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LangGraph: Namespace prefix matching crosses segment boundaries in Postgres and SQLite stores

Moderate severity GitHub Reviewed Published Jul 30, 2026 in langchain-ai/langgraph • Updated Aug 11, 2026

Package

pip langgraph-checkpoint-postgres (pip)

Affected versions

< 3.1.1

Patched versions

3.1.1
pip langgraph-checkpoint-sqlite (pip)
< 3.1.1
3.1.1

Description

Summary

The Postgres and SQLite stores persist hierarchical namespaces as a dot-joined string (("memories", "alice") becomes memories.alice) and scoped reads by matching that string with LIKE '<path>%'. Because LIKE has no notion of the . separator, a scoped search or list_namespaces also matched sibling namespaces whose flattened form shares leading characters.

Applications commonly use the namespace as a tenant boundary. Where they do, a read scoped to one namespace could return items belonging to another, without any crafted input — an ordinary scoped request was sufficient.

We have no evidence of this behavior being exploited in the wild.

Affected users / systems

You may be affected if you:

  • use PostgresStore/AsyncPostgresStore or SqliteStore/AsyncSqliteStore, and
  • rely on the namespace to separate data between users or tenants, and
  • have namespace labels where one is a prefix of another (1 and 12, alice and alice2), or labels containing _ or %

Applications whose namespace labels are fixed-length identifiers such as UUIDs, containing no _ or %, are not affected — no such label can be a prefix of another. InMemoryStore compares namespaces element-wise and is not affected.

Three distinct cases were possible:

  • Sibling namespaces. A read scoped to ("foo",) also returned items under ("foobar",) and ("foo2",).
  • Unescaped pattern metacharacters. _ and % are legal namespace labels — only . is rejected — but were interpolated into the match pattern unescaped, so ("user_1",) also matched ("userX1",).
  • Suffix conditions. list_namespaces(suffix=("alice",)) also matched the sibling leaf users.malice.

This is not SQL injection. Values were passed as bound parameters and never interpolated into statement text; the bound value was itself a LIKE pattern whose metacharacters were not neutralized.

Impact

  • Confidentiality: disclosure of stored items belonging to namespaces outside the caller's intended scope, where namespaces are used as a tenant or user boundary.
  • No integrity or availability impact. get, put, and delete compare namespaces with = and were never affected; the issue is limited to read paths.

Patches / mitigation

Prefix scoping now matches the namespace exactly or requires the . separator before any remainder, pattern metacharacters in labels are escaped, and list_namespaces uses segment-aware matching for both prefix and suffix conditions.

On SQLite, the descendant match moved from LIKE to GLOB. LIKE is case-insensitive for ASCII in SQLite, so scoped reads previously matched namespaces differing only in case, while get/put/delete treated them as distinct. Search now agrees with them.

Upgrade to langgraph-checkpoint-postgres 3.1.1 or langgraph-checkpoint-sqlite 3.1.1.

Compatibility

* in a list_namespaces match path now spans exactly one namespace segment. This restores the documented behavior — NamespacePath documents ("cache", "*", "v1") as "any cache category with v1 version" — and matches InMemoryStore. Multi-segment matching was an artifact of translating * into a SQL % wildcard, the same mechanism responsible for this issue, and could not be preserved while fixing it.

Callers relying on the previous behavior can express "match at any depth" by combining both match conditions, which are ANDed:

list_namespaces(prefix=["uid"], suffix=["alice"])

Applications whose namespace labels cannot be prefixes of one another see no behavioral change.

Operational guidance

  • Prefer fixed-length namespace labels such as UUIDs, so no label can be a prefix of another.
  • Where labels are user-supplied, validate them at the boundary rather than relying on scoping alone.

LangSmith / hosted deployments note

Unlike previous store advisories, this issue does reach hosted deployments. LangSmith deployments default to LANGGRAPH_STORE_BACKEND=python, which uses AsyncPostgresStore from checkpoint-postgres. Deployments configured with LANGGRAPH_STORE_BACKEND=grpc use a separate implementation that received an equivalent fix.

References

@nick-hollon-lc nick-hollon-lc published to langchain-ai/langgraph Jul 30, 2026
Published to the GitHub Advisory Database Aug 6, 2026
Reviewed Aug 6, 2026
Last updated Aug 11, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
High
Privileges required
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
None
Availability
None

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(13th percentile)

Weaknesses

Exposure of Sensitive Information to an Unauthorized Actor

The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information. Learn more on MITRE.

Incorrect Authorization

The product performs an authorization check when an actor attempts to access a resource or perform an action, but it does not correctly perform the check. Learn more on MITRE.

CVE ID

CVE-2026-71433

GHSA ID

GHSA-47pj-3jcm-6whg

Credits

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