CVE-2026-55253 (GCVE-0-2026-55253)
Vulnerability from cvelistv5 – Published: 2026-09-14 17:09 – Updated: 2026-09-14 20:06
VLAI
EPSS
VEX
Title
LangChain MongoDB: NoSQL Operator Injection in MongoDBSaver.list() leading to cross-tenant data exposure
Summary
LangChain MongoDB provides integrations between MongoDB, Atlas, LangChain, and LangGraph. Prior to langgraph-checkpoint-mongodb 0.3.0 and langgraph-store-mongodb 0.4.0, MongoDBSaver.list(), MongoDBSaver.alist(), and MongoDBStore.search() incorporate filter dictionaries into MongoDB queries without recursively rejecting keys prefixed with $. An authenticated caller who controls a filter argument through HTTP query parameters, request body fields, or agent tool arguments can inject MongoDB Query Language operators such as $regex or $where. In a multi-tenant deployment that uses the filter to enforce per-user or per-tenant isolation, injected operators can bypass intended equality filtering and expose other tenants' checkpoint or store data. Filters constructed entirely from trusted server-side values have lower practical risk. This issue is fixed in langgraph-checkpoint-mongodb 0.3.0 and langgraph-store-mongodb 0.4.0.
Severity
7.7 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-14 19:20 UTC
CWE
- CWE-943 - Improper Neutralization of Special Elements in Data Query Logic
Assigner
References
7 references
| URL | Tags |
|---|---|
| https://github.com/langchain-ai/langchain-mongodb… | x_refsource_CONFIRM |
| https://github.com/langchain-ai/langchain-mongodb… | x_refsource_MISC |
| https://github.com/langchain-ai/langchain-mongodb… | x_refsource_MISC |
| https://github.com/langchain-ai/langchain-mongodb… | x_refsource_MISC |
| https://github.com/langchain-ai/langchain-mongodb… | x_refsource_MISC |
| https://github.com/langchain-ai/langchain-mongodb… | x_refsource_MISC |
| https://github.com/langchain-ai/langchain-mongodb… | x_refsource_MISC |
Impacted products
3 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| langchain-ai | langchain-mongodb |
Affected:
< 0.4.0
|
guessed | |
| langchain-ai | langgraph-checkpoint-mongodb |
Affected:
< 0.3.0
|
guessed | |
| langchain-ai | langgraph-store-mongodb |
Affected:
< 0.4.0
|
guessed |
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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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