Spectra Assure
Community
failIncident: Malware
Scanned: 12 days ago

xlutils

Artifact:
Utilities for working with Excel files that require both xlrd and xlwt
License: Permissive (MIT)
Published: over 9 years 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 develop dependencies

INCIDENTS FOR THIS VERSION:

malware
4 months agoReported By: ReversingLabs (Automated)
Learn more about malware detection

Popularity

24.56M
Total Downloads
Contributor
Declared Dependencies
71
Dependents

Top issues

Problem

Proprietary ReversingLabs malware detection algorithms have determined that the software package has one or more malicious development dependencies. Development dependencies may be optional, and could be installed or downloaded only if a certain pre-defined condition is met. Development dependencies are used by software developers during application production. Presence of malicious development dependencies could be an indication of a software build pipeline compromise. When software dependencies are confirmed to be found within the software package, additional issues might also be reported. 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.

Prevalence in PyPI community

0 packages
found in
Top 100
0 packages
found in
Top 1k
2 packages
found in
Top 10k
25 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 they are well-documented.
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

70 packages
found in
Top 100
472 packages
found in
Top 1k
4207 packages
found in
Top 10k
413.79k 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

Prevalence in PyPI community

Behavior often found in this community (Common)
68 packages
found in
Top 100
533 packages
found in
Top 1k
3858 packages
found in
Top 10k
146.15k packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
45 packages
found in
Top 100
306 packages
found in
Top 1k
2155 packages
found in
Top 10k
51.08k packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
20 packages
found in
Top 100
182 packages
found in
Top 1k
1802 packages
found in
Top 10k
186.71k 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

Prevalence in PyPI community

Behavior often found in this community (Common)
74 packages
found in
Top 100
598 packages
found in
Top 1k
4564 packages
found in
Top 10k
227.42k packages
in community

Top vulnerabilities

No vulnerabilities found.