GHSA-QPXX-2CWH-R5VH
Vulnerability from github – Published: 2025-05-26 09:30 – Updated: 2025-06-04 21:04
VLAI
Summary
pypickle Incorrect Privilege Assignment vulnerability
Details
A vulnerability was found in erdogant pypickle up to 1.1.5. It has been classified as critical. This affects the function Save of the file pypickle/pypickle.py. The manipulation leads to improper authorization. Attacking locally is a requirement. The exploit has been disclosed to the public and may be used. Upgrading to version 2.0.0 is able to address this issue. The patch is named 14b4cae704a0bb4eb6723e238f25382d847a1917. It is recommended to upgrade the affected component.
Severity
5.3 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "pypickle"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.0.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-5175"
],
"database_specific": {
"cwe_ids": [
"CWE-266"
],
"github_reviewed": true,
"github_reviewed_at": "2025-05-27T19:54:23Z",
"nvd_published_at": "2025-05-26T08:15:19Z",
"severity": "MODERATE"
},
"details": "A vulnerability was found in erdogant pypickle up to 1.1.5. It has been classified as critical. This affects the function Save of the file pypickle/pypickle.py. The manipulation leads to improper authorization. Attacking locally is a requirement. The exploit has been disclosed to the public and may be used. Upgrading to version 2.0.0 is able to address this issue. The patch is named 14b4cae704a0bb4eb6723e238f25382d847a1917. It is recommended to upgrade the affected component.",
"id": "GHSA-qpxx-2cwh-r5vh",
"modified": "2025-06-04T21:04:25Z",
"published": "2025-05-26T09:30:45Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-5175"
},
{
"type": "WEB",
"url": "https://github.com/erdogant/pypickle/issues/3"
},
{
"type": "WEB",
"url": "https://github.com/erdogant/pypickle/issues/3#issue-3070689116"
},
{
"type": "WEB",
"url": "https://github.com/erdogant/pypickle/issues/3#issuecomment-2888589652"
},
{
"type": "WEB",
"url": "https://github.com/erdogant/pypickle/commit/14b4cae704a0bb4eb6723e238f25382d847a1917"
},
{
"type": "WEB",
"url": "https://github.com/PrinceRaj-0/Vulnerability-Disclosure/blob/main/CVE-2025-5175.md"
},
{
"type": "PACKAGE",
"url": "https://github.com/erdogant/pypickle"
},
{
"type": "WEB",
"url": "https://github.com/erdogant/pypickle/releases/tag/2.0.0"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/pypickle/PYSEC-2025-46.yaml"
},
{
"type": "WEB",
"url": "https://vuldb.com/?ctiid.310263"
},
{
"type": "WEB",
"url": "https://vuldb.com/?id.310263"
},
{
"type": "WEB",
"url": "https://vuldb.com/?submit.579824"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "pypickle Incorrect Privilege Assignment vulnerability"
}
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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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