FKIE_CVE-2025-68664
Vulnerability from fkie_nvd - Published: 2025-12-23 23:15 - Updated: 2026-06-17 09:59
Severity
9.3 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:L/A:N
8.2 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:N
8.2 (High) - CVSS:3.1/
Summary
LangChain is a framework for building agents and LLM-powered applications. Prior to versions 0.3.81 and 1.2.5, a serialization injection vulnerability exists in LangChain's dumps() and dumpd() functions. The functions do not escape dictionaries with 'lc' keys when serializing free-form dictionaries. The 'lc' key is used internally by LangChain to mark serialized objects. When user-controlled data contains this key structure, it is treated as a legitimate LangChain object during deserialization rather than plain user data. This issue has been patched in versions 0.3.81 and 1.2.5.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| langchain | langchain_core | * | |
| langchain | langchain_core | * |
{
"affected": [
{
"affectedData": [
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"product": "langchain",
"vendor": "langchain-ai",
"versions": [
{
"status": "affected",
"version": "\u003e= 1.0.0, \u003c 1.2.5"
},
{
"status": "affected",
"version": "\u003c 0.3.81"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
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"criteria": "cpe:2.3:a:langchain:langchain_core:*:*:*:*:*:python:*:*",
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"versionEndExcluding": "0.3.81",
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},
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}
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],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "LangChain is a framework for building agents and LLM-powered applications. Prior to versions 0.3.81 and 1.2.5, a serialization injection vulnerability exists in LangChain\u0027s dumps() and dumpd() functions. The functions do not escape dictionaries with \u0027lc\u0027 keys when serializing free-form dictionaries. The \u0027lc\u0027 key is used internally by LangChain to mark serialized objects. When user-controlled data contains this key structure, it is treated as a legitimate LangChain object during deserialization rather than plain user data. This issue has been patched in versions 0.3.81 and 1.2.5."
}
],
"id": "CVE-2025-68664",
"lastModified": "2026-06-17T09:59:23.937",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 9.3,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:L/A:N",
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"scope": "UNCHANGED",
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"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:N",
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"impactScore": 4.2,
"source": "nvd@nist.gov",
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"ssvcV203": [
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"options": [
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{
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{
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],
"role": "CISA Coordinator",
"timestamp": "2025-12-24T14:40:55.506059Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-12-23T23:15:44.933",
"references": [
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"source": "security-advisories@github.com",
"tags": [
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"tags": [
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"url": "https://github.com/langchain-ai/langchain/releases/tag/langchain-core%3D%3D0.3.81"
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"vulnStatus": "Analyzed",
"weaknesses": [
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"lang": "en",
"value": "CWE-502"
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],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
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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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