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failIncident: Removal
Scanned: 20 days ago

langchain-deepseek

Artifact:
removed
Using the deepseek model in langchain
License: Permissive (MIT)
Published: 9 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
No evidence of malware inclusion

INCIDENTS:

removal
Reported By: Community

Popularity

2.5M
Total Downloads
1
Contributor
6
Declared Dependencies
59
Dependents

Top issues

See all issues

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.

Top behaviors

See all behaviors

Prevalence in PyPI community

Behavior often found in this community (Common)
75 packages
found in
Top 100
451 packages
found in
Top 1k
3488 packages
found in
Top 10k
109392 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
24 packages
found in
Top 100
163 packages
found in
Top 1k
1243 packages
found in
Top 10k
72644 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

Prevalence in PyPI community

Behavior often found in this community (Common)
1 packages
found in
Top 100
11 packages
found in
Top 1k
85 packages
found in
Top 10k
3307 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
74 packages
found in
Top 100
606 packages
found in
Top 1k
4422 packages
found in
Top 10k
171320 packages
in community

Top vulnerabilities

No vulnerabilities found.

FAQ for langchain-deepseek

What is langchain-deepseek?

Using the deepseek model in langchain.

Is langchain-deepseek malicious or is it safe to use?

The Python package langchain-deepseek 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. 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.

Is langchain-deepseek popular?

The Python package langchain-deepseek is not widely used. It has 2M 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 langchain-deepseek once it is in my app?

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