

Top 10k

443.06k 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

Prevalence in PyPI community

7 packages

found in

Top 100

82 packages

found in

Top 1k

1208 packages

found in

Top 10k

109.57k packages

in community

Next steps

Confirm that the software package references a component or a dependency with a restrictive license.

Consider replacing the software component with an alternative that offers a license compatible with organization policy.

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

36 packages

found in

Top 100

209 packages

found in

Top 1k

1750 packages

found in

Top 10k

81.53k 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

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.

hardixx-code

SAFE Assessment

Compliance

Security

Threats

IMPORTANT: All versions of this package have been maliciousLatest version with malware incident detected: 3 months agoVersion: 1.0.5

INCIDENTS FOR THIS VERSION:

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

Problem

Prevalence in PyPI community

Next steps

SQ30109Detected presence of malicious files through analyst-vetted file reputation.Causes risk: analyst-vetted malware foundthreats

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

TH30106Detected presence of software components that have low popularity or number of downloads.hunting

Problem

Prevalence in PyPI community

Next steps

SQ12405Detected presence of licenses that place restrictions on software distribution.Causes risk: software distribution restrictionslicenses

Problem

Prevalence in PyPI community

Next steps

SQ31106Detected presence of medium severity vulnerabilities.Causes risk: medium severity vulnerabilitiesvulnerabilities

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

Did you know...

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

Problem

Prevalence in PyPI community

Next steps

SQ30109Detected presence of malicious files through analyst-vetted file reputation.Causes risk: analyst-vetted malware foundthreats

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

TH30106Detected presence of software components that have low popularity or number of downloads.hunting

Problem

Prevalence in PyPI community

Next steps

SQ12405Detected presence of licenses that place restrictions on software distribution.Causes risk: software distribution restrictionslicenses

Problem

Prevalence in PyPI community

Next steps

SQ31106Detected presence of medium severity vulnerabilities.Causes risk: medium severity vulnerabilitiesvulnerabilities

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