List of software quality issues with the number of affected components.
category ALL
Policies
Info
Category
Detected presence of severe vulnerabilities with active exploitation.
Causes risk: actively exploited vulnerabilities
vulnerabilities
Problem
Software composition analysis has identified a component with one or more known severe vulnerabilities. Available threat intelligence telemetry has confirmed that the reported high or critical severity vulnerabilities are actively being exploited by malicious actors.Prevalence in PyPI community
35 packages
found in
Top 100
210 packages
found in
Top 1k
1787 packages
found in
Top 10k
86.39k packages
in community
Next steps
We strongly advise updating the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.
Detected presence of critical severity vulnerabilities.
Causes risk: critical severity vulnerabilities
vulnerabilities
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 critical severity.Prevalence in PyPI community
27 packages
found in
Top 100
156 packages
found in
Top 1k
1294 packages
found in
Top 10k
58.62k packages
in community
Next steps
Perform impact analysis for the reported CVEs.
We strongly advise updating the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.
Detected presence of high severity vulnerabilities.
Causes risk: high severity vulnerabilities
vulnerabilities
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
42 packages
found in
Top 100
278 packages
found in
Top 1k
1960 packages
found in
Top 10k
77.08k 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.
Detected presence of medium severity vulnerabilities.
Causes risk: medium severity vulnerabilities
vulnerabilities
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
36 packages
found in
Top 100
209 packages
found in
Top 1k
1750 packages
found in
Top 10k
81.53k 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.
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 low severity vulnerabilities.
Causes risk: low severity vulnerabilities
vulnerabilities
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
19 packages
found in
Top 100
59 packages
found in
Top 1k
395 packages
found in
Top 10k
11.9k 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.
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.
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.