List of software quality issues with the number of affected components.
category ALL
Policies
Info
Category
Problem
Sensitive executable memory regions should be kept as read-only to protect the integrity of trusted execution code flow paths. Imported function addresses are pointers to the symbols that implement the application-required functionality. If those pointers are changed by malicious code, execution paths can be redirected to unintended locations. Most modern programming language toolchains protect those memory regions appropriately. These issues are commonly reported for outdated linkers and non-compliant executable packing solutions.
Prevalence in PyPI community
14 packages
found in
Top 100
32 packages
found in
Top 1k
154 packages
found in
Top 10k
4.75k packages
in community
Next steps
Review the programming language linker options, and consider a build toolchain update.
Problem
Sensitive executable memory regions should be kept as read-only to protect the integrity of trusted execution code flow paths. Thread local storage (TLS) callbacks are pointers to code initialization and resource release functions. If those pointers are changed by malicious code, execution paths can be redirected to unintended locations. Most modern programming language toolchains protect those memory regions appropriately. These issues are commonly reported for outdated linkers and non-compliant executable packing solutions.
Prevalence in PyPI community
6 packages
found in
Top 100
19 packages
found in
Top 1k
110 packages
found in
Top 10k
3.49k packages
in community
Next steps
Review the programming language linker options, and consider a build toolchain update.
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. Some open source projects have a history of security lapses that culminated with a publication of one or more malicious component versions. To ensure that repeated supply chain incidents do not occur, the open source project should be closely monitored for up to two years. All software package versions that are published within two years of the malware incident will convey a warning about the history of security incidents tied to the open source project.
Prevalence in PyPI community
5 packages
found in
Top 100
21 packages
found in
Top 1k
132 packages
found in
Top 10k
2.52k 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 that their versions are pinned.
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
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 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
Control Flow Guard (CFG/CFI) protects the code flow integrity by ensuring that indirect calls are made only to vetted functions. This mitigation protects dynamically resolved function targets by instrumenting the code responsible for transferring execution control. Because the code flow integrity is verified during runtime, malicious code is less likely to be able to hijack trusted execution paths.
Prevalence in PyPI community
28 packages
found in
Top 100
119 packages
found in
Top 1k
511 packages
found in
Top 10k
10.89k packages
in community
Next steps
It's highly recommended to enable this option for all software components used at security boundaries, or those that process user controlled inputs.
To enable this mitigation, refer to your programming language toolchain documentation.
In Microsoft VisualStudio, you can enable CFG mitigation by passing the /guard:cf parameter to the compiler and linker.
Problem
Control Flow Guard (CFG/CFI) protects the code flow integrity by ensuring that dynamic calls are made only to vetted functions. Trusted execution paths rely on the ability of the operating system to build a list of valid function targets. Certain functions can intentionally be disallowed to prevent malicious code from deactivating vulnerability mitigation features. A list of such invalid function targets can include publicly exported symbols. Applications that enhance control flow integrity through export suppression rely on libraries to mark their publicly visible symbols as suppressed. This is done for all symbols that are considered to be sensitive functions, and to which access should be restricted. It is considered dangerous to mix applications that perform export suppression with libraries that do not.
Prevalence in PyPI community
30 packages
found in
Top 100
155 packages
found in
Top 1k
849 packages
found in
Top 10k
23.76k packages
in community
Next steps
To enable this mitigation on library code, refer to your programming language toolchain documentation.
In Microsoft VisualStudio, you can enable CFG mitigation by passing the /guard:cf parameter to the compiler and linker.
Problem
Control Flow Guard (CFG/CFI) protects the code flow integrity by ensuring that indirect calls are made only to vetted functions. This mitigation protects dynamically resolved function targets by instrumenting the code responsible for transferring execution control. Higher-level programming languages implement structured exception handling by managing their own code flow execution paths. As such, they are subject to code flow hijacking during runtime. Language-specific exception handling mitigation enforces execution integrity by instrumenting calls to manage execution context switching. Any deviation from the known and trusted code flow paths will cause the application to terminate. This makes malicious code less likely to execute.
Prevalence in PyPI community
36 packages
found in
Top 100
177 packages
found in
Top 1k
956 packages
found in
Top 10k
27.76k packages
in community
Next steps
It's highly recommended to enable this option for all software components used at security boundaries, or those that process user controlled inputs.
To enable this mitigation, refer to your programming language toolchain documentation.
In Microsoft VisualStudio, you can enable CFG mitigation by passing the /guard:cf parameter to the compiler and linker.
Problem
Operating systems allow multiple user accounts to coexist on a single computer system. Each registered user has identity information associated with their account. At the very least, user accounts consist of a user name and an optional password. In some cases, user account data may also include personally identifiable information. Extended personal information may include user's given and last name, their email and mailing address, personal photo and their telephone number. Financially motivated attackers may seek to collect personal information for purposes of selling the private data to a third-party. Malicious code that typically exhibits these behavior traits is commonly referred to as an information stealer. While the presence of code that accesses identity information does not necessarily imply malicious intent, all of its uses in a software package should be documented and approved. Accessing identity information is a very common behavior for software packages. One example of acceptable use for such functions is verifying that the active user has purchased a software license that allows them to run the application.
Prevalence in PyPI community
17 packages
found in
Top 100
116 packages
found in
Top 1k
699 packages
found in
Top 10k
27.52k packages
in community
Next steps
Investigate reported detections as indicators of software tampering.
Consult Mitre ATT&CK documentation: T1033 - System Owner/User Discovery.