Top issues
Detected presence of known software supply chain attack artifacts.
Causes risk: supply chain attack artifacts
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
11 packages
found in
Top 10k
14.01k 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
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
10 packages
found in
Top 10k
14.02k packages
in community
Next steps
Investigate the build and release environment for software supply chain compromise.
Avoid using this software package.
Detected presence of files with behaviors that match the infostealer malware profile.
Causes risk: malware-like behaviors found
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 infostealer malware profile. Infostealers are commonly used to steal sensitive user data such as stored login details, financial information, and other personally identifiable information.Prevalence in PyPI community
0 packages
found in
Top 100
0 packages
found in
Top 1k
3 packages
found in
Top 10k
2.05k packages
in community
Next steps
Investigate reported detections.
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 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
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 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. Developers that use open source components within their applications can specify the exact version of the component their application depends on. However, since components are frequently updated, some developers opt to always use the latest version of the software component. This helps reduce the number of vulnerabilities that open source components can introduce in the application. However, it does expose the developer and the build environment to risks associated with software supply chain attacks. Should a threat actor hijack the ownership of the software component publishing account, or even its publishing token, they could issue a malicious update that can infect the build environment or the application itself. To ensure that the build system updates the software component to a malicious version, threat actors often set the version number to an unusually high value. If a build system is instructed to use the latest component version, it will install the component with the highest version number, and execute its code.Prevalence in PyPI community
0 packages
found in
Top 100
1 packages
found in
Top 1k
7 packages
found in
Top 10k
492 packages
in community
Next steps
Review software component versions to ensure there were no accidental code updates.
If the software component versions differ from expected, investigate the build and release environment for software supply chain compromise.
Consider pinning the software component version to prevent accidental code updates.
Avoid using this software package until it is vetted as safe.
Top behaviors
Creates a process.
execution
Prevalence in PyPI community
Behavior often found in this community (Common)
69 packages
found in
Top 100
506 packages
found in
Top 1k
3612 packages
found in
Top 10k
163.85k packages
in community
The software package is published with an unusual version number.
anomaly
Prevalence in PyPI community
Behavior commonly used by malicious software (Important)
Behavior uncommon for this community (Uncommon)
0 packages
found in
Top 100
1 packages
found in
Top 1k
7 packages
found in
Top 10k
492 packages
in community
Enumerates environment variables related to Amazon Web Services (AWS).
search
Prevalence in PyPI community
Behavior often found in this community (Common)
6 packages
found in
Top 100
39 packages
found in
Top 1k
230 packages
found in
Top 10k
5.1k packages
in community
Queries the login name of the user.
search
Prevalence in PyPI community
Behavior often found in this community (Common)
9 packages
found in
Top 100
64 packages
found in
Top 1k
343 packages
found in
Top 10k
11.88k packages
in community
Enumerates system information.
search
Prevalence in PyPI community
Behavior often found in this community (Common)
44 packages
found in
Top 100
286 packages
found in
Top 1k
1787 packages
found in
Top 10k
48.75k packages
in community
Top vulnerabilities
No vulnerabilities found.