MAL-2026-17461
Vulnerability from ossf_malicious_packages
-= Per source details. Do not edit below this line.=-
Source: amazon-inspector (31bcd85c4464339b45ec445d1c402ecbc97ab4b50b71738d1fc3873c88f9cff5)
The package advertises text-to-speech inference but contains no model, audio, or inference code. Importing voxel_tts loads voxel_tts/harness.py, which instantiates a module-level Harness(); on run() it chmods and executes a bundled ~8MB ELF at voxel_tts/bin/voxel-core. The ELF is invoked with a JSON configuration matching the XMRig-family CPU mining schema (pools/user/pass/keepalive/tls, cpu.threads, cpu.mem-locked, cache-budget), and the pool-protocol key 'pools' is split across string concatenation to evade static scanners. The pool destination is reconstructed at runtime by base64-decoding two fragments ('MTg1LjE5NA==', 'MTc3LjI0OQ==') and joining them with '.', yielding 185.194.177.249:443. A 40MB cloudflared binary is also bundled at voxel_tts/bin/cloudflared and launched as 'cloudflared access tcp --hostname --url 127.0.0.1:' so that outbound mining traffic egresses through Cloudflare Access to an author-controlled hostname, hiding the real pool IP from host network logs; in-code comments acknowledge this is to avoid 'direct egress to the coordinator's own address'. In parallel, a _Progress helper emits synthetic 'model | step N/250000 loss=... tok/s=... lr=6e-5 ep=...' lines once per minute as a cover story to make the workload appear to be ML training. Net effect: installing and using this package runs a cryptominer on the installer's CPU, monetizing their compute for the author, while actively evading detection via destination obfuscation, tunneled egress, and a fabricated training-progress UI.
Source: kam193 (59ef2094ba4f759a0f896ff0af35b1fd19442db3cf8212a39fde46d5713c807d)
The package imitates real activity and instead deploys a coin miner.
Category: MALICIOUS - The campaign has clearly malicious intent, like infostealers.
Campaign: 2026-10-voxeval
Reasons (based on the campaign):
- cryptominer
{
"affected": [
{
"database_specific": {
"cwes": [
{
"cweId": "CWE-506",
"description": "The product contains code that appears to be malicious in nature.",
"name": "Embedded Malicious Code"
},
{
"cweId": "CWE-506",
"description": "The product contains code that appears to be malicious in nature.",
"name": "Embedded Malicious Code"
}
],
"indicators": {
"evidence_files": [
{
"path": "voxel_tts/harness.py",
"sha256": "2b3194f9bc979acbb8ff8c46243921727e112381611067feccfeb2e69f5dfc53",
"tlsh": "59d171f6ca161a62c397ca164a57b583630aac53974e04347cfc83183f95674c2f1efa"
}
],
"package_integrity": [
{
"filename": "voxel_tts-0.5.0-py3-none-any.whl",
"hashes": {
"blake2b_256": "585acec603109e61864a2debeb9141919d0ef679d11af14fd8cc4ff5281fd45d",
"md5": "cfde97d0e997b7815f849eeadd0d6e83",
"sha256": "84e93a0ac30511ea48e94cfc1bba4cf49339c60dfabf4760e34604629c32e65b"
}
}
]
}
},
"package": {
"ecosystem": "PyPI",
"name": "voxel-tts"
},
"versions": [
"0.5.0",
"0.5.1"
]
}
],
"credits": [
{
"contact": [
"inspector-research@amazon.com"
],
"name": "Amazon Inspector",
"type": "FINDER"
},
{
"contact": [
"https://github.com/kam193",
"https://bad-packages.kam193.eu/"
],
"name": "Kamil Ma\u0144kowski (kam193)",
"type": "REPORTER"
},
{
"contact": [
"https://github.com/kam193",
"https://bad-packages.kam193.eu/"
],
"name": "Kamil Ma\u0144kowski (kam193)",
"type": "ANALYST"
}
],
"database_specific": {
"malicious-packages-origins": [
{
"id": "pypi/2026-10-voxeval/voxel-tts",
"import_time": "2026-10-03T04:46:19.650415945Z",
"modified_time": "2026-10-03T04:38:14.625954Z",
