Your RSA-2048 keys break in 2030. Find every one of them before attackers do.
🐍 PyPI

GHSA-9rwj-6rc7-p77c

HIGH

LangGraph's SQLite is vulnerable to SQL injection via metadata filter key in SQLite checkpointer list method

Also known asCVE-2025-67644
Published
Dec 10, 2025
Updated
Dec 11, 2025
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed

EPSS Exploitation Probability

via FIRST.org ↗
2.1%probability of exploitation in next 30 days
Lower Risk79th percentile+2.05%
0.00%0.90%1.79%2.69%0.0%2.1%Jan 26Apr 26Jun 26

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

1 pkg affected
🐍langgraph-checkpoint-sqlite

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Context

A SQL injection vulnerability exists in LangGraph's SQLite checkpoint implementation that allows attackers to manipulate SQL queries through metadata filter keys. This affects applications that accept untrusted metadata filter keys (not just filter values) in checkpoint search operations.

Impact

Attackers who control metadata filter keys can execute arbitrary sql queries against the database.

Root Cause

The _metadata_predicate() function constructs SQL queries by interpolating filter keys directly into f-strings without validation:

# VULNERABLE CODE (before fix)
for query_key, query_value in metadata_filter.items():
    operator, param_value = _where_value(query_value)
    predicates.append(
        f"json_extract(CAST(metadata AS TEXT), '$.{query_key}') {operator}"
    )
    param_values.append(param_value)

While filter values are parameterized, filter keys are not validated, allowing SQL injection.

Attack Example

Before Fix:

from langgraph.checkpoint.sqlite import SqliteSaver

saver = SqliteSaver.from_conn_string("checkpoints.db")

# Attacker controls the filter keys
malicious_filter = {"x') OR '1'='1": "dummy"}

# Returns ALL checkpoints, bypassing filtering
results = list(saver.list(None, filter=malicious_filter))

Resulting SQL:

WHERE json_extract(CAST(metadata AS TEXT), '$.x') OR '1'='1') = ?
-- Injected condition makes WHERE clause always true

Who Is Affected?

LangSmith Deployment Customers: NOT Impacted

LangSmith deployment customers are NOT affected by this vulnerability. LangSmith deployments do not allow configuring custom checkpointers, so the vulnerable code path cannot be reached.

High Risk: Custom Server Deployments

You are affected if your application:

  • Runs a custom server with SqliteSaver checkpointer
  • Exposes an endpoint for fetching checkpoint history (e.g., via get_state_history())
  • Accepts metadata filter keys from untrusted sources

Example vulnerable code:

# Custom server endpoint - User controls filter key names - DANGEROUS
@app.post("/api/history")
def get_history(request):
    filter_field = request.json.get("filter_field")  # Untrusted input
    filter_value = request.json.get("filter_value")

    # VULNERABLE: Attacker can bypass access controls
    history = list(graph.get_state_history(
        config,
        filter={filter_field: filter_value}
    ))
    return history

Note on privilege escalation: If an endpoint allows end users to specify arbitrary filter keys, those users likely already have legitimate access to query the checkpoint database. In such cases, this vulnerability may not constitute a privilege escalation, as users who can control filter keys would typically already be expected to have database access. However, the SQL injection still allows bypassing intended filtering logic and metadata-based access controls that the application may rely on for data isolation.

Additional Security Hardening (Defense in Depth)

This release also includes hardening improvements:

1. Checkpoint Limit Parameter: used f-string interpolation into parameterized query. Not considered a vulnerability as it requires users to accept untrusted input and not validate it against the actual API signature.

2. Store Filter Value Parameterization: Refactored all filter value handling from manual quote escaping to parameterized queries

Remediation

Immediate Actions

  1. Update to the patched version of langgraph-checkpoint-sqlite
  2. Audit your code for locations where filter keys come from untrusted sources

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIlanggraph-checkpoint-sqliteall versions3.0.1

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for langgraph-checkpoint-sqlite. 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.

  2. Fix

    Update langgraph-checkpoint-sqlite to 3.0.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-9rwj-6rc7-p77c is resolved across your whole dependency graph.

  3. 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.

  4. How O3 protects you

    O3 pinpoints whether GHSA-9rwj-6rc7-p77c 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-9rwj-6rc7-p77c. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

# Context A SQL injection vulnerability exists in LangGraph's SQLite checkpoint implementation that allows attackers to manipulate SQL queries through metadata filter keys. This affects applications that accept **untrusted metadata filter keys** (not just filter values) in checkpoint search operations. # Impact Attackers who control metadata filter keys can execute arbitrary sql queries against the database. # Root Cause The `_metadata_predicate()` function constructs SQL queries by interpolating filter keys directly into f-strings without validation: ```python # VULNERABLE CODE (before
O3 Security · Impact-Aware SCA

Is GHSA-9rwj-6rc7-p77c in your dependencies?

O3 detects GHSA-9rwj-6rc7-p77c across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.