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failIncident: Malware
Scanned: 8 days ago

soopsocks

Artifact:
latest
malicious
SOCKS5 server with Discord egress + Windows auto-start (service or scheduled task)
License: Permissive (MIT)
Published: 2 months ago



SAFE Assessment

Compliance

Licenses
No license compliance issues
Secrets
No sensitive information found

Security

Vulnerabilities
1 severe vulnerabilities exploited
Hardening
1 modern mitigations missing

Threats

Tampering
2 malware-like behaviors found
Malware
3 supply chain attack artifacts

INCIDENTS FOR THIS VERSION:

malware
2 months agoReported By: Community (JFrog)
malware
2 months agoReported By: ReversingLabs (Researcher)
Learn more about malware detection
List of software quality issues with the number of affected components.
Policies
Info
Count
Category

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
5 packages
found in
Top 10k
13913 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
7 packages
found in
Top 10k
13959 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

38 packages
found in
Top 100
303 packages
found in
Top 1k
2611 packages
found in
Top 10k
103184 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. Available threat intelligence telemetry has confirmed that the reported vulnerabilities are actively being exploited by malicious actors. Malware code that propagates through these vulnerabilities has been created. This increases the chance of automated malware attacks affecting the software component users.

Prevalence in PyPI community

10 packages
found in
Top 100
78 packages
found in
Top 1k
751 packages
found in
Top 10k
27887 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

25 packages
found in
Top 100
212 packages
found in
Top 1k
1951 packages
found in
Top 10k
77976 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 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 backdoor malware profile. Backdoors are commonly used by malicious actors to gain unauthorized access to exposed computer systems over the internet. However, due to high-privilege access requirements, some security solutions may also trigger this detection when analyzed.

Prevalence in PyPI community

0 packages
found in
Top 100
0 packages
found in
Top 1k
1 packages
found in
Top 10k
183 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.
In the case this behavior is intended, rewrite the flagged code without using the malware-like behaviors.

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

14 packages
found in
Top 100
22 packages
found in
Top 1k
138 packages
found in
Top 10k
3863 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

50 packages
found in
Top 100
352 packages
found in
Top 1k
2858 packages
found in
Top 10k
108771 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

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 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.