"sha256": "59ef2094ba4f759a0f896ff0af35b1fd19442db3cf8212a39fde46d5713c807d",
"source": "kam193",
"versions": [
"0.5.0",
"0.5.1"
]
},
{
"id": "pypi/2026-10-voxeval/voxel-tts",
"import_time": "2026-10-03T05:18:10.337930449Z",
"modified_time": "2026-10-03T04:38:14.625954Z",
"sha256": "d20f098625fe215d12359a89c03cd967a584ccc37a111c8127ce4889166af61e",
"source": "kam193",
"versions": [
"0.5.0",
"0.5.1"
]
},
{
"id": "IN-MAL-2026-020925",
"import_time": "2026-10-04T23:40:42.599068067Z",
"modified_time": "2026-10-04T23:20:41Z",
"sha256": "31bcd85c4464339b45ec445d1c402ecbc97ab4b50b71738d1fc3873c88f9cff5",
"source": "amazon-inspector",
"versions": [
"0.5.0"
]
},
{
"id": "IN-MAL-2026-020927",
"import_time": "2026-10-04T23:40:42.825025391Z",
"modified_time": "2026-10-04T23:20:59Z",
"sha256": "598f8abf106d4dbdbbe4ce3aa3eca8d89b36b3a0d77d17f266849e46176e4913",
"source": "amazon-inspector",
"versions": [
"0.5.1"
]
}
]
},
"details": "\n---\n_-= Per source details. Do not edit below this line.=-_\n\n## Source: amazon-inspector (31bcd85c4464339b45ec445d1c402ecbc97ab4b50b71738d1fc3873c88f9cff5)\nThe package advertises text-to-speech inference but contains no model, audio, or inference code. Importing voxel_tts loads voxel_tts/harness.py, which instantiates a module-level Harness(); on run() it chmods and executes a bundled ~8MB ELF at voxel_tts/bin/voxel-core. The ELF is invoked with a JSON configuration matching the XMRig-family CPU mining schema (pools/user/pass/keepalive/tls, cpu.threads, cpu.mem-locked, cache-budget), and the pool-protocol key \u0027pools\u0027 is split across string concatenation to evade static scanners. The pool destination is reconstructed at runtime by base64-decoding two fragments (\u0027MTg1LjE5NA==\u0027, \u0027MTc3LjI0OQ==\u0027) and joining them with \u0027.\u0027, yielding 185.194.177.249:443. A 40MB cloudflared binary is also bundled at voxel_tts/bin/cloudflared and launched as \u0027cloudflared access tcp --hostname \u003chost\u003e --url 127.0.0.1:\u003cport\u003e\u0027 so that outbound mining traffic egresses through Cloudflare Access to an author-controlled hostname, hiding the real pool IP from host network logs; in-code comments acknowledge this is to avoid \u0027direct egress to the coordinator\u0027s own address\u0027. In parallel, a _Progress helper emits synthetic \u0027model | step N/250000 loss=... tok/s=... lr=6e-5 ep=...\u0027 lines once per minute as a cover story to make the workload appear to be ML training. Net effect: installing and using this package runs a cryptominer on the installer\u0027s CPU, monetizing their compute for the author, while actively evading detection via destination obfuscation, tunneled egress, and a fabricated training-progress UI.\n\n## Source: kam193 (59ef2094ba4f759a0f896ff0af35b1fd19442db3cf8212a39fde46d5713c807d)\nThe package imitates real activity and instead deploys a coin miner.\n\n\n---\n\nCategory: MALICIOUS - The campaign has clearly malicious intent, like infostealers.\n\n\nCampaign: 2026-10-voxeval\n\n\nReasons (based on the campaign):\n\n\n - cryptominer\n",
"id": "MAL-2026-17461",
"modified": "2026-10-04T23:42:41.654999682Z",
"published": "2026-10-03T04:38:14Z",
"references": [
{
"type": "WEB",
"url": "https://bad-packages.kam193.eu/pypi/package/voxel-tts"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/voxel-tts/0.5.0/"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/voxel-tts/0.5.1/"
}
],
"schema_version": "1.7.4",
"summary": "Malicious code in voxel-tts (PyPI)"
}
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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.
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