Spectra Assure
Community
failIncident: Malware
Scanned: 5 days ago

bigpyx

Artifact:
latest
malicious
A small, easy-to-use wrapper around Python's Decimal with configurable precision and rounding.
License: Permissive (MIT)
Published: about 2 months 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
4 supply chain attack artifacts

INCIDENTS FOR THIS VERSION:

malware
about 2 months agoReported By: Community (OpenSSF)
malware
about 1 month agoReported By: ReversingLabs (Researcher)
Learn more about malware detection

Popularity

519
Total Downloads
Contributor
Declared Dependencies
0
Dependents

Top issues

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

Uniform Resource Locators (URLs) are structured addresses that point to locations and assets on the internet. URLs allow software developers to build complex applications that exchange data with servers that can be hosted in multiple geographical regions. URLs can commonly be found embedded in documentation, configuration files, source code and compiled binaries. One or more embedded URLs were discovered to link to raw files hosted on GitHub. Attackers often abuse popular web services to host malicious payloads. Since code-sharing services URLs are typically allowed by security solutions, using them for payload delivery increases the odds that the malicious code will reach the user. While the presence of code-sharing service locations does not imply malicious intent, all of their uses in a software package should be documented and approved. An increasing number of software supply chain attacks in the open source space leverages the GitHub service to deliver malicious payloads.

Prevalence in PyPI community

36 packages
found in
Top 100
219 packages
found in
Top 1k
1678 packages
found in
Top 10k
63.41k packages
in community

Next steps

Investigate reported detections.
If the software should not include these network references, 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 an alternative delivery mechanism for software packages.

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.

Top behaviors

Prevalence in PyPI community

Behavior often found in this community (Common)
39 packages
found in
Top 100
252 packages
found in
Top 1k
1477 packages
found in
Top 10k
53.15k packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
36 packages
found in
Top 100
219 packages
found in
Top 1k
1678 packages
found in
Top 10k
63.42k packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
51 packages
found in
Top 100
408 packages
found in
Top 1k
2829 packages
found in
Top 10k
106.17k packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
30 packages
found in
Top 100
166 packages
found in
Top 1k
1155 packages
found in
Top 10k
31.66k packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
24 packages
found in
Top 100
199 packages
found in
Top 1k
959 packages
found in
Top 10k
27.04k packages
in community

Top vulnerabilities

No vulnerabilities found.