LangChain serialization injection vulnerability enables secret extraction
A serialization injection vulnerability exists in LangChain JS's toJSON() method (and subsequently when string-ifying objects using JSON.stringify(). The method did not escape objects with 'lc' keys when serializing free-form data in kwargs. The 'lc' key is used internally by LangChain to mark serialized objects. When user-controlled data contains this key structure, it is treated as a legitimate LangChain object during deserialization rather than plain user data.
The core vulnerability was in Serializable.toJSON(): this method failed to escape user-controlled objects containing 'lc' keys within kwargs (e.g., additional_kwargs, metadata, response_metadata). When this unescaped data was later deserialized via load(