Spectra Assure

failIncident: Malware

Scanned:

requests-toolkit

Artifact:

latest

malicious

Extensions for Requests

License: unknown

New!

Published:

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See on PyPI

SAFE Assessment

Compliance

Licenses

1 weak copyleft linked components

Secrets

1 active web service credentials

Security

Vulnerabilities

1 severe vulnerabilities exploited

Hardening

1 baseline mitigations missing

Threats

Tampering

No evidence of software tampering

Malware

1 malicious components found

INCIDENTS FOR THIS VERSION:

malware

Reported By: ReversingLabs (Automated)

Learn more about malware detection

List of software quality issues with the number of affected components.

Policies

Info

Problem

Proprietary ReversingLabs malware detection algorithms have determined that the software package contains one or more malicious files. The detection was made by a machine learning model. This malware detection method is considered proactive, and can typically identify the malware threat type. 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 components to be detected as malicious.

Prevalence in PyPI community

0 packages

found in

Top 100

2 packages

found in

Top 1k

10 packages

found in

Top 10k

328 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.

Avoid using this software package until it is vetted as safe.

Consider rewriting code that may have triggered the detection due to its malware similarity.

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

Perform impact analysis for the reported CVEs.

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 as a Service (SaaS) platforms expose programmable interfaces to their authenticated users. These web services enable action automation and secure exchange of information. For authorization, users provide a unique token that confirms their access rights to the web service. Access tokens for supported web services are automatically validated via the least privilege APIs the service exposes. Detected tokens have been accepted as valid by the services they are associated with. This indicates they are currently active and may be abused if exposed to the public. Web service access tokens are considered secrets. They should never be included in a software release package, even if they are obfuscated by encryption on the client-side.

Prevalence in PyPI community

0 packages

found in

Top 100

0 packages

found in

Top 1k

2 packages

found in

Top 10k

248 packages

in community

Next steps

You should securely store web service access tokens, and fully automate their management and periodic rotation.

If tokens were published unintentionally and the software has been made public, you should revoke exposed tokens and file a security incident.

Examples of service tokens that may have been detected include AWS, Facebook, JWT, SWT, Slack and others.

Problem

Data Execution Prevention (DEP/NX) is a vulnerability mitigation option that prevents data from being interpreted as code anywhere within the application. This mitigation protects the application stack, heap and other memory data ranges. Executable files that fail to implement this mitigation expose the user to increased risks of malicious code injection.

Prevalence in PyPI community

23 packages

found in

Top 100

96 packages

found in

Top 1k

422 packages

found in

Top 10k

5.91k packages

in community

Next steps

It's highly recommended to enable this option for all software components used at security boundaries, or those that process user controlled inputs.

To enable this mitigation, refer to your programming language linker documentation.

In Microsoft VisualStudio, you can enable DEP mitigation by setting the linker option /NXCOMPAT to ON.

Problem

Security Development Lifecycle (SDL) is a group of enhanced compile-time checks that report common coding mistakes as errors. These checks prevent the use of hard-to-secure string manipulation functions. They enforce static memory access checks, and allow only the use of range-verified string parsing functions. While these checks do not prevent every memory corruption issue by themselves, they do help reduce the likelihood.

Prevalence in PyPI community

10 packages

found in

Top 100

45 packages

found in

Top 1k

247 packages

found in

Top 10k

4.13k packages

in community

Next steps

It's highly recommended to enable these checks for all software components used at security boundaries, or those that process user controlled inputs.

To enable these checks, refer to your programming language toolchain documentation.

In Microsoft VisualStudio, you can enable this feature by setting the compiler option /SDL to ON.

Problem

Sensitive executable memory regions should be kept as read-only to protect the integrity of trusted execution code flow paths. Imported function addresses are pointers to the symbols that implement the application-required functionality. If those pointers are changed by malicious code, execution paths can be redirected to unintended locations. Most modern programming language toolchains protect those memory regions appropriately. These issues are commonly reported for outdated linkers and non-compliant executable packing solutions.

Prevalence in PyPI community

15 packages

found in

Top 100

29 packages

found in

Top 1k

165 packages

found in

Top 10k

3.83k packages

in community

Next steps

Review the programming language linker options, and consider a build toolchain update.

Problem

Sensitive executable memory regions should be kept as read-only to protect the integrity of trusted execution code flow paths. Thread local storage (TLS) callbacks are pointers to code initialization and resource release functions. If those pointers are changed by malicious code, execution paths can be redirected to unintended locations. Most modern programming language toolchains protect those memory regions appropriately. These issues are commonly reported for outdated linkers and non-compliant executable packing solutions.

Prevalence in PyPI community

7 packages

found in

Top 100

16 packages

found in

Top 1k

121 packages

found in

Top 10k

3.03k packages

in community

Next steps

Review the programming language linker options, and consider a build toolchain update.

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 high severity.

Prevalence in PyPI community

42 packages

found in

Top 100

278 packages

found in

Top 1k

1960 packages

found in

Top 10k

77.08k packages

in community

Next steps

Perform impact analysis for the reported CVEs.

Update 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

Uniform Resource Locators (URLs) are structured addresses that point to locations and assets on the internet. URLs allow software developers to build complex applications that exchange data with servers that can be hosted in multiple geographical regions. URLs can commonly be found embedded in documentation, configuration files, source code and compiled binaries. One or more embedded URLs were discovered to link to raw files hosted on GitHub. Attackers often abuse popular web services to host malicious payloads. Since code-sharing services URLs are typically allowed by security solutions, using them for payload delivery increases the odds that the malicious code will reach the user. While the presence of code-sharing service locations does not imply malicious intent, all of their uses in a software package should be documented and approved. An increasing number of software supply chain attacks in the open source space leverages the GitHub service to deliver malicious payloads.

