List of software quality issues with the number of affected components.
category ALL
Policies
Info
Category
Problem
Proprietary ReversingLabs malware detection algorithms have determined that the software package contains one or more malicious files. The detection was made by a machine learning model. This malware detection method is considered proactive, and can typically identify the malware threat type. The detection is strongly influenced by behaviors that software components exhibit. Behaviors similar to previously discovered malware and software supply chain attacks may cause some otherwise benign components to be detected as malicious.
Prevalence in PyPI community
0 packages
found in
Top 100
2 packages
found in
Top 1k
10 packages
found in
Top 10k
328 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.
Avoid using this software package until it is vetted as safe.
Consider rewriting code that may have triggered the detection due to its malware similarity.
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. Python Package Index (PyPI) repository is often abused by threat actors to publish software packages that exhibit malicious behaviors. Malware authors use numerous tactics to lure developers into including malicious PyPI packages in their software projects. Most malicious packages published on PyPI target developers and their workstations. However, some are designed to activate only when deployed in the end-user environment. Both types of Python malicious packages are detected by proprietary ReversingLabs threat hunting algorithms. This detection method is considered proactive, and it is based on Machine Learning (ML) algorithms that can detect novel malware. The detection is strongly influenced by behaviors that software components exhibit. Behaviors similar to previously discovered malware and software supply chain attacks may cause some otherwise benign software packages to be detected by this policy.
Prevalence in PyPI community
1 packages
found in
Top 100
18 packages
found in
Top 1k
104 packages
found in
Top 10k
16.5k 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
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
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. When accessing the internet, a device is assigned a unique Internet Protocol (IP) address. This address identifies the point of origin and destination of each request a connected device makes. Attackers often aim to better understand their targets. Collecting basic reconnaissance information typically includes the IP address of a machine. While the operating system has the utilities to get this information, some attackers may prefer getting this data from an external source. Many web services host pages that return the IP address of the caller. For that reason, attackers often opt to get the IP information from a third-party service. While the presence of IP querying services does not imply malicious intent, all of their uses in a software package should be documented and approved.
Prevalence in PyPI community
0 packages
found in
Top 100
13 packages
found in
Top 1k
71 packages
found in
Top 10k
4.23k 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 mechanism for detecting the machine's IP address.
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. Webhooks are web callback interfaces that enable real-time event notifications. Applications provide a public-facing interface that the web service calls when an appropriate event occurs. Attackers often abuse Discord webhooks as a command and control mechanism that instructs the infected computer systems to perform malicious actions. While the presence of Discord webhooks 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 leverages Discord webhooks for command and control.
Prevalence in PyPI community
0 packages
found in
Top 100
2 packages
found in
Top 1k
9 packages
found in
Top 10k
1.01k 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.
Remove all references to flagged network locations.