List of software quality issues with the number of affected components.
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Category
Detected presence of known software supply chain attack artifacts.
Causes risk: supply chain attack artifacts
3
threats
Problem
Proprietary ReversingLabs malware detection algorithms have determined that the software package contains one or more malicious components. The detection was made by either a static byte signature, software component identity, or a complete file hash. This malware detection method is considered highly accurate, and can typically attribute malware to previously discovered software supply chain attacks. It is common to have multiple supply chain attack artifacts that relate to a single malware incident.Prevalence in PyPI community
0 packages
found in
Top 100
0 packages
found in
Top 1k
5 packages
found in
Top 10k
13913 packages
in community
Next steps
If the software intent does not relate to malicious behavior, investigate the build and release environment for software supply chain compromise.
Avoid using this software package.
Detected presence of malicious files through analyst-vetted file reputation.
Causes risk: analyst-vetted malware found
3
threats
Problem
Threat researchers have manually inspected the software package and determined that it contains one or more malicious files. The detection was made by a hash-based file reputation lookup. This malware detection method is considered highly accurate, and can typically identify the malware family by name.Prevalence in PyPI community
0 packages
found in
Top 100
0 packages
found in
Top 1k
7 packages
found in
Top 10k
13959 packages
in community
Next steps
Investigate the build and release environment for software supply chain compromise.
Avoid using this software package.
Detected presence of severe vulnerabilities with active exploitation.
Causes risk: actively exploited vulnerabilities
1
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
38 packages
found in
Top 100
303 packages
found in
Top 1k
2611 packages
found in
Top 10k
103184 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 malware-exploited vulnerabilities.
Causes risk: malware exploited vulnerabilities
1
vulnerabilities
Problem
Software composition analysis has identified a component with one or more known vulnerabilities. Available threat intelligence telemetry has confirmed that the reported vulnerabilities are actively being exploited by malicious actors. Malware code that propagates through these vulnerabilities has been created. This increases the chance of automated malware attacks affecting the software component users.Prevalence in PyPI community
10 packages
found in
Top 100
78 packages
found in
Top 1k
751 packages
found in
Top 10k
27887 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
1
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
25 packages
found in
Top 100
212 packages
found in
Top 1k
1951 packages
found in
Top 10k
77976 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 files with behaviors that match the backdoor malware profile.
Causes risk: malware-like behaviors found
2
hunting
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 exclusively used by malicious software with the intent to cause harm. When a software package matches behavior traits of malicious software, it becomes flagged by security solutions. It is highly likely that the software package was tampered with by a malicious actor or a rogue insider. Detected threat type matches the behaviors typically exhibited by the backdoor malware profile. Backdoors are commonly used by malicious actors to gain unauthorized access to exposed computer systems over the internet. However, due to high-privilege access requirements, some security solutions may also trigger this detection when analyzed.Prevalence in PyPI community
0 packages
found in
Top 100
0 packages
found in
Top 1k
1 packages
found in
Top 10k
183 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.
In the case this behavior is intended, rewrite the flagged code without using the malware-like behaviors.
Detected Windows executable files with imported functions susceptible to pointer hijacking.
Causes risk: execution hijacking concerns
1
hardening
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
22 packages
found in
Top 1k
138 packages
found in
Top 10k
3863 packages
in community
Next steps
Review the programming language linker options, and consider a build toolchain update.
Detected presence of high severity vulnerabilities.
Causes risk: high severity vulnerabilities
1
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
50 packages
found in
Top 100
352 packages
found in
Top 1k
2858 packages
found in
Top 10k
108771 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 software components that were recently published to the public package repository.
1
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
No prevalence information at this timeNext 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 have low popularity or number of downloads.
1
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
No prevalence information at this timeNext 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.
10