MAL-2025-192891
Vulnerability from ossf_malicious_packages
Published
2025-12-23 08:38
Modified
2025-12-23 08:38
Summary
Malicious code in blastchamber-python-pypi (PyPI)
Details
-= Per source details. Do not edit below this line.=-
Credits
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "blastchamber-python-pypi",
"purl": "pkg:pypi/blastchamber-python-pypi"
},
"versions": [
"0.0.4",
"0.1.0",
"0.2.0",
"0.2.2"
]
}
],
"credits": [
{
"contact": [
"https://www.reversinglabs.com"
],
"name": "ReversingLabs",
"type": "FINDER"
}
],
"database_specific": {
"malicious-packages-origins": [
{
"id": "RLMA-2025-06555",
"import_time": "2025-12-24T10:07:30.233748445Z",
"modified_time": "2025-12-23T08:38:03Z",
"sha256": "2c7eb8338cd27ff8b5034d39ee52ef1540c025589e08299a7346234598d46604",
"source": "reversing-labs",
"versions": [
"0.0.4",
"0.1.0",
"0.2.0",
"0.2.2"
]
}
]
},
"details": "\n---\n_-= Per source details. Do not edit below this line.=-_\n",
"id": "MAL-2025-192891",
"modified": "2025-12-23T08:38:03Z",
"published": "2025-12-23T08:38:03Z",
"schema_version": "1.7.4",
"summary": "Malicious code in blastchamber-python-pypi (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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