List of software quality issues with the number of affected components.
category ALL
Policies
Info
Category
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 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 components sometimes need to interact with sensitive parts of the runtime environment, often requiring privileged access to accomplish a task. Cloud workload configuration includes high-value information such as cloud provider credentials, environment variables containing secrets, and configuration files used by cloud and container orchestration tools. That information is used by applications running in cloud and containerized environments. Attackers often abuse access to cloud workload configuration to harvest secrets from developer machines and build environments, which can later be exfiltrated to attacker-controlled infrastructure and used to gain unauthorized access to cloud resources. While the presence of code that accesses cloud workload configuration does not necessarily imply malicious intent, all of its uses in a software package should be documented and approved. Only select software components should consider using functions that read cloud workload configuration. One example of acceptable use for such functions is infrastructure-as-code tooling that legitimately needs to read credentials to provision or manage cloud resources on behalf of the developer.
Prevalence in PyPI community
5 packages
found in
Top 100
13 packages
found in
Top 1k
83 packages
found in
Top 10k
2.05k packages
in community
Next steps
Investigate reported detections as indicators of software tampering.
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. 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
2 packages
found in
Top 100
22 packages
found in
Top 1k
623 packages
found in
Top 10k
614.08k 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 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.
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 low severity.
Prevalence in PyPI community
22 packages
found in
Top 100
136 packages
found in
Top 1k
1255 packages
found in
Top 10k
76.42k packages
in community
Next steps
Perform impact analysis for the reported CVEs.
Update the component to the latest version.
Lower severity vulnerabilities can be resolved with less urgency, but you should still make a plan to do so.
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