Vulnerability-Lookup

MAL-2026-17200

Vulnerability from ossf_malicious_packages

Published

2026-09-27 14:15

Modified

2026-09-27 14:15

Summary

Malicious code in aseity (PyPI)

Details

-= Per source details. Do not edit below this line.=-

Source: kam193 (cf65ea5c0fe1eeef9f47a75d65e291a715094076714694247ad03714eabc53ca)

During installation, obfuscated code is used to fetch code hidden in an image containing a Python application with a native extension module. This module holds an obfuscated infostealer which collects sensitive data and exfiltrates them to a C2 server retrieved from transaction history in the Polygon blockchain.

Category: MALICIOUS - The campaign has clearly malicious intent, like infostealers.

Campaign: 2026-09-donutautosellsrc

Reasons (based on the campaign):

infostealer
Downloads and executes a remote executable.
obfuscation
malware
native-extension
steganography
c2-in-blockchain
The package contains code to detect if it is running in a sandbox environment.

Credits

Kamil Mańkowski (kam193) github.com/kam193 bad-packages.kam193.eu/

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "aseity"
      },
      "versions": [
        "0.1.0"
      ]
    }
  ],
  "credits": [
    {
      "contact": [
        "https://github.com/kam193",
        "https://bad-packages.kam193.eu/"
      ],
      "name": "Kamil Ma\u0144kowski (kam193)",
      "type": "REPORTER"
    }
  ],
  "database_specific": {
    "iocs": {
      "domains": [
        "thisisafalsepositive.st",
        "sltnnt.ru"
      ],
      "urls": [
        "https://thisisafalsepositive.st/cdn/v2/9f4e7a2c1b8d.png",
        "https://thisisafalsepositive.st/cdn/v2/promotion/manifest.json"
      ]
    },
    "malicious-packages-origins": [
      {
        "id": "pypi/2026-09-donutautosellsrc/aseity",
        "import_time": "2026-09-27T15:16:24.602624157Z",
        "modified_time": "2026-09-27T14:15:46.125923Z",
        "sha256": "cf65ea5c0fe1eeef9f47a75d65e291a715094076714694247ad03714eabc53ca",
        "source": "kam193",
        "versions": [
          "0.1.0"
        ]
      }
    ]
  },
  "details": "\n---\n_-= Per source details. Do not edit below this line.=-_\n\n## Source: kam193 (cf65ea5c0fe1eeef9f47a75d65e291a715094076714694247ad03714eabc53ca)\nDuring installation, obfuscated code is used to fetch code hidden in an image containing a Python application with a native extension module. This module holds an obfuscated infostealer which collects sensitive data and exfiltrates them to a C2 server retrieved from transaction history in the Polygon blockchain.\n\n\n---\n\nCategory: MALICIOUS - The campaign has clearly malicious intent, like infostealers.\n\n\nCampaign: 2026-09-donutautosellsrc\n\n\nReasons (based on the campaign):\n\n\n - infostealer\n\n\n - Downloads and executes a remote executable.\n\n\n - obfuscation\n\n\n - malware\n\n\n - native-extension\n\n\n - steganography\n\n\n - c2-in-blockchain\n\n\n - The package contains code to detect if it is running in a sandbox environment.\n",
  "id": "MAL-2026-17200",
  "modified": "2026-09-27T14:15:46Z",
  "published": "2026-09-27T14:15:46Z",
  "references": [
    {
      "type": "EVIDENCE",
      "url": "https://www.virustotal.com/gui/file/d03c42c275f0dbc617428441508c49ae1adcbbc95af4eeb094bca4e4f8943f3e/detection"
    },
    {
      "type": "WEB",
      "url": "https://polygonscan.com/address/0x9c0a507300fd902787bb193d80fca5ce6e1bff9a"
    },
    {
      "type": "WEB",
      "url": "https://bad-packages.kam193.eu/pypi/package/aseity"
    }
  ],
  "schema_version": "1.7.4",
  "summary": "Malicious code in aseity (PyPI)"
}

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.

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.

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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