Top issues
Detected presence of files with behaviors similar to malicious packages published on PyPI.
Causes risk: suspicious application behaviors
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. 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
47 packages
found in
Top 100
226 packages
found in
Top 1k
1735 packages
found in
Top 10k
74797 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. One or more embedded URLs were discovered to link to raw files hosted on GitHub. Attackers often abuse popular web services to host malicious payloads. Since code-sharing services URLs are typically allowed by security solutions, using them for payload delivery increases the odds that the malicious code will reach the user. While the presence of code-sharing service locations 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 the GitHub service to deliver malicious payloads.Prevalence in PyPI community
33 packages
found in
Top 100
206 packages
found in
Top 1k
1631 packages
found in
Top 10k
63840 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 delivery mechanism for software packages.
Detected presence of software components that were recently published to the public package repository.
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.
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
0 packages
found in
Top 100
2 packages
found in
Top 1k
7 packages
found in
Top 10k
1009 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.
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
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.
Top behaviors
Contains Base64-encoded URLs.
anomaly
Prevalence in PyPI community
Behavior commonly used by malicious software (Important)
Behavior uncommon for this community (Uncommon)
0 packages
found in
Top 100
2 packages
found in
Top 1k
24 packages
found in
Top 10k
759 packages
in community
Decodes data using the Base64 algorithm.
packer
Prevalence in PyPI community
Behavior often found in this community (Common)
40 packages
found in
Top 100
253 packages
found in
Top 1k
1433 packages
found in
Top 10k
53416 packages
in community
Contains URLs that link to raw files on GitHub.
network
Prevalence in PyPI community
Behavior often found in this community (Common)
33 packages
found in
Top 100
207 packages
found in
Top 1k
1634 packages
found in
Top 10k
63910 packages
in community
Contains unusually long strings.
anomaly
Prevalence in PyPI community
Behavior often found in this community (Common)
49 packages
found in
Top 100
364 packages
found in
Top 1k
2374 packages
found in
Top 10k
87567 packages
in community
Opens a URL.
network
Prevalence in PyPI community
Behavior often found in this community (Common)
30 packages
found in
Top 100
161 packages
found in
Top 1k
1162 packages
found in
Top 10k
32895 packages
in community
Top vulnerabilities
No vulnerabilities found.