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 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
2 packages
found in
Top 1k
18 packages
found in
Top 10k
15.82k 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.
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
1 packages
found in
Top 1k
15 packages
found in
Top 10k
15.24k packages
in community
Next steps
Investigate the build and release environment for software supply chain compromise.
Avoid using this software package.
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
6 packages
found in
Top 10k
2.63k 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.
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. Open source communities depend on the work of thousands of software developers that volunteer their time to maintain software components. While the majority of open source contributors are altruistic and trustworthy, some software developers are also members of security research or bug bounty programs. Researchers that participate in bug bounty programs develop applications that leak sensitive environment information to prove that they've successfully bypassed security mechanisms. Code written by these software developers should be put under a higher degree of scrutiny, and their code should never appear in software packages intended for release.
Prevalence in PyPI community
0 packages
found in
Top 100
0 packages
found in
Top 1k
0 packages
found in
Top 10k
296 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.
Consider removing the software component.
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. The ReversingLabs community package index may place software packages into quarantine during an ongoing security incident investigation. When a software project is placed into quarantine, it is typically unavailable for installation. Additionally, repository maintainers may also hide quarantined software projects from users that might stumble upon them using repository search functions. Quarantine is typically raised for software projects that were reported for unusual code changes or unexpected software behaviors.
Prevalence in PyPI community
1 packages
found in
Top 100
7 packages
found in
Top 1k
26 packages
found in
Top 10k
21.51k 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.
Revise the use of components that raise these alarms. If you can't deprecate those components, make sure they are well-documented.
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. 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
0 packages
found in
Top 100
7 packages
found in
Top 1k
48 packages
found in
Top 10k
22.29k 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. 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
2 packages
found in
Top 100
12 packages
found in
Top 1k
54 packages
found in
Top 10k
99.05k 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.
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.
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
2 packages
found in
Top 100
22 packages
found in
Top 1k
623 packages
found in
Top 10k
614.08k packages
in community
Next 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
20 packages
found in
Top 100
103 packages
found in
Top 1k
958 packages
found in
Top 10k
55.62k 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
Out-of-band application security testing tools (OAST) rely on external servers to detect security vulnerabilities in web applications. This form of security testing inspects the web application from the outside in, similar to how the attackers would probe its defenses. External domains are commonly used to facilitate out-of-band security testing. Attackers commonly abuse tools designed for security testing to monitor network traffic and find weaknesses that can be exploited. While the presence of domains related to OAST tools does not imply malicious intent, all of their uses in a software package should be documented and approved. Attackers might have purposely injected security testing tools in the software package to monitor the network traffic of the infected computer system. It is also possible that the software package has mistakenly included a part of its testing infrastructure during packaging.
Prevalence in PyPI community
0 packages
found in
Top 100
2 packages
found in
Top 1k
2 packages
found in
Top 10k
936 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 removing all references to flagged network locations.
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