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Search Results (5 CVEs found)
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2026-115883 | 1 Langchain-ai | 3 Langgraph, Langgraph-checkpoint-postgres, Langgraph-checkpoint-sqlite | 2026-10-26 | N/A |
| LangGraph checkpoint savers provide Postgres- and SQLite-backed state persistence for LangGraph workflows and agents. Prior to langgraph-checkpoint-postgres 3.1.3 and langgraph-checkpoint-sqlite 3.1.2, PostgresStore, AsyncPostgresStore, SqliteStore, and AsyncSqliteStore flatten namespace labels with ".".join(namespace), while BaseStore validates labels only for put and aput. Unvalidated dotted labels passed through get, search, delete, list_namespaces, their asynchronous equivalents, or direct batch and abatch operations can resolve to another tenant's stored namespace, allowing cross-namespace reads, overwrites, or deletion. InMemoryStore is not affected because it compares namespace tuples. This issue is fixed in langgraph-checkpoint-postgres 3.1.3 and langgraph-checkpoint-sqlite 3.1.2. | ||||
| CVE-2026-71433 | 2 Langchain, Langchain-ai | 3 Langgraph-checkpoint-sqlite, Langgraph, Langgraph-checkpoint-postgres | 2026-08-07 | 5.3 Medium |
| LangGraph Checkpoint Postgres and SQLite Checkpoint are the Postgres and SQLite implementations of LangGraph's checkpoint saver. Prior to 3.1.1, the langgraph-checkpoint-postgres and langgraph-checkpoint-sqlite packages persisted hierarchical namespaces as a dot joined string and scoped reads by matching that string as a simple prefix pattern, so a read scoped to one namespace could also match a sibling namespace whose flattened form shares the same leading characters, or a namespace label containing unescaped pattern metacharacters, allowing an authenticated caller to retrieve stored items belonging to another tenant or user through an ordinary scoped search or list namespaces call, with no crafted input required. This issue is fixed in versions 3.1.1 of langgraph-checkpoint-postgres and langgraph-checkpoint-sqlite. | ||||
| CVE-2026-48775 | 2 Langchain, Langchain-ai | 3 Langgraph-checkpoint, Langgraph, Langgraph-checkpoint | 2026-06-16 | 6.8 Medium |
| LangGraph SQLite Checkpoint is an implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via aiosqlite). In versions 4.1.0 and prior, the JsonPlusSerializer can reconstruct Python objects from JSON checkpoint payloads. Under conditions where someone could modify checkpoint bytes at rest in the backing store, the deserialization path could reconstruct objects beyond what the application expects, which could in turn result in code execution at checkpoint load time. This is a defense-in-depth issue. The affected behavior is reachable only when checkpoint bytes at rest in the backing store can be modified by an unauthorized party. In most deployments that prerequisite already implies a serious incident; the additional concern is turning "checkpoint-store write access" into code execution in the application runtime. This issue has been fixed in version 4.1.1. | ||||
| CVE-2026-27794 | 1 Langchain-ai | 1 Langgraph-checkpoint | 2026-04-17 | 6.6 Medium |
| LangGraph Checkpoint defines the base interface for LangGraph checkpointers. Prior to version 4.0.0, a Remote Code Execution vulnerability exists in LangGraph's caching layer when applications enable cache backends that inherit from `BaseCache` and opt nodes into caching via `CachePolicy`. Prior to `langgraph-checkpoint` 4.0.0, `BaseCache` defaults to `JsonPlusSerializer(pickle_fallback=True)`. When msgpack serialization fails, cached values can be deserialized via `pickle.loads(...)`. Caching is not enabled by default. Applications are affected only when the application explicitly enables a cache backend (for example by passing `cache=...` to `StateGraph.compile(...)` or otherwise configuring a `BaseCache` implementation), one or more nodes opt into caching via `CachePolicy`, and the attacker can write to the cache backend (for example a network-accessible Redis instance with weak/no auth, shared cache infrastructure reachable by other tenants/services, or a writable SQLite cache file). An attacker must be able to write attacker-controlled bytes into the cache backend such that the LangGraph process later reads and deserializes them. This typically requires write access to a networked cache (for example a network-accessible Redis instance with weak/no auth or shared cache infrastructure reachable by other tenants/services) or write access to local cache storage (for example a writable SQLite cache file via permissive file permissions or a shared writable volume). Because exploitation requires write access to the cache storage layer, this is a post-compromise / post-access escalation vector. LangGraph Checkpoint 4.0.0 patches the issue. | ||||
| CVE-2025-67644 | 2 Langchain, Langchain-ai | 4 Langchain, Langgraph-checkpoint-sqlite, Langchain and 1 more | 2026-03-17 | 7.3 High |
| LangGraph SQLite Checkpoint is an implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via aiosqlite). Versions 3.0.0 and below are vulnerable to SQL injection through the checkpoint implementation. Checkpoint allows attackers to manipulate SQL queries through metadata filter keys, affecting applications that accept untrusted metadata filter keys (not just filter values) in checkpoint search operations. The _metadata_predicate() function constructs SQL queries by interpolating filter keys directly into f-strings without validation. This issue is fixed in version 3.0.1. | ||||
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