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failIncident: Malware
Scanned: about 22 hours ago

discordpydebug

Artifact:
Discord py error logger
License: Permissive (MIT)
Published: over 3 years ago



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
No evidence of software tampering
Malware
3 supply chain attack artifacts

INCIDENTS FOR THIS VERSION:

malware
7 months agoReported By: Community (Socket)
malware
6 months agoReported By: ReversingLabs (Researcher)
See more info on our blog

Popularity

11.76k
Total Downloads
Contributor
Declared Dependencies
0
Dependents

Top issues

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 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

Prevalence in PyPI community

Behavior often found in this community (Common)
68 packages
found in
Top 100
508 packages
found in
Top 1k
3570 packages
found in
Top 10k
165477 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

No behavior prevalence information at this time

Prevalence in PyPI community

Behavior often found in this community (Common)
68 packages
found in
Top 100
585 packages
found in
Top 1k
4048 packages
found in
Top 10k
149289 packages
in community

Top vulnerabilities

No vulnerabilities found.