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failIncident: Malware
Scanned: 6 days ago

kirux189894

Artifact:
latest
malicious
Research
License: unknown
Published: 16 days ago
See on PyPI

SAFE Assessment

Compliance

Licenses
No license compliance issues
Secrets
No sensitive information found

Security

Vulnerabilities
No known vulnerabilities detected
Hardening
No application hardening issues

Threats

Tampering
1 suspicious application behaviors
Malware
5 undesirable applications found

INCIDENTS:

malware
7 days agoReported By: ReversingLabs (Researcher)
Learn more about malware detection
malware
6 days agoReported By: ReversingLabs (Automated)
Learn more about malware detection

Popularity

279
Total Downloads
0
Contributors
1
Declared Dependencies
0
Dependents

Top issues

See all issues

Problem

Potentially unwanted applications (PUAs) can be considered a risk by some software users. This threat type typically collects private user data, or in more extreme cases, tampers with system security settings. Most threat prevention solutions detect and block PUAs. Software packages that trigger security solution detections also tend to increase the number of support calls and open tickets from users.

Prevalence in PyPI community

1 packages
found in
Top 100
5 packages
found in
Top 1k
18 packages
found in
Top 10k
1306 packages
in community

Next steps

Revise the use of components that raise these alarms. If you can't deprecate those components, make sure they are well-documented.

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

Applications communicate with web services by exchanging HTTP requests. During software development, externally hosted services are used by developers to debug software quality issues relating to exchanging HTTP requests. Attackers commonly abuse tools designed for HTTP request inspection to monitor network traffic and extract sensitive information from the HTTP traffic. While the presence of domains related to HTTP inspection 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

10 packages
found in
Top 100
39 packages
found in
Top 1k
229 packages
found in
Top 10k
11208 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.

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 time

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 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 time

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.

Top behaviors

See all behaviors

Prevalence in PyPI community

Behavior commonly used by malicious software (Important)
Behavior uncommon for this community (Uncommon)
0 packages
found in
Top 100
6 packages
found in
Top 1k
303 packages
found in
Top 10k
8293 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
68 packages
found in
Top 100
508 packages
found in
Top 1k
3570 packages
found in
Top 10k
165477 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
26 packages
found in
Top 100
157 packages
found in
Top 1k
1202 packages
found in
Top 10k
28931 packages
in community

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

Prevalence in PyPI community

Behavior often found in this community (Common)
32 packages
found in
Top 100
280 packages
found in
Top 1k
2165 packages
found in
Top 10k
147011 packages
in community

Top vulnerabilities

No vulnerabilities found.

FAQ for kirux189894

Is kirux189894 malicious or is it safe to use?

The Python package kirux189894 was scanned for malware, software tampering, risky behaviors, exposed secrets and known vulnerabilities. Malware or tampering has been detected, making it unsafe to download and use. 1 other issue and risky behavior was found. The package contains risks, and the analysis results should be reviewed before it is downloaded and used. Visit the Issues and Behaviors sections of the analysis for more details. All versions of the kirux189894 package were malicious.

Is kirux189894 popular?

The Python package kirux189894 is not widely used. It has 279 recorded downloads. A package's popularity is not a good indicator of its safety, visit the SAFE Assessment section to see the full analysis of package deployment risk categories.

How do I secure kirux189894 once it is in my app?

Since we can't know when or where malicious attacks will happen, we recommend tracking how kirux189894 behaviors change over multiple software releases. By adopting differential analysis in your release process, you can detect unexpected changes to a kirux189894 version, which can prevent advanced software supply chain attacks. Read how our technology can help prevent future attacks similar to SolarWinds and 3CX.

Did you know...

... that you can use ReversingLabs’ Spectra Assure platform to perform regular risk assessments of packages you develop in-house?

We recommend continuous software safeness monitoring through CI/CD integrations and pre-release/deployment checks. In addition to basic package information found on this page our platform offers rich reports for developers and DevSecOps that help them remediate all reported issues.