List of software quality issues with the number of affected components.
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Problem
Security Development Lifecycle (SDL) is a group of enhanced compile-time checks that report common coding mistakes as errors. These checks prevent the use of hard-to-secure string manipulation functions. They enforce static memory access checks, and allow only the use of range-verified string parsing functions. While these checks do not prevent every memory corruption issue by themselves, they do help reduce the likelihood.
Prevalence in PyPI community
10 packages
found in
Top 100
45 packages
found in
Top 1k
247 packages
found in
Top 10k
4.13k packages
in community
Next steps
It's highly recommended to enable these checks for all software components used at security boundaries, or those that process user controlled inputs.
To enable these checks, refer to your programming language toolchain documentation.
In Microsoft VisualStudio, you can enable this feature by setting the compiler option /SDL to ON.
Problem
Security Development Lifecycle (SDL) is a group of enhanced compile-time checks that report common coding mistakes as errors, preventing them from reaching production. These checks minimize the number of security issues by enforcing strict memory access checks. They also prevent the use of hard-to-secure string and memory manipulation functions. To prove the binary has been compiled with these checks enabled, the compiler emits a special debug object. Removing the debug table eliminates this proof. Therefore, this check only applies to binaries that still have their debug tables.
Prevalence in PyPI community
12 packages
found in
Top 100
63 packages
found in
Top 1k
326 packages
found in
Top 10k
7.08k packages
in community
Next steps
You should keep the debug table to prove that the SDL process has been followed.
To enable these checks, refer to your programming language toolchain documentation.
In Microsoft VisualStudio, you can enable this feature by setting the compiler option /SDL to ON.
Problem
Security Development Lifecycle (SDL) is a group of enhanced compile-time checks that report common coding mistakes as errors. These checks prevent the use of hard-to-secure memory manipulation functions. They enforce static memory access checks, and allow only the use of range-verified memory access functions. While these checks do not prevent every memory corruption issue by themselves, they do help reduce the likelihood.
Prevalence in PyPI community
4 packages
found in
Top 100
45 packages
found in
Top 1k
242 packages
found in
Top 10k
5.25k packages
in community
Next steps
It's highly recommended to enable these checks for all software components used at security boundaries, or those that process user controlled inputs.
To enable these checks, refer to your programming language toolchain documentation.
In Microsoft VisualStudio, you can enable this feature by setting the compiler option /SDL to ON.
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
92 packages
found in
Top 1k
907 packages
found in
Top 10k
43.88k 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
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
143 packages
found in
Top 1k
833 packages
found in
Top 10k
15.19k 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
164 packages
found in
Top 1k
932 packages
found in
Top 10k
17.86k 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 indirect calls are made only to vetted functions. This mitigation protects dynamically resolved function targets by instrumenting the code responsible for transferring execution control. Function pointers that get resolved through import and delayed import address tables do not need to be monitored during application runtime. Instead, it is expected that modern programming language toolchains place those pointers in read-only memory locations. However, the delayed import functions are resolved as they are needed during runtime. To ensure the function pointers remain read-only, the operating system must be made aware if it is safe to re-protect the memory pages that hold them. Modern toolchains typically separate import data from other application regions for this very reason.
Prevalence in PyPI community
1 packages
found in
Top 100
4 packages
found in
Top 1k
38 packages
found in
Top 10k
468 packages
in community
Next steps
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
16 packages
found in
Top 100
113 packages
found in
Top 1k
669 packages
found in
Top 10k
19.67k packages
in community
Next steps
Investigate reported detections as indicators of software tampering.
Consult Mitre ATT&CK documentation: T1033 - System Owner/User Discovery.