List of software quality issues with the number of affected components.
category ALL
Policies
Info
Category
Problem
Software composition analysis has identified a component with one or more known severe vulnerabilities. Available threat intelligence telemetry has confirmed that the reported high or critical severity vulnerabilities are actively being exploited by malicious actors.
Prevalence in PyPI community
40 packages
found in
Top 100
232 packages
found in
Top 1k
2014 packages
found in
Top 10k
115.63k packages
in community
Next steps
We strongly advise updating 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 composition analysis has identified a component with one or more known vulnerabilities. Available threat intelligence telemetry has confirmed that the reported vulnerabilities are actively being exploited by malicious actors. Malware code that propagates through these vulnerabilities has been created. This increases the chance of automated malware attacks affecting the software component users.
Prevalence in PyPI community
10 packages
found in
Top 100
60 packages
found in
Top 1k
555 packages
found in
Top 10k
25.8k packages
in community
Next steps
We strongly advise updating 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. The ReversingLabs community package index may place software packages into quarantine during an ongoing security incident investigation. When a software project is placed into quarantine, it is typically unavailable for installation. Additionally, repository maintainers may also hide quarantined software projects from users that might stumble upon them using repository search functions. Quarantine is typically raised for software projects that were reported for unusual code changes or unexpected software behaviors.
Prevalence in PyPI community
1 packages
found in
Top 100
7 packages
found in
Top 1k
26 packages
found in
Top 10k
21.51k 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 composition analysis has identified a component with one or more known vulnerabilities. Based on the CVSS scoring, these vulnerabilities have been marked as high severity.
Prevalence in PyPI community
45 packages
found in
Top 100
313 packages
found in
Top 1k
2319 packages
found in
Top 10k
126.15k 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 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
0 packages
found in
Top 100
7 packages
found in
Top 1k
48 packages
found in
Top 10k
22.29k 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.
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
48 packages
found in
Top 100
274 packages
found in
Top 1k
2027 packages
found in
Top 10k
102.45k 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.
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
43 packages
found in
Top 100
210 packages
found in
Top 1k
2021 packages
found in
Top 10k
127.4k 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 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. While most behaviors are benign, some are commonly abused by malicious software with the intent to cause harm. When a software package shares behavior traits with malicious software, it may become flagged by security solutions. Any detection from security solutions can cause friction for the end-users during software deployment. While the behavior is likely intended by the developer, there is a small chance this detection is true positive, and an early indication of a software supply chain attack.
Prevalence in PyPI community
20 packages
found in
Top 100
103 packages
found in
Top 1k
958 packages
found in
Top 10k
55.62k 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.
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. Top-level domains (TLD) are a part of the Domain Name System (DNS), and are used to lookup an Internet Protocol (IP) address of a requested website. There are a few different types of top-level domains. Generic, sponsored and country-code TLDs are generally accessible to the public. Registrars that govern the assignment of domain names within the TLD may choose to sell specific domain names to an interested party. However, some registrars are known to have less strict rules for assigning domain names. Attackers often abuse gaps in governance and actively seek to register their malicious domains in such TLDs. This issue is raised for all domains registered within TLDs that harbor an excessive number of malicious sites. While the presence of suspicious TLDs does not imply malicious intent, all of its uses in a software package should be documented and approved.
Prevalence in PyPI community
12 packages
found in
Top 100
94 packages
found in
Top 1k
536 packages
found in
Top 10k
23.62k 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 changing the top-level domain to avoid being flagged by security solutions.
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
7 packages
found in
Top 100
34 packages
found in
Top 1k
839 packages
found in
Top 10k
928.02k 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.
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