Spectra Assure
Community
Docs
failIncident: Malware
Scanned: 4 days ago

aliyun-ai-labs-snippets-sdk

Artifact:
latest
malicious
AI Labs Snippets SDK for Python
License: Permissive (MIT)
Published: 6 months 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
3 malware-like behaviors found
Malware
4 supply chain attack artifacts

INCIDENTS FOR THIS VERSION:

malware
6 months agoReported By: ReversingLabs (Automated)
Learn more about malware detection
malware
6 months agoReported By: ReversingLabs (Researcher)
See more info on our blog
malware
5 months agoReported By: Community (OpenSSF)

Popularity

709
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

Proprietary ReversingLabs malware detection algorithms have determined that the software package contains one or more malicious files. The detection was made by a heuristic signature. This malware detection method is considered proactive, and can typically identify the malware family or at least the threat type.

Prevalence in PyPI community

4 packages
found in
Top 100
17 packages
found in
Top 1k
50 packages
found in
Top 10k
678 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

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 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.

Prevalence in PyPI community

0 packages
found in
Top 100
0 packages
found in
Top 1k
0 packages
found in
Top 10k
26 packages
in community

Next steps

Investigate reported detections.
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

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 infostealer malware profile. Infostealers are commonly used to steal sensitive user data such as stored login details, financial information, and other personally identifiable information.

Prevalence in PyPI community

0 packages
found in
Top 100
0 packages
found in
Top 1k
1 packages
found in
Top 10k
1960 packages
in community

Next steps

Investigate reported detections.
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.

Top behaviors

Prevalence in PyPI community

Behavior exclusively used by malicious software (Malicious)
Behavior uncommon for this community (Uncommon)
0 packages
found in
Top 100
0 packages
found in
Top 1k
2 packages
found in
Top 10k
5 packages
in community

Prevalence in PyPI community

Behavior commonly used by malicious software (Important)
Behavior uncommon for this community (Uncommon)
0 packages
found in
Top 100
4 packages
found in
Top 1k
11 packages
found in
Top 10k
454 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
39 packages
found in
Top 100
280 packages
found in
Top 1k
1754 packages
found in
Top 10k
67026 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
40 packages
found in
Top 100
253 packages
found in
Top 1k
1433 packages
found in
Top 10k
53416 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
68 packages
found in
Top 100
540 packages
found in
Top 1k
3644 packages
found in
Top 10k
154572 packages
in community

Top vulnerabilities

No vulnerabilities found.