MAL-2026-17417
Vulnerability from ossf_malicious_packages
Published
2026-09-30 19:15
Modified
2026-09-30 19:15
Summary
Malicious code in beautifytext (PyPI)
Details
-= Per source details. Do not edit below this line.=-
Source: kam193 (cba19cfc0b2bdeec177fafdffa10e730769079a14ece3bb4740bfc0ded9fef3b)
During import, the package silently spans a separate process that waits for and executes remote commands.
Category: MALICIOUS - The campaign has clearly malicious intent, like infostealers.
Campaign: 2026-07-beautifytext
Reasons (based on the campaign):
-
rat
-
The package contains code to execute remote commands (probably limited to a specific set) on the victim's machine.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "beautifytext"
},
"versions": [
"1.0.3",
"1.0.4",
"1.0.7"
]
}
],
"credits": [
{
"contact": [
"https://github.com/kam193",
"https://bad-packages.kam193.eu/"
],
"name": "Kamil Ma\u0144kowski (kam193)",
"type": "REPORTER"
}
],
"database_specific": {
"iocs": {
"domains": [
"bleood.wisp.uno"
]
},
"malicious-packages-origins": [
{
"id": "pypi/2026-07-beautifytext/beautifytext",
"import_time": "2026-09-30T19:40:14.775642175Z",
"modified_time": "2026-09-30T19:15:23.492694Z",
"sha256": "cba19cfc0b2bdeec177fafdffa10e730769079a14ece3bb4740bfc0ded9fef3b",
"source": "kam193",
"versions": [
"1.0.3",
"1.0.4",
"1.0.7"
]
}
]
},
"details": "\n---\n_-= Per source details. Do not edit below this line.=-_\n\n## Source: kam193 (cba19cfc0b2bdeec177fafdffa10e730769079a14ece3bb4740bfc0ded9fef3b)\nDuring import, the package silently spans a separate process that waits for and executes remote commands.\n\n\n---\n\nCategory: MALICIOUS - The campaign has clearly malicious intent, like infostealers.\n\n\nCampaign: 2026-07-beautifytext\n\n\nReasons (based on the campaign):\n\n\n - rat\n\n\n - The package contains code to execute remote commands (probably limited to a specific set) on the victim\u0027s machine.\n",
"id": "MAL-2026-17417",
"modified": "2026-09-30T19:15:23Z",
"published": "2026-09-30T19:15:23Z",
"references": [
{
"type": "WEB",
"url": "https://bad-packages.kam193.eu/pypi/package/beautifytext"
}
],
"schema_version": "1.7.4",
"summary": "Malicious code in beautifytext (PyPI)"
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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