Vulnerabilities in pkg:pypi/langgraph

PACKAGE
Advisory Identifier: GHSA-g48c-2wqr-h844
Advisory Summary

CVE-2026-28277 is a MODERATE (CVSS 6.8) langgraph checkpoint loading has unsafe vulnerability (CWE-502: Deserialization of Untrusted Data) affecting Langgraph libraries in the PyPI ecosystem. The issue involves langgraph checkpoint loading has unsafe msgpack deserialization. Remediation is available by upgrading affected packages to version 1.0.10.

1 Known Advisory Record(s)
Package Vulnerability Intelligence

pkg:pypi/langgraph

1 Known Advisory Record(s)

Vulnerability advisories affecting package pkg:pypi/langgraph. Select an advisory below to view technical details or fixes.

Advisory ID CVE / NVD Severity Summary
GHSA-g48c-2wqr-h844 CVE-2026-28277 MODERATE LangGraph checkpoint loading has unsafe msgpack deserialization

CVE-2026-28277 at a Glance

CVE Identifier CVE-2026-28277
GHSA Identifier GHSA-g48c-2wqr-h844
Severity MODERATE
CVSS v3.1 Base Score 6.8
CWE Classification CWE-502: Deserialization of Untrusted Data
Affected Product Langgraph
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 6.8

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:A/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H).

Attack Vector Adjacent (AV:A)
Attack Complexity Low (AC:L)
Privileges Required High (PR:H)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity High (I:H)
Availability High (A:H)

How to Fix CVE-2026-28277

To remediate this vulnerability, upgrade all affected Langgraph dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

langgraph fixed: 1.0.10
pip install langgraph>=1.0.10
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show langgraph

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-28277, inspect your installed packages using pip:

pip show langgraph

Analyze the terminal output to locate any version of Langgraph in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 1.0.10), your application is affected.

Note: The pip show langgraph command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-502: Deserialization of Untrusted Data, where the product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid. In Langgraph, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

LangGraph checkpointers can load msgpack-encoded checkpoints that reconstruct Python objects during deserialization. If an attacker can modify checkpoint data in the backing store (for example, after a database compromise or other privileged write access to the persistence layer), they can potentially supply a crafted payload that triggers unsafe object reconstruction when the checkpoint is loaded. This is a **post-exploitation / defense-in-depth** issue. Exploitation requires the ability to write attacker-controlled checkpoint bytes at rest. In most deployments that prerequisite already implies a serious incident; the additional risk is turning “checkpoint-store write access” into code execution in the application runtime, which can expand blast radius (for example by exposing environment variables or cloud credentials available to the runtime). There is no evidence of exploitation in the wild, and LangGraph is not aware of a practical exploitation path in existing deployments today. This change is intended to reduce the blast radius of a checkpoint-store compromise. ## Affected users / systems Users may be affected if they: - use a persistent checkpointer (database, remote store, shared filesystem, etc.), - load/resume from checkpoints, and - operate in an environment where an attacker could gain privileged write access to checkpoint data in the backing store. This issue requires the attacker to be able to modify persisted checkpoint bytes (or to compromise a trusted component that writes them). It is generally not reachable by an unauthenticated remote attacker in a correctly configured deployment. ## Impact - Potential **arbitrary code execution** or other unsafe side effects during checkpoint deserialization. - Escalation from “write access to checkpoint store” to “code execution in the application runtime,” which may expose runtime secrets or provide access to other systems the runtime can reach. ## Exploitation scenario (high level) 1. Attacker gains privileged write access to the checkpoint store (for example, via database compromise, leaked credentials, or abuse of an administrative data path). 2. Attacker writes a crafted checkpoint payload containing msgpack data intended to reconstruct dangerous objects. 3. Application resumes and deserializes the checkpoint; unsafe reconstruction could execute attacker-controlled behavior. ## Mitigation / remediation LangGraph provides an allowlist-based hardening mechanism for msgpack checkpoint deserialization. ### Strict mode (environment variable) - **`LANGGRAPH_STRICT_MSGPACK`** - When set truthy (`1`, `true`, `yes`), the default msgpack deserialization policy becomes strict. - Concretely: `JsonPlusSerializer()` will default `allowed_msgpack_modules` to `None` (strict) instead of `True` (warn-and-allow), unless `allowed_msgpack_modules=...` is explicitly passed. ### `allowed_msgpack_modules` (serializer/checkpointer config) This setting controls what msgpack “ext” types are allowed to be reconstructed. - `True` (default when strict mode is not enabled): allow all ext types, but log a warning when deserializing a type that is not explicitly registered. - `None` (strict): only a built-in safe set is reconstructed; other ext types are blocked. - `[(module, class_name), ...]` (strict allowlist): the built-in safe set plus exactly the listed symbols are reconstructed (exact-match). ### Built-in safe set A small set of types is always treated as safe to reconstruct (for example `datetime` types, `uuid.UUID`, `decimal.Decimal`, `set`/`frozenset`/`deque`, `ipaddress` types, `pathlib` paths, `zoneinfo.ZoneInfo`, compiled regex patterns, and selected LangGraph internal types). ### Automatically derived allowlist (only when compiling graphs) When `LANGGRAPH_STRICT_MSGPACK` is enabled and `StateGraph` is compiled, LangGraph derives an allowlist from the graph’s schemas and channels and applies it to the checkpointer. - The allowlist is built by walking the state/input/output/context schemas (plus node/branch input schemas) and channel value/update types. It includes Pydantic v1/v2 models, dataclasses, enums, TypedDict field types, and common typing constructs (containers, unions, `Annotated`). - LangGraph also includes a curated set of common LangChain message classes. This derived allowlist is only applied if the selected checkpointer supports `with_allowlist(...)`. If a user is constructing serializers/checkpointers manually (or using a checkpointer that does not support allowlist propagation), they will need to configure `allowed_msgpack_modules` themselves. ### Operational guidance - Treat checkpoint stores as integrity-sensitive. Restrict write access and rotate credentials if compromise is suspected. - Enable strict mode (`LANGGRAPH_STRICT_MSGPACK=true`) in production if feasible, and rely on schema-driven allowlisting to reduce incompatibilities. - Avoid providing custom msgpack deserialization hooks that reconstruct arbitrary types unless checkpoint data is fully trusted. ## Limitations / important notes - If a checkpointer implementation does **not** support allowlist application (i.e., does not implement `with_allowlist`), allowlist enforcement may be skipped (with a warning). In that situation, strict expectations may not hold. - If an application supplies a custom msgpack unpack hook (`ext_hook`), the custom hook controls reconstruction and can bypass the default allowlist checks (intentional escape hatch, but it weakens the protection). ## LangSmith / hosted deployments note LangSmith is not aware of this issue presenting risk to existing LangSmith-hosted deployments. The described threat model requires an attacker to tamper with the checkpoint persistence layer used by the deployment; typical hosted configurations are designed to prevent such access. First reported by: yardenporat353

