Summary
LangGraph: Namespace prefix matching crosses segment boundaries in Postgres and SQLite stores
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/AsyncPostgresStoreorSqliteStore/AsyncSqliteStore, and - rely on the namespace to separate data between users or tenants, and
- have namespace labels where one is a prefix of another (
1and12,aliceandalice2), 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 leafusers.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.
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.
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, anddeletecompare namespaces with=and were never affected; the issue is limited to read paths.
The application does not correctly enforce access controls, allowing a principal to access resources or operations beyond their granted permissions. Typical impact: unauthorized data access or execution of privileged operations.
CVE-2026-71433 has a CVSS score of 5.3 (Medium). The vector is network-reachable, low privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (3.1.1); upgrading removes the vulnerable code path.
Affected versions
Security releases
Kodem intelligence
Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.
Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.
Already deployed Kodem?
See it in your environmentNew to Kodem? Get a demo →Remediation advice
langgraph-checkpoint-postgres to 3.1.1 or later; langgraph-checkpoint-sqlite to 3.1.1 or later
Kodem Kai can prioritize this vulnerability in your dependency tree and generate a fix recommendation.
Frequently Asked Questions
- What is CVE-2026-71433? CVE-2026-71433 is a medium-severity incorrect authorization vulnerability in langgraph-checkpoint-postgres (pip), affecting versions < 3.1.1. It is fixed in 3.1.1. The application does not correctly enforce access controls, allowing a principal to access resources or operations beyond their granted permissions.
- How severe is CVE-2026-71433? CVE-2026-71433 has a CVSS score of 5.3 (Medium). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
- Which packages are affected by CVE-2026-71433?
langgraph-checkpoint-postgres(pip) (versions < 3.1.1)langgraph-checkpoint-sqlite(pip) (versions < 3.1.1)
- Is there a fix for CVE-2026-71433? Yes. CVE-2026-71433 is fixed in 3.1.1. Upgrade to this version or later.
- Is CVE-2026-71433 exploitable, and should I be worried? Whether CVE-2026-71433 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
- What actually determines whether CVE-2026-71433 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
- How do I fix CVE-2026-71433?
- Upgrade
langgraph-checkpoint-postgresto 3.1.1 or later - Upgrade
langgraph-checkpoint-sqliteto 3.1.1 or later
- Upgrade