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failIncident: Malware
Scanned: 28 days ago

aliyun-ai-labs-sdk

Artifact:
latest
malicious
Research
AI Labs SDK for Python
License: Permissive (MIT)
Published: 6 months 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 components prone to hijacking
Malware
4 undesirable applications found

INCIDENTS FOR THIS VERSION:

malware
6 months agoReported By: ReversingLabs (Researcher)
Learn more about malware detection
malware
6 months agoReported By: ReversingLabs (Automated)
Learn more about malware detection
malware
5 months agoReported By: Community (OpenSSF)
More info

Popularity

216
Total Downloads
1
Contributor
0
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 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 time

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

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 using components that are rarely used to build applications 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. Open source communities depend on the work of thousands of software developers that volunteer their time to maintain software components. Software developers build up the reputation of their open source projects by developing in public. Modern source code repositories have many social features that allow software developers to handle bug reports, have discussions with their users, and convey reaching significant project milestones. It is uncommon to find open source projects that omit linking their component to a publicly accessible source code repository.

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 often found in this community (Common)
39 packages
found in
Top 100
280 packages
found in
Top 1k
1754 packages
found in
Top 10k
67026 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
40 packages
found in
Top 100
253 packages
found in
Top 1k
1433 packages
found in
Top 10k
53416 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
68 packages
found in
Top 100
540 packages
found in
Top 1k
3644 packages
found in
Top 10k
154572 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
25 packages
found in
Top 100
193 packages
found in
Top 1k
894 packages
found in
Top 10k
24665 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
22 packages
found in
Top 100
157 packages
found in
Top 1k
996 packages
found in
Top 10k
29388 packages
in community

Top vulnerabilities

No vulnerabilities found.

FAQ for aliyun-ai-labs-sdk

What is aliyun-ai-labs-sdk?

AI Labs SDK for Python. For more information about this package, visit its homepage.

Is aliyun-ai-labs-sdk malicious or is it safe to use?

The Python package aliyun-ai-labs-sdk 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 aliyun-ai-labs-sdk package were malicious.

Is aliyun-ai-labs-sdk popular?

The Python package aliyun-ai-labs-sdk is not widely used. It has 216 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 aliyun-ai-labs-sdk once it is in my app?

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