CVE-2026-28277 Affected Langgraph Versions

1 component(s)
Fixed Versions:
1.0.10
Product / Package Ecosystem Affected Versions Fixed Version
langgraph
PyPI
< 1.0.10
1.0.10

References

Frequently Asked Questions

What is CVE-2026-28277?
CVE-2026-28277 is a security vulnerability in Langgraph involving LangGraph checkpoint loading has unsafe msgpack deserialization under CWE-502: Deserialization of Untrusted Data.
Which Langgraph versions are affected?
Affected versions include releases prior to 1.0.10 across affected packages: langgraph.
What version fixes CVE-2026-28277?
Upgrading to 1.0.10 (or the latest patched release for your respective branch) resolves the vulnerability.
Is langgraph affected?
Yes, langgraph is affected in releases prior to 1.0.10. Upgrade your dependency to 1.0.10 or later.
What is the CVSS score of CVE-2026-28277?
CVE-2026-28277 has a CVSS v3.1 base score of 6.8 (MODERATE) with vector string CVSS:3.1/AV:A/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2026-28277?
CVE-2026-28277 is classified under CWE-502: Deserialization of Untrusted Data (The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.).
How can I check PyPI dependencies for CVE-2026-28277?
Run the dependency tree command: 'pip show langgraph'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-g48c-2wqr-h844",
  "modified" : "2026-06-06T00:47:12Z",
  "published" : "2026-03-05T20:19:49Z",
  "aliases" : [ "CVE-2026-28277" ],
  "summary" : "LangGraph checkpoint loading has unsafe msgpack deserialization",
  "details" : "LangGraph checkpointers can load msgpack-encoded checkpoints that reconstruct Python objects during deserialization. If an attacker can modify checkpoint data in the backing store (for example, after a database compromise or other privileged write access to the persistence layer), they can potentially supply a crafted payload that triggers unsafe object reconstruction when the checkpoint is loaded.\n\nThis is a **post-exploitation / defense-in-depth** issue. Exploitation requires the ability to write attacker-controlled checkpoint bytes at rest. In most deployments that prerequisite already implies a serious incident; the additional risk is turning “checkpoint-store write access” into code execution in the application runtime, which can expand blast radius (for example by exposing environment variables or cloud credentials available to the runtime).\n\nThere is no evidence of exploitation in the wild, and LangGraph is not aware of a practical exploitation path in existing deployments today. This change is intended to reduce the blast radius of a checkpoint-store compromise.\n\n## Affected users / systems\n\nUsers may be affected if they:\n\n- use a persistent checkpointer (database, remote store, shared filesystem, etc.),\n- load/resume from checkpoints, and\n- operate in an environment where an attacker could gain privileged write access to checkpoint data in the backing store.\n\nThis issue requires the attacker to be able to modify persisted checkpoint bytes (or to compromise a trusted component that writes them). It is generally not reachable by an unauthenticated remote attacker in a correctly configured deployment.\n\n## Impact\n- Potential **arbitrary code execution** or other unsafe side effects during checkpoint deserialization.\n- Escalation from “write access to checkpoint store” to “code execution in the application runtime,” which may expose runtime secrets or provide access to other systems the runtime can reach.\n\n## Exploitation scenario (high level)\n1. Attacker gains privileged write access to the checkpoint store (for example, via database compromise, leaked credentials, or abuse of an administrative data path).\n2. Attacker writes a crafted checkpoint payload containing msgpack data intended to reconstruct dangerous objects.\n3. Application resumes and deserializes the checkpoint; unsafe reconstruction could execute attacker-controlled behavior.\n\n## Mitigation / remediation\nLangGraph provides an allowlist-based hardening mechanism for msgpack checkpoint deserialization.