LangChain Experimental vulnerable to arbitrary code execution
The advisory, in context
langchain_experimental (aka LangChain Experimental) before 0.0.52, part of LangChain before 0.1.8, allows an attacker to bypass the CVE-2023-44467 fix and execute arbitrary code via the __import__, __subclasses__, __builtins__, __globals__, __getattribute__, __bases__, __mro__, or __base__ attribute in Python code. These are not prohibited by pal_chain/base.py.
Affected packages
Start with the recorded fix for your release branch. Check your installed version and test compatibility before upgrading. Fixing this advisory does not rule out other vulnerabilities in the release.
Earlier releases before 0.0.52
Fixed in 0.0.52
54 explicitly affected versions
0.0.1, 0.0.10, 0.0.11, 0.0.12, 0.0.13, 0.0.14, 0.0.15, 0.0.16, 0.0.17, 0.0.18, 0.0.19, 0.0.1rc1, 0.0.1rc2, 0.0.1rc3, 0.0.1rc4, 0.0.2, 0.0.20, 0.0.21, 0.0.22, 0.0.23, 0.0.24, 0.0.25, 0.0.27, 0.0.28, 0.0.29, 0.0.3, 0.0.30, 0.0.31, 0.0.32, 0.0.33, 0.0.34, 0.0.35, 0.0.36, 0.0.37, 0.0.38, 0.0.39, 0.0.4, 0.0.40, 0.0.41, 0.0.42, 0.0.43, 0.0.44, 0.0.45, 0.0.46, 0.0.47, 0.0.48, 0.0.49, 0.0.5, 0.0.50, 0.0.51, 0.0.6, 0.0.7, 0.0.8, 0.0.9
View affected-version evidence
{
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.0.52"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.0.1",
"0.0.10",
"0.0.11",
"0.0.12",
"0.0.13",
"0.0.14",
"0.0.15",
"0.0.16",
"0.0.17",
"0.0.18",
"0.0.19",
"0.0.1rc1",
"0.0.1rc2",
"0.0.1rc3",
"0.0.1rc4",
"0.0.2",
"0.0.20",
"0.0.21",
"0.0.22",
"0.0.23",
"0.0.24",
"0.0.25",
"0.0.27",
"0.0.28",
"0.0.29",
"0.0.3",
"0.0.30",
"0.0.31",
"0.0.32",
"0.0.33",
"0.0.34",
"0.0.35",
"0.0.36",
"0.0.37",
"0.0.38",
"0.0.39",
"0.0.4",
"0.0.40",
"0.0.41",
"0.0.42",
"0.0.43",
"0.0.44",
"0.0.45",
"0.0.46",
"0.0.47",
"0.0.48",
"0.0.49",
"0.0.5",
"0.0.50",
"0.0.51",
"0.0.6",
"0.0.7",
"0.0.8",
"0.0.9"
]
}References
- https://nvd.nist.gov/vuln/detail/CVE-2024-27444
- https://github.com/langchain-ai/langchain/commit/de9a6cdf163ed00adaf2e559203ed0a9ca2f1de7
- https://github.com/langchain-ai/langchain
- https://github.com/pypa/advisory-database/tree/main/vulns/langchain-experimental/PYSEC-2026-375.yaml
- https://pypi.org/project/langchain-experimental