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 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 are typically distributed in standardized packaging formats. Software packages are built from instructions written within package manifests that act as blueprints for package assembly. A package manifest declares the most important software properties, such as the package name, its authors and license, external dependencies, and various actions that may occur during the package lifecycle. Package managers are specialized tools used by developers to manage software components. Package managers read these manifests to deploy software components along with their dependencies. The premise of the package management system is that software components are isolated from each other, and that they rely on the package manager to provide their dependencies. However, it was detected that a software component includes code capable of accessing or modifying directories that are maintained exclusively by package managers. This is unusual as it resembles tactics used by threat actors that tamper with installed software components and inject malicious code into trusted execution paths.
Prevalence in PyPI community
8 packages
found in
Top 100
50 packages
found in
Top 1k
303 packages
found in
Top 10k
11.8k 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 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 components sometimes need to interact with sensitive parts of the runtime environment, often requiring privileged access to accomplish a task. Build pipeline configuration includes high-value information such as CI/CD platform secrets and tokens, pipeline definition files and runner configuration, build-time environment variables containing signing keys or deploy credentials, and artifact registry and package publishing credentials. That information is used by continuous integration and delivery systems. Attackers often abuse access to build pipeline configuration to harvest secrets from build environments, which can later be exfiltrated to attacker-controlled infrastructure and used to tamper with software releases or publish malicious artifacts under trusted identities. While the presence of code that accesses build pipeline 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 build pipeline configuration. One example of acceptable use for such functions is release tooling that reads publishing credentials to push artifacts.
Prevalence in PyPI community
0 packages
found in
Top 100
16 packages
found in
Top 1k
58 packages
found in
Top 10k
2.44k packages
in community
Next steps
Investigate reported detections as indicators of software tampering.
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. 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 service 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 leverage the GitHub service to deliver malicious payloads.
Prevalence in PyPI community
37 packages
found in
Top 100
233 packages
found in
Top 1k
1795 packages
found in
Top 10k
92.7k 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
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
Various network communication protocols allow including plaintext authentication credentials. Information such as user names and passwords could be passed through a non-encrypted channel, and therefore intercepted by malicious actors. Credentials are considered secrets, and should be kept encrypted until they are used. This policy control matches the following URI pattern protocol://username:password@domain within any software package component.
Prevalence in PyPI community
15 packages
found in
Top 100
78 packages
found in
Top 1k
317 packages
found in
Top 10k
13.04k packages
in community
Next steps
Review the reported matches. If the warning refers to a placeholder credential value, it can be safely ignored.
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. URL paths provide additional information to a web service when making a request. They are an optional, but an important part of the URL, as they may define specific content or actions based on the data being passed. Some parameters they pass might be considered sensitive information. Since path components are not encrypted this might cause sensitive information to leak. This issue is raised for URL paths than might contain information that attackers can easily intercept. Examples of sensitive information fields include passwords and other similar parameters.
Prevalence in PyPI community
12 packages
found in
Top 100
82 packages
found in
Top 1k
522 packages
found in
Top 10k
15.75k 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 removing all references to flagged network locations.
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 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
64 packages
found in
Top 100
413 packages
found in
Top 1k
3331 packages
found in
Top 10k
468.19k 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.