List of software quality issues with the number of affected components.
category ALL
Policies
Info
Count
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 active web service tokens.
Causes risk: active web service credentials
1
secrets
Problem
Software as a Service (SaaS) platforms expose programmable interfaces to their authenticated users. These web services enable action automation and secure exchange of information. For authorization, users provide a unique token that confirms their access rights to the web service. Access tokens for supported web services are automatically validated via the least privilege APIs the service exposes. Detected tokens have been accepted as valid by the services they are associated with. This indicates they are currently active and may be abused if exposed to the public. Web service access tokens are considered secrets. They should never be included in a software release package, even if they are obfuscated by encryption on the client-side.Prevalence in PyPI community
0 packages
found in
Top 100
0 packages
found in
Top 1k
1 packages
found in
Top 10k
299 packages
in community
Next steps
You should securely store web service access tokens, and fully automate their management and periodic rotation.
If tokens were published unintentionally and the software has been made public, you should revoke exposed tokens and file a security incident.
Examples of service tokens that may have been detected include AWS, Facebook, JWT, SWT, Slack and others.
Detected presence of files with behaviors that match the infostealer 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 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
1 packages
found in
Top 10k
1960 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
1
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.
Detected presence of software components that were removed from the public package repository.
Causes risk: components prone to hijacking
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. Open source projects are the intellectual property of their respective authors. At any time, the authors may choose to completely remove the software component from a public repository. This often occurs when a software project reaches its end-of-life stage, or when the software authors lose interest in maintaining the project. This kind of removal frees up the software package name, its unique software identifier in the public repository, for other developers to use. However, new software project owners might have malicious intent. Threat actors are continuously monitoring popular package names in case their unique identifiers suddenly become available for hijacking. Once the software projects falls under new ownership, the new maintainers may opt to use the project popularity to spread malware to unsuspecting users.Prevalence in PyPI community
No prevalence information at this timeNext 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.
Revise the use of components that raise these alarms. If you can't deprecate those components, make sure that their versions are pinned.
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.
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.
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
11 packages
found in
Top 1k
67 packages
found in
Top 10k
3941 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
1002 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.
10