List of software quality issues with the number of affected components.
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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.
Detected presence of software components that are rarely included by other public software packages.
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 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
1 packages
found in
Top 100
11 packages
found in
Top 1k
910 packages
found in
Top 10k
717.09k 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
70 packages
found in
Top 100
472 packages
found in
Top 1k
4207 packages
found in
Top 10k
413.79k 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 Linux executable files that were compiled without the recommended dynamic symbol hijacking protections.
Causes risk: execution hijacking concerns
hardening
Problem
On Linux, external symbols are resolved via the procedure linkage table (PLT) and the global offset table (GOT). Without any protection, both are writable at runtime and thus leave the executable vulnerable to pointer hijacking - an attack where the function address is overwritten with an address of a malicious function. Pointer hijacking can be mitigated by using full read-only relocations, which instruct the compiler to unify global offset tables into a single read-only table. This requires that all external function symbols are resolved at load-time instead of during execution, and may increase loading time for large programs.Prevalence in PyPI community
26 packages
found in
Top 100
135 packages
found in
Top 1k
847 packages
found in
Top 10k
17.09k packages
in community
Next steps
In most cases, it's recommended to use full read-only relocations (in GCC: -Wl,-z,relro,-z,now).
If the executable load-time is an issue, you should use partial read-only relocations.
Detected presence of hardcoded source code filenames or paths.
Causes risk: debugging symbols found
secrets
Problem
Common compilers often embed source code information into executables for debugging purposes, usually by mapping symbols to source filenames or paths. While this is typically desirable in open-source software and standard tools, that information can be used to determine security weaknesses, code repository layout, trade secrets and similar sensitive information. Such symbols make it easier to reverse-engineer a closed source application.Prevalence in PyPI community
27 packages
found in
Top 100
138 packages
found in
Top 1k
922 packages
found in
Top 10k
19.5k packages
in community
Next steps
Strip out such information in the linking phase by using compiler options like the -s flag in GCC, or in the post-build phase by using the strip tool.
Detected Linux executable files without any fortified functions.
Causes risk: low priority mitigations absent
hardening
Problem
Fortified functions are usually wrappers around standard glibc functions (such as memcpy) which perform boundary checks either at compile time or run time to determine if a memory violation has occurred. The compiler needs additional context to generate such calls (for example, array size that needs to be known at compile time). Because of this, the compiler will virtually never substitute all viable functions with their fortified counterparts in complex programs. However, lack of any fortified functions may indicate that this compiler feature was not used at all.Prevalence in PyPI community
21 packages
found in
Top 100
106 packages
found in
Top 1k
615 packages
found in
Top 10k
10.44k packages
in community
Next steps
In GCC, you can enable fortified functions with -D_FORTIFY_SOURCE=2 flag, while using at least -O1 optimization level.