Spectra Assure

failIncident: Malware

Scanned:

prof-tg-gjho-qu

Artifact:

latest

removed

malicious

Research

نسخ صفقات من تيليجرام إلى منصة Quotex

License: unknown

Published:

See on PyPI

SAFE Assessment

Compliance

Licenses

No license compliance issues

Secrets

1 inactive web service credentials

Security

Vulnerabilities

No known vulnerabilities detected

Hardening

2 low priority mitigations absent

Threats

Tampering

2 malware-like behaviors found

Malware

3 supply chain attack artifacts

INCIDENTS FOR THIS VERSION:

removal

Reported By: Community

malware

Reported By: Community (OpenSSF)

More info

malware

Reported By: ReversingLabs (Researcher)

Learn more about malware detection

malware

N/AReported By: Community (kam193)

More info

Popularity

194

Total Downloads

Contributors

Declared Dependencies

Dependents

Top issues

See all 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

11 packages

found in

Top 10k

14.01k 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

10 packages

found in

Top 10k

14.02k 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. 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

3 packages

found in

Top 10k

2.05k 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 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. Open source projects are the intellectual property of their respective authors. At any time, the authors may choose to completely remove the software component from a public repository. This often occurs when a software project reaches its end-of-life stage, or when the software authors lose interest in maintaining the project. This kind of removal frees up the software package name, its unique software identifier in the public repository, for other developers to use. However, new software project owners might have malicious intent. Threat actors are continuously monitoring popular package names in case their unique identifiers suddenly become available for hijacking. Once the software projects falls under new ownership, the new maintainers may opt to use the project popularity to spread malware to unsuspecting users.

Prevalence in PyPI community

0 packages

found in

Top 100

1 packages

found in

Top 1k

20 packages

found in

Top 10k

83.87k 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.

Revise the use of components that raise these alarms. If you can't deprecate those components, make sure that their versions are pinned.

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

1 packages

found in

Top 100

13 packages

found in

Top 1k

37 packages

found in

Top 10k

443.06k packages

in community

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

See all behaviors

Prevalence in PyPI community

Behavior often found in this community (Common)

67 packages

found in

Top 100

525 packages

found in

Top 1k

4055 packages

found in

Top 10k

154.83k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

33 packages

found in

Top 100

225 packages

found in

Top 1k

1322 packages

found in

Top 10k

35.04k packages

in community

Prevalence in PyPI community

Behavior uncommon for this community (Uncommon)

1 packages

found in

Top 100

2 packages

found in

Top 1k

17 packages

found in

Top 10k

1.81k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

5 packages

found in

Top 100

17 packages

found in

Top 1k

144 packages

found in

Top 10k

6.26k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

13 packages

found in

Top 100

81 packages

found in

Top 1k

473 packages

found in

Top 10k

10.5k packages

in community

Top vulnerabilities

No vulnerabilities found.

FAQ for prof-tg-gjho-qu

What is prof-tg-gjho-qu?

نسخ صفقات من تيليجرام إلى منصة Quotex.

Is prof-tg-gjho-qu malicious or is it safe to use?

The Python package prof-tg-gjho-qu has been removed from registry. It was scanned for malware, software tampering, risky behaviors, exposed secrets and known vulnerabilities. Malware or tampering has been detected, making it unsafe to use. 2 other issues and risky behaviors were found. The package contains risks, and the analysis results should be reviewed before it is used. Visit the Issues and Behaviors sections of the analysis for more details. All versions of the prof-tg-gjho-qu package were malicious.

Is prof-tg-gjho-qu popular?

The Python package prof-tg-gjho-qu is not widely used. It has 194 recorded downloads. A package's popularity is not a good indicator of its safety, visit the SAFE Assessment section to see the full analysis of package deployment risk categories.

How do I secure prof-tg-gjho-qu once it is in my app?

Since we can't know when or where malicious attacks will happen, we recommend tracking how prof-tg-gjho-qu behaviors change over multiple software releases. By adopting differential analysis in your release process, you can detect unexpected changes to a prof-tg-gjho-qu version, which can prevent advanced software supply chain attacks. Read how our technology can help prevent future attacks similar to SolarWinds and 3CX.

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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Popularity

194

Total Downloads

Contributors

Declared Dependencies

Dependents

Top issues

See all issues

Problem

Prevalence in PyPI community

0 packages

found in

Top 100

0 packages

found in

Top 1k

11 packages

found in

Top 10k

14.01k 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

Prevalence in PyPI community

0 packages

found in

Top 100

0 packages

found in

Top 1k

10 packages

found in

Top 10k

14.02k packages

in community

Next steps

Investigate the build and release environment for software supply chain compromise.

