Spectra Assure

failIncident: Malware

Scanned:

composer-dev

Artifact:

latest

removed

malicious

Research

Security research - Google VRP dependency confusion PoC. Contact: security@example.com

License: unknown

Published:

Visit GitHub

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 malware-like behaviors found

Malware

5 analyst-vetted malware found

INCIDENTS FOR THIS VERSION:

malware

Reported By: Community (kam193)

More info

malware

Reported By: Community (OpenSSF)

More info

malware

Reported By: ReversingLabs (Researcher)

Learn more about malware detection

removal

Reported By: Community

Popularity

192

Total Downloads

Contributor

Declared Dependencies

Dependents

Top issues

See all issues

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.

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.

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. 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

0 packages

found in

Top 100

1 packages

found in

Top 1k

20 packages

found in

Top 10k

83.87k 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

0 packages

found in

Top 100

0 packages

found in

Top 1k

5 packages

found in

Top 10k

38.63k 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.

Top behaviors

See all behaviors

Prevalence in PyPI community

Behavior uncommon for this community (Uncommon)

2 packages

found in

Top 100

14 packages

found in

Top 1k

92 packages

found in

Top 10k

2.94k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

67 packages

found in

Top 100

525 packages

found in

Top 1k

4055 packages

found in

Top 10k

154.83k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

30 packages

found in

Top 100

166 packages

found in

Top 1k

1155 packages

found in

Top 10k

31.66k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

37 packages

found in

Top 100

269 packages

found in

Top 1k

1633 packages

found in

Top 10k

59.6k packages

in community

Prevalence in PyPI community

Behavior commonly used by malicious software (Important)

Behavior uncommon for this community (Uncommon)

0 packages

found in

Top 100

13 packages

found in

Top 1k

71 packages

found in

Top 10k

4.24k packages

in community

Top vulnerabilities

No vulnerabilities found.

FAQ for composer-dev

What is composer-dev?

Security research - Google VRP dependency confusion PoC. Contact: security@example.com. For more information about this package, visit its homepage.

Is composer-dev malicious or is it safe to use?

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

Is composer-dev popular?

The Python package composer-dev is not widely used. It has 192 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 composer-dev once it is in my app?

Since we can't know when or where malicious attacks will happen, we recommend tracking how composer-dev behaviors change over multiple software releases. By adopting differential analysis in your release process, you can detect unexpected changes to a composer-dev 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.

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Popularity

192

Total Downloads

Contributor

Declared Dependencies

Dependents

Top issues

See all issues

Problem

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.

Problem

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.

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

Prevalence in PyPI community

0 packages

found in

Top 100

1 packages

found in

Top 1k

20 packages

found in

Top 10k

83.87k 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

0 packages

found in

Top 100

0 packages

found in

Top 1k

5 packages

found in

Top 10k

38.63k 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.

Top behaviors

See all behaviors

Prevalence in PyPI community

Behavior uncommon for this community (Uncommon)

2 packages

found in

Top 100

14 packages

found in

Top 1k

92 packages

found in

Top 10k

2.94k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

67 packages

found in

Top 100

525 packages

found in

Top 1k

4055 packages

found in

Top 10k

154.83k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

30 packages

found in

Top 100

166 packages

found in

Top 1k

1155 packages

found in

Top 10k

31.66k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

37 packages

found in

Top 100

269 packages

found in

Top 1k

1633 packages

found in

Top 10k

59.6k packages

in community

Prevalence in PyPI community

Behavior commonly used by malicious software (Important)

Behavior uncommon for this community (Uncommon)

0 packages

found in

Top 100

13 packages

found in

Top 1k

71 packages

found in

Top 10k

4.24k packages

in community

Top vulnerabilities

No vulnerabilities found.

composer-dev

SAFE Assessment

Compliance

Security

Threats

IMPORTANT: All versions of this package have been maliciousLatest version with malware incident detected: about 2 months agoVersion: 9.9.9

INCIDENTS FOR THIS VERSION:

Popularity

Top issues

SQ30109Detected presence of malicious files through analyst-vetted file reputation.Causes risk: analyst-vetted malware foundthreats

Problem

Prevalence in PyPI community

Next steps

TH15108Detected presence of files with behaviors that match the infostealer malware profile.Causes risk: malware-like behaviors foundhunting

Problem

Prevalence in PyPI community

Next steps

TH15501Detected presence of files with behaviors similar to malicious packages published on PyPI.Causes risk: suspicious application behaviorshunting

Problem

Prevalence in PyPI community

Next steps

TH30103Detected presence of software components that were removed from the public package repository.Causes risk: components prone to hijackinghunting

Problem

Prevalence in PyPI community

Next steps

TH30105Detected presence of software components that were recently published to the public package repository.hunting

Problem

Prevalence in PyPI community

Next steps

Top behaviors

Queries the computer's network name.search

Prevalence in PyPI community

Contains IP addresses.network

Prevalence in PyPI community

Opens a URL.network

Prevalence in PyPI community

Contains URLs that reference the host by IP address.network

Prevalence in PyPI community

Contains URLs related to IP querying services.network

Prevalence in PyPI community

Top vulnerabilities

FAQ for composer-dev

What is composer-dev?

Is composer-dev malicious or is it safe to use?

Is composer-dev popular?

How do I secure composer-dev once it is in my app?

Did you know...

Popularity

Top issues

SQ30109Detected presence of malicious files through analyst-vetted file reputation.Causes risk: analyst-vetted malware foundthreats

Problem

Prevalence in PyPI community

Next steps

TH15108Detected presence of files with behaviors that match the infostealer malware profile.Causes risk: malware-like behaviors foundhunting

Problem

Prevalence in PyPI community

Next steps

TH15501Detected presence of files with behaviors similar to malicious packages published on PyPI.Causes risk: suspicious application behaviorshunting

Problem

Prevalence in PyPI community

Next steps

TH30103Detected presence of software components that were removed from the public package repository.Causes risk: components prone to hijackinghunting

Problem

Prevalence in PyPI community

Next steps

TH30105Detected presence of software components that were recently published to the public package repository.hunting

Problem

Prevalence in PyPI community

Next steps

Top behaviors

Queries the computer's network name.search

Prevalence in PyPI community

Contains IP addresses.network

Prevalence in PyPI community

Opens a URL.network

Prevalence in PyPI community

Contains URLs that reference the host by IP address.network

Prevalence in PyPI community

Contains URLs related to IP querying services.network

Prevalence in PyPI community