Top issues
Detected presence of potentially unwanted applications.
Causes risk: undesirable applications found
threats
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.
Detected presence of files with behaviors similar to malicious packages published on PyPI.
Causes risk: suspicious application behaviors
hunting
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.
Detected presence of software components that had a recent package version removal incident.
hunting
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. Some open source repositories allow the developers to take down software component versions that they have published. For open source projects, version unpublishing is uncommon. Versions are typically removed due to a security incident, such as malicious code tampering or accidental development secrets exposure. Software developers often prioritize taking down such packages before informing the community that they have experienced a security incident. Therefore, it is prudent to review the reasons behind software version removals as these events might be a signal of an ongoing software supply chain attack.Prevalence in PyPI community
47 packages
found in
Top 100
238 packages
found in
Top 1k
1834 packages
found in
Top 10k
89.18k packages
in community
Next steps
Review software component documentation for the reasons behind the recent version removal.
If the software version was removed due to a security incident, 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.
Detected presence of software components that were recently published to the public package repository.
hunting
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.
Detected presence of software components that have low popularity or number of downloads.
hunting
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
Executes Zlib-compressed data.
packer
Prevalence in PyPI community
Behavior commonly used by malicious software (Important)
Behavior uncommon for this community (Uncommon)
0 packages
found in
Top 100
0 packages
found in
Top 1k
1 packages
found in
Top 10k
53 packages
in community
Decrypts data using Advanced Encryption Standard (AES).
packer
Prevalence in PyPI community
Behavior uncommon for this community (Uncommon)
0 packages
found in
Top 100
15 packages
found in
Top 1k
156 packages
found in
Top 10k
5.53k packages
in community
Decodes data using the Base64 algorithm.
packer
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
Decompresses data using the Zlib algorithm.
packer
Prevalence in PyPI community
Behavior often found in this community (Common)
22 packages
found in
Top 100
83 packages
found in
Top 1k
430 packages
found in
Top 10k
9.5k packages
in community
Executes an expression.
execution
Prevalence in PyPI community
Behavior often found in this community (Common)
53 packages
found in
Top 100
351 packages
found in
Top 1k
1856 packages
found in
Top 10k
48.82k packages
in community
Top vulnerabilities
No vulnerabilities found.