Avoid using this software package.

Problem

Prevalence in PyPI community

0 packages

found in

Top 100

0 packages

found in

Top 1k

3 packages

found in

Top 10k

2.05k 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

Prevalence in PyPI community

0 packages

found in

Top 100

1 packages

found in

Top 1k

20 packages

found in

Top 10k

83.87k 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.

Revise the use of components that raise these alarms. If you can't deprecate those components, make sure that their versions are pinned.

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

1 packages

found in

Top 100

13 packages

found in

Top 1k

37 packages

found in

Top 10k

443.06k packages

in community

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

See all behaviors

Prevalence in PyPI community

Behavior often found in this community (Common)

67 packages

found in

Top 100

525 packages

found in

Top 1k

4055 packages

found in

Top 10k

154.83k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

33 packages

found in

Top 100

225 packages

found in

Top 1k

1322 packages

found in

Top 10k

35.04k packages

in community

Prevalence in PyPI community

Behavior uncommon for this community (Uncommon)

1 packages

found in

Top 100

2 packages

found in

Top 1k

17 packages

found in

Top 10k

1.81k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

5 packages

found in

Top 100

17 packages

found in

Top 1k

144 packages

found in

Top 10k

6.26k packages

in community

Prevalence in PyPI community

Behavior often found in this community (Common)

13 packages

found in

Top 100

81 packages

found in

Top 1k

473 packages

found in

Top 10k

10.5k packages

in community

Top vulnerabilities

No vulnerabilities found.

prof-tg-gjho-qu

SAFE Assessment

Compliance

Security

Threats

IMPORTANT: All versions of this package have been maliciousLatest version with malware incident detected: 10 months agoVersion: 0.0.1

INCIDENTS FOR THIS VERSION:

Popularity

Top issues

SQ30105Detected presence of known software supply chain attack artifacts.Causes risk: supply chain attack artifactsthreats

Problem

Prevalence in PyPI community

Next steps

SQ30109Detected presence of malicious files through analyst-vetted file reputation.Causes risk: analyst-vetted malware foundthreats

Problem

Prevalence in PyPI community

Next steps

TH15108Detected presence of files with behaviors that match the infostealer malware profile.Causes risk: malware-like behaviors foundhunting

Problem

Prevalence in PyPI community

Next steps

TH30103Detected presence of software components that were removed from the public package repository.Causes risk: components prone to hijackinghunting

Problem

Prevalence in PyPI community

Next steps

TH30106Detected presence of software components that have low popularity or number of downloads.hunting

Problem

Prevalence in PyPI community

Next steps

Top behaviors

Contains IP addresses.network

Prevalence in PyPI community

Contains URLs.network

Prevalence in PyPI community

Contains URLs related to the Telegram API.network

Prevalence in PyPI community

Contains URLs related to messaging services.network

Prevalence in PyPI community

Modifies file/directory attributes.file

Prevalence in PyPI community

Top vulnerabilities

FAQ for prof-tg-gjho-qu

What is prof-tg-gjho-qu?

Is prof-tg-gjho-qu malicious or is it safe to use?

Is prof-tg-gjho-qu popular?

How do I secure prof-tg-gjho-qu once it is in my app?

Did you know...

Popularity

Top issues

SQ30105Detected presence of known software supply chain attack artifacts.Causes risk: supply chain attack artifactsthreats

Problem

Prevalence in PyPI community

Next steps

SQ30109Detected presence of malicious files through analyst-vetted file reputation.Causes risk: analyst-vetted malware foundthreats

Problem

Prevalence in PyPI community

Next steps

TH15108Detected presence of files with behaviors that match the infostealer malware profile.Causes risk: malware-like behaviors foundhunting

Problem

Prevalence in PyPI community

Next steps

TH30103Detected presence of software components that were removed from the public package repository.Causes risk: components prone to hijackinghunting

Problem

Prevalence in PyPI community

Next steps

TH30106Detected presence of software components that have low popularity or number of downloads.hunting

Problem

Prevalence in PyPI community

Next steps

Top behaviors

Contains IP addresses.network

Prevalence in PyPI community

Contains URLs.network

Prevalence in PyPI community

Contains URLs related to the Telegram API.network

Prevalence in PyPI community

Contains URLs related to messaging services.network

Prevalence in PyPI community

Modifies file/directory attributes.file

Prevalence in PyPI community