PYSEC-2026-447
Vulnerability from pysec - Published: 2026-06-29 11:50 - Updated: 2026-06-29 12:05
VLAI
Details
An issue in pandas-ai v.0.8.1 and before allows a remote attacker to execute arbitrary code via the _is_jailbreak function.
Severity
9.8 (Critical)
Impacted products
| Name | purl | pandasai |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "pandasai"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"last_affected": "0.8.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.0.1",
"0.0.2",
"0.0.3",
"0.1.0",
"0.1.1",
"0.2.0",
"0.2.1",
"0.2.10",
"0.2.11",
"0.2.12",
"0.2.13",
"0.2.14",
"0.2.15",
"0.2.16",
"0.2.2",
"0.2.3",
"0.2.4",
"0.2.5",
"0.2.6",
"0.2.7",
"0.2.8",
"0.2.9",
"0.3.0",
"0.4.0",
"0.4.1",
"0.4.2",
"0.5.0",
"0.5.1",
"0.5.2",
"0.5.3",
"0.5.4",
"0.5.5",
"0.6.0",
"0.6.1",
"0.6.10",
"0.6.11",
"0.6.12",
"0.6.2",
"0.6.3",
"0.6.4",
"0.6.5",
"0.6.6",
"0.6.7",
"0.6.8",
"0.6.9",
"0.7.0",
"0.7.1",
"0.7.2",
"0.8.0",
"0.8.1"
]
}
],
"aliases": [
"CVE-2023-39661",
"GHSA-8fp9-43pw-56vw"
],
"details": "An issue in pandas-ai v.0.8.1 and before allows a remote attacker to execute arbitrary code via the `_is_jailbreak` function.",
"id": "PYSEC-2026-447",
"modified": "2026-06-29T12:05:39.507745Z",
"published": "2026-06-29T11:50:44.070778Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-39661"
},
{
"type": "WEB",
"url": "https://github.com/gventuri/pandas-ai/issues/410"
},
{
"type": "PACKAGE",
"url": "https://github.com/gventuri/pandas-ai"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/pandasai"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-8fp9-43pw-56vw"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
],
"summary": "PandasAI vulnerable to arbitrary code execution"
}
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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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