Spectra Assure
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failIncident: Malware
Scanned: about 8 hours ago

kzip

Artifact:
A compact Python library for archiving and extracting ZIP files.
License: Permissive (MIT)
New!
Published: about 8 hours ago



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
No evidence of software tampering
Malware
1 malicious components found

INCIDENTS FOR THIS VERSION:

malware
about 8 hours agoReported By: ReversingLabs (Automated)
Learn more about malware detection
removal
about 7 hours agoReported By: Community

Popularity

N/A
Total Downloads
Contributors
Declared Dependencies
0
Dependents

Top issues

Problem

Proprietary ReversingLabs malware detection algorithms have determined that the software package contains one or more malicious files. The detection was made by a machine learning model. This malware detection method is considered proactive, and can typically identify the malware threat type. 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 components to be detected as malicious.

Prevalence in PyPI community

0 packages
found in
Top 100
6 packages
found in
Top 1k
36 packages
found in
Top 10k
1693 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.
Avoid using this software package until it is vetted as safe.
Consider rewriting code that may have triggered the detection due to its malware similarity.

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

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. 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

Prevalence in PyPI community

Behavior uncommon for this community (Uncommon)
0 packages
found in
Top 100
4 packages
found in
Top 1k
4 packages
found in
Top 10k
54 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
4 packages
found in
Top 100
12 packages
found in
Top 1k
50 packages
found in
Top 10k
1145 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
6 packages
found in
Top 100
17 packages
found in
Top 1k
72 packages
found in
Top 10k
1561 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
40 packages
found in
Top 100
253 packages
found in
Top 1k
1433 packages
found in
Top 10k
53416 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
22 packages
found in
Top 100
75 packages
found in
Top 1k
397 packages
found in
Top 10k
12684 packages
in community

Top vulnerabilities

No vulnerabilities found.