Spectra Assure
Community
Docs
warningRisk: Tampering
Scanned: 4 days ago

pulsecord

Artifact:
latest
Helper
License: Permissive (MIT)
New!
Published: 4 days 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
1 suspicious application behaviors
Malware
No evidence of malware inclusion

Popularity

269
Total Downloads
Contributors
Declared Dependencies
0
Dependents

Top issues

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. Python Package Index (PyPI) repository is often abused by threat actors to publish software packages that exhibit malicious behaviors. Malware authors use numerous tactics to lure developers into including malicious PyPI packages in their software projects. Most malicious packages published on PyPI target developers and their workstations. However, some are designed to activate only when deployed in the end-user environment. Both types of Python malicious packages are detected by proprietary ReversingLabs threat hunting algorithms. This detection method is considered proactive, and it is based on Machine Learning (ML) algorithms that can detect novel malware. 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 software packages to be detected by this policy.

Prevalence in PyPI community

47 packages
found in
Top 100
226 packages
found in
Top 1k
1735 packages
found in
Top 10k
74797 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, or until the issue is risk accepted.
Consider rewriting the flagged code without using the marked behaviors.

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 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 commonly abused by malicious software with the intent to cause harm. When a software package shares behavior traits with malicious software, it may become flagged by security solutions. Any detection from security solutions can cause friction for the end-users during software deployment. While the behavior is likely intended by the developer, there is a small chance this detection is true positive, and an early indication of a software supply chain attack.

Prevalence in PyPI community

0 packages
found in
Top 100
2 packages
found in
Top 1k
7 packages
found in
Top 10k
1009 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, or until the issue is risk accepted.
Consider rewriting the flagged code without using the marked behaviors.

Problem

Attackers commonly hide their malicious payloads in layers of packing and code obfuscation. Base-encoding is a common data transformation technique used to convert binary payloads into text. Detected software behaviors indicate that the code has the ability to decode and execute Base-encoded data. While presence of dynamic code execution does not imply malicious intent, all of its uses in a software package should be documented and approved. When a software package has behavior traits similar to malicious software, it may become flagged by security solutions. One example of acceptable use for dynamic Base-encoded data execution is transfer of software components over the network.

Prevalence in PyPI community

1 packages
found in
Top 100
5 packages
found in
Top 1k
19 packages
found in
Top 10k
6125 packages
in community

Next steps

Investigate reported detections as indicators of software tampering.
Consult Mitre ATT&CK documentation: T1027 - Obfuscated Files or Information.
Consider rewriting the flagged code without using the marked behaviors.

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.

Top behaviors

Prevalence in PyPI community

Behavior commonly used by malicious software (Important)
Behavior uncommon for this community (Uncommon)
1 packages
found in
Top 100
2 packages
found in
Top 1k
9 packages
found in
Top 10k
5667 packages
in community

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)
12 packages
found in
Top 100
40 packages
found in
Top 1k
255 packages
found in
Top 10k
14296 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)
25 packages
found in
Top 100
205 packages
found in
Top 1k
1070 packages
found in
Top 10k
28156 packages
in community

Top vulnerabilities

No vulnerabilities found.