Spectra Assure

failIncident: Malware

Scanned:

tensorflow-opt

Artifact:

latest

removed

malicious

Research

License: Permissive (MIT)

Published:

Visit GitHub

See on PyPI

SAFE Assessment

Compliance

Licenses

No license compliance issues

Secrets

No sensitive information found

Security

Vulnerabilities

19 severe vulnerabilities exploited

Hardening

1 baseline mitigations missing

Threats

Tampering

2 malware-like behaviors found

Malware

4 supply chain attack artifacts

INCIDENTS FOR THIS VERSION:

malware

Reported By: ReversingLabs (Automated)

Learn more about malware detection

malware

Reported By: Community (OpenSSF)

More info

removal

Reported By: Community

malware

Reported By: ReversingLabs (Researcher)

Learn more about malware detection

malware

N/AReported By: Community (kam193)

More info

Overview issues23 vulnerabilities92 malware5 behaviors213 dependencies0 contributors1 versions26

Popularity

22.69k

Total Downloads

Contributor

Declared Dependencies

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

0 packages

found in

Top 100

3 packages

found in

Top 1k

54 packages

found in

Top 10k

1.75k 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

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

0 packages

found in

Top 1k

11 packages

found in

Top 10k

14.01k 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

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 composition analysis has identified a component with one or more known severe vulnerabilities. Available threat intelligence telemetry has confirmed that the reported high or critical severity vulnerabilities are actively being exploited by malicious actors.

Prevalence in PyPI community

35 packages

found in

Top 100

210 packages

found in

Top 1k

1787 packages

found in

Top 10k

86.39k packages

in community

Next steps

We strongly advise updating the component to the latest version.

If the update can't resolve the issue, create a plan to isolate or replace the affected component.

Problem

Software composition analysis has identified a component with one or more known vulnerabilities. Based on the CVSS scoring, these vulnerabilities have been marked as critical severity.

Prevalence in PyPI community

27 packages

found in

Top 100

156 packages

found in

Top 1k

1294 packages

found in

Top 10k

58.62k packages

in community

Next steps

45 (45 Fixable)

CVE-2016-9841c

CVE-2016-9843c

CVE-2018-1000007c

None

Exploits Unknown

Exploits Exist

Exploited by Malware

Patching Mandated

FAQ for tensorflow-opt

What is tensorflow-opt?

For more information about this package, visit its homepage.

Is tensorflow-opt malicious or is it safe to use?

The Python package tensorflow-opt 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. 21 other issues and risky behaviors were 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 tensorflow-opt package were malicious.

Is tensorflow-opt popular?

The Python package tensorflow-opt is not widely used. It has 23K 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 tensorflow-opt once it is in my app?

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

This website uses cookies to ensure the best website experience. By continuing to use this website you are giving your consent to cookies being used. Detailed information about our use of cookies is here.

Popularity

22.69k

Total Downloads

Contributor

Declared Dependencies

Dependents

Top issues

See all issues

Problem

Prevalence in PyPI community

0 packages

found in

Top 100

3 packages

found in

Top 1k

54 packages

found in

Top 10k

1.75k 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

Prevalence in PyPI community

0 packages

found in

Top 100

0 packages

found in

Top 1k

11 packages

found in

Top 10k

14.01k 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

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

35 packages

found in

Top 100

210 packages

found in

Top 1k

1787 packages

found in

Top 10k

86.39k packages

in community

Next steps

We strongly advise updating the component to the latest version.

If the update can't resolve the issue, create a plan to isolate or replace the affected component.

Problem

Software composition analysis has identified a component with one or more known vulnerabilities. Based on the CVSS scoring, these vulnerabilities have been marked as critical severity.

Prevalence in PyPI community

27 packages

found in

Top 100

156 packages

found in

Top 1k

1294 packages

found in

Top 10k

58.62k packages

in community

Next steps

45 (45 Fixable)

CVE-2016-9841c

CVE-2016-9843c

CVE-2018-1000007c

None

Exploits Unknown

Exploits Exist

Exploited by Malware

Patching Mandated

tensorflow-opt

SAFE Assessment

Compliance

Security

Threats

IMPORTANT: All versions of this package have been maliciousLatest version with malware incident detected: almost 4 years agoVersion: 0.40

INCIDENTS FOR THIS VERSION:

Popularity

Top issues

SQ30103Detected presence of potentially unwanted applications.Causes risk: undesirable applications foundthreats

Problem

Prevalence in PyPI community

Next steps

SQ30105Detected presence of known software supply chain attack artifacts.Causes risk: supply chain attack artifactsthreats

Problem

Prevalence in PyPI community

Next steps

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

Problem

Prevalence in PyPI community

Next steps

SQ31102Detected presence of severe vulnerabilities with active exploitation.Causes risk: actively exploited vulnerabilitiesvulnerabilities

Problem

Prevalence in PyPI community

Next steps

SQ31104Detected presence of critical severity vulnerabilities.Causes risk: critical severity vulnerabilitiesvulnerabilities

Problem

Prevalence in PyPI community

Next steps

Top behaviors

Deletes the value of a registry key.registry

Prevalence in PyPI community

Requests permission required to shut down a system.permissions

Prevalence in PyPI community

Deletes files in Windows system directories.file

Prevalence in PyPI community

Changes the value of a registry key.registry

Prevalence in PyPI community

Accesses the Event Log.monitor

Prevalence in PyPI community

Top vulnerabilities

FAQ for tensorflow-opt

What is tensorflow-opt?

Is tensorflow-opt malicious or is it safe to use?

Is tensorflow-opt popular?

How do I secure tensorflow-opt once it is in my app?

Did you know...

Popularity

Top issues

SQ30103Detected presence of potentially unwanted applications.Causes risk: undesirable applications foundthreats

Problem

Prevalence in PyPI community

Next steps

SQ30105Detected presence of known software supply chain attack artifacts.Causes risk: supply chain attack artifactsthreats

Problem

Prevalence in PyPI community

Next steps

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

Problem

Prevalence in PyPI community

Next steps

SQ31102Detected presence of severe vulnerabilities with active exploitation.Causes risk: actively exploited vulnerabilitiesvulnerabilities

Problem

Prevalence in PyPI community

Next steps

SQ31104Detected presence of critical severity vulnerabilities.Causes risk: critical severity vulnerabilitiesvulnerabilities

Problem

Prevalence in PyPI community

Next steps

Top behaviors

Deletes the value of a registry key.registry

Prevalence in PyPI community

Requests permission required to shut down a system.permissions

Prevalence in PyPI community

Deletes files in Windows system directories.file

Prevalence in PyPI community

Changes the value of a registry key.registry

Prevalence in PyPI community

Accesses the Event Log.monitor

Prevalence in PyPI community