\n\n### Strict mode (environment variable)\n- **`LANGGRAPH_STRICT_MSGPACK`**\n  - When set truthy (`1`, `true`, `yes`), the default msgpack deserialization policy becomes strict.\n  - Concretely: `JsonPlusSerializer()` will default `allowed_msgpack_modules` to `None` (strict) instead of `True` (warn-and-allow), unless `allowed_msgpack_modules=...` is explicitly passed.\n\n### `allowed_msgpack_modules` (serializer/checkpointer config)\nThis setting controls what msgpack “ext” types are allowed to be reconstructed.\n\n- `True` (default when strict mode is not enabled): allow all ext types, but log a warning when deserializing a type that is not explicitly registered.\n- `None` (strict): only a built-in safe set is reconstructed; other ext types are blocked.\n- `[(module, class_name), ...]` (strict allowlist): the built-in safe set plus exactly the listed symbols are reconstructed (exact-match).\n\n### Built-in safe set\nA small set of types is always treated as safe to reconstruct (for example `datetime` types, `uuid.UUID`, `decimal.Decimal`, `set`/`frozenset`/`deque`, `ipaddress` types, `pathlib` paths, `zoneinfo.ZoneInfo`, compiled regex patterns, and selected LangGraph internal types).\n\n### Automatically derived allowlist (only when compiling graphs)\nWhen `LANGGRAPH_STRICT_MSGPACK` is enabled and `StateGraph` is compiled, LangGraph derives an allowlist from the graph’s schemas and channels and applies it to the checkpointer.\n\n- The allowlist is built by walking the state/input/output/context schemas (plus node/branch input schemas) and channel value/update types. It includes Pydantic v1/v2 models, dataclasses, enums, TypedDict field types, and common typing constructs (containers, unions, `Annotated`).\n- LangGraph also includes a curated set of common LangChain message classes.\n\nThis derived allowlist is only applied if the selected checkpointer supports `with_allowlist(...)`. If a user is constructing serializers/checkpointers manually (or using a checkpointer that does not support allowlist propagation), they will need to configure `allowed_msgpack_modules` themselves.\n\n### Operational guidance\n- Treat checkpoint stores as integrity-sensitive. Restrict write access and rotate credentials if compromise is suspected.\n- Enable strict mode (`LANGGRAPH_STRICT_MSGPACK=true`) in production if feasible, and rely on schema-driven allowlisting to reduce incompatibilities.\n- Avoid providing custom msgpack deserialization hooks that reconstruct arbitrary types unless checkpoint data is fully trusted.\n\n## Limitations / important notes\n- If a checkpointer implementation does **not** support allowlist application (i.e., does not implement `with_allowlist`), allowlist enforcement may be skipped (with a warning). In that situation, strict expectations may not hold.\n- If an application supplies a custom msgpack unpack hook (`ext_hook`), the custom hook controls reconstruction and can bypass the default allowlist checks (intentional escape hatch, but it weakens the protection).\n\n## LangSmith / hosted deployments note\nLangSmith is not aware of this issue presenting risk to existing LangSmith-hosted deployments. The described threat model requires an attacker to tamper with the checkpoint persistence layer used by the deployment; typical hosted configurations are designed to prevent such access.\n\nFirst reported by:  yardenporat353",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:A/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "langgraph"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "1.0.10"
      } ]
    } ],
    "database_specific" : {
      "last_known_affected_version_range" : "<= 1.0.9"
    }
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/langchain-ai/langgraph/security/advisories/GHSA-g48c-2wqr-h844"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-28277"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/langchain-ai/langgraph"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/langgraph/PYSEC-2026-83.yaml"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-502" ],
    "severity" : "MODERATE",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-03-05T20:19:49Z",
    "nvd_published_at" : "2026-03-05T20:16:15Z"
  }
}