Prevalence in PyPI community

36 packages

found in

Top 100

219 packages

found in

Top 1k

1678 packages

found in

Top 10k

63.41k 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 an alternative delivery mechanism for software packages.

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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List of software quality issues with the number of affected components.

Policies

Info

Problem

Prevalence in PyPI community

0 packages

found in

Top 100

2 packages

found in

Top 1k

10 packages

found in

Top 10k

328 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.

Avoid using this software package until it is vetted as safe.

Consider rewriting code that may have triggered the detection due to its malware similarity.

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

Perform impact analysis for the reported CVEs.

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

Prevalence in PyPI community

0 packages

found in

Top 100

0 packages

found in

Top 1k

2 packages

found in

Top 10k

248 packages

in community

Next steps

You should securely store web service access tokens, and fully automate their management and periodic rotation.

If tokens were published unintentionally and the software has been made public, you should revoke exposed tokens and file a security incident.

Examples of service tokens that may have been detected include AWS, Facebook, JWT, SWT, Slack and others.

Problem

Prevalence in PyPI community

23 packages

found in

Top 100

96 packages

found in

Top 1k

422 packages

found in

Top 10k

5.91k packages

in community

Next steps

It's highly recommended to enable this option for all software components used at security boundaries, or those that process user controlled inputs.

To enable this mitigation, refer to your programming language linker documentation.

In Microsoft VisualStudio, you can enable DEP mitigation by setting the linker option /NXCOMPAT to ON.

Problem

Prevalence in PyPI community

10 packages

found in

Top 100

45 packages

found in

Top 1k

247 packages

found in

Top 10k

4.13k packages

in community

Next steps

It's highly recommended to enable these checks for all software components used at security boundaries, or those that process user controlled inputs.

To enable these checks, refer to your programming language toolchain documentation.

In Microsoft VisualStudio, you can enable this feature by setting the compiler option /SDL to ON.

Problem

Prevalence in PyPI community

15 packages

found in

Top 100

29 packages

found in

Top 1k

165 packages

found in

Top 10k

3.83k packages

in community

Next steps

Review the programming language linker options, and consider a build toolchain update.

Problem

Prevalence in PyPI community

7 packages

found in

Top 100

16 packages

found in

Top 1k

121 packages

found in

Top 10k

3.03k packages

in community

Next steps

Review the programming language linker options, and consider a build toolchain update.

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 high severity.

Prevalence in PyPI community

42 packages

found in

Top 100

278 packages

found in

Top 1k

1960 packages

found in

Top 10k

77.08k packages

in community

Next steps

Perform impact analysis for the reported CVEs.

Update 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

Prevalence in PyPI community

36 packages

found in

Top 100

219 packages

found in

Top 1k

1678 packages

found in

Top 10k

63.41k 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 an alternative delivery mechanism for software packages.

requests-toolkit

SAFE Assessment

Compliance

Security

Threats

IMPORTANT: This package had 2 malicious incidents in versions published within 2 years prior to the latestLatest version with malware incident detected: about 5 hours agoVersion: 0.1.3

INCIDENTS FOR THIS VERSION:

SQ30108Detected presence of malicious files by a machine learning algorithm.Causes risk: malicious components 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

SQ34401Detected presence of active web service tokens.Causes risk: active web service credentialssecrets

Problem

Prevalence in PyPI community

Next steps

SQ14102Detected Windows executable files that do not implement the DEP vulnerability mitigation protection.Causes risk: baseline mitigations missinghardening

Problem

Prevalence in PyPI community

Next steps

SQ14140Detected Windows executable files compiled without following the SDL best practices while using banned string functions.Causes risk: misconfigured toolchains detectedhardening

Problem

Prevalence in PyPI community

Next steps

SQ14156Detected Windows executable files with imported functions susceptible to pointer hijacking.Causes risk: execution hijacking concernshardening

Problem

Prevalence in PyPI community

Next steps

SQ14158Detected Windows executable files with TLS callbacks susceptible to pointer hijacking.Causes risk: execution hijacking concernshardening

Problem

Prevalence in PyPI community

Next steps

SQ31105Detected presence of high severity vulnerabilities.Causes risk: high severity vulnerabilitiesvulnerabilities

Problem

Prevalence in PyPI community

Next steps

TH17127Detected presence of files containing URLs that link to raw files on GitHub.hunting

Problem

Prevalence in PyPI community

Next steps

Did you know...

SQ30108Detected presence of malicious files by a machine learning algorithm.Causes risk: malicious components 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

SQ34401Detected presence of active web service tokens.Causes risk: active web service credentialssecrets

Problem

Prevalence in PyPI community

Next steps

SQ14102Detected Windows executable files that do not implement the DEP vulnerability mitigation protection.Causes risk: baseline mitigations missinghardening

Problem

Prevalence in PyPI community

Next steps

SQ14140Detected Windows executable files compiled without following the SDL best practices while using banned string functions.Causes risk: misconfigured toolchains detectedhardening

Problem

Prevalence in PyPI community

Next steps

SQ14156Detected Windows executable files with imported functions susceptible to pointer hijacking.Causes risk: execution hijacking concernshardening

Problem

Prevalence in PyPI community

Next steps

SQ14158Detected Windows executable files with TLS callbacks susceptible to pointer hijacking.Causes risk: execution hijacking concernshardening

Problem

Prevalence in PyPI community

Next steps