PYSEC-2026-3734
Vulnerability from pysec - Published: 2026-08-25 02:16 - Updated: 2026-09-01 08:54
VLAI
Details
NLTK before 3.10.0 (affected versions <=3.9.4) contains an unsafe pickle deserialization vulnerability in the TransitionParser.parse() method (nltk/parse/transitionparser.py). The method calls pickle_load() with the default restricted=False, routing deserialization through WarningUnpickler, which does not override find_class() and therefore permits arbitrary class resolution. When an application loads an attacker-crafted model file, embedded pickle gadget chains execute arbitrary Python code with the privileges of the user running the application. NLTK provides a RestrictedUnpickler for safe deserialization, but it is not used by production code paths. Fixed in 3.10.0.
Severity
Impacted products
| Name | purl | nltk | pkg:pypi/nltk |
|---|
Aliases
{
"affected": [
{
"ecosystem_specific": {},
"package": {
"ecosystem": "PyPI",
"name": "nltk",
"purl": "pkg:pypi/nltk"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "3.10.0"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.8",
"0.9",
"0.9.3",
"0.9.4",
"0.9.5",
"0.9.6",
"0.9.7",
"0.9.8",
"0.9.9",
"2.0.1",
"2.0.1rc1",
"2.0.1rc2-git",
"2.0.1rc3",
"2.0.1rc4",
"2.0.2",
"2.0.3",
"2.0.4",
"2.0.5",
"2.0b4",
"2.0b5",
"2.0b6",
"2.0b7",
"2.0b8",
"2.0b9",
"3.0.0",
"3.0.0b1",
"3.0.0b2",
"3.0.1",
"3.0.2",
"3.0.3",
"3.0.4",
"3.0.5",
"3.1",
"3.2",
"3.2.1",
"3.2.2",
"3.2.3",
"3.2.4",
"3.2.5",
"3.3",
"3.4",
"3.4.1",
"3.4.2",
"3.4.3",
"3.4.4",
"3.4.5",
"3.5",
"3.5b1",
"3.6",
"3.6.1",
"3.6.2",
"3.6.3",
"3.6.4",
"3.6.5",
"3.6.6",
"3.6.7",
"3.7",
"3.8",
"3.8.1",
"3.9",
"3.9.1",
"3.9.2",
"3.9.3",
"3.9.4",
"3.9b1"
]
}
],
"aliases": [
"CVE-2026-78683",
"GHSA-rhp5-r9x4-f5g2"
],
"details": "NLTK before 3.10.0 (affected versions \u003c=3.9.4) contains an unsafe pickle deserialization vulnerability in the TransitionParser.parse() method (nltk/parse/transitionparser.py). The method calls pickle_load() with the default restricted=False, routing deserialization through WarningUnpickler, which does not override find_class() and therefore permits arbitrary class resolution. When an application loads an attacker-crafted model file, embedded pickle gadget chains execute arbitrary Python code with the privileges of the user running the application. NLTK provides a RestrictedUnpickler for safe deserialization, but it is not used by production code paths. Fixed in 3.10.0.",
"id": "PYSEC-2026-3734",
"modified": "2026-09-01T08:54:51.968743Z",
"published": "2026-08-25T02:16:53.033Z",
"references": [
{
"type": "ADVISORY",
"url": "https://www.vulncheck.com/advisories/nltk-before-remote-code-execution-via-unsafe-pickle-deserialization"
},
{
"type": "EVIDENCE",
"url": "https://github.com/nltk/nltk/security/advisories/GHSA-rhp5-r9x4-f5g2"
}
],
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
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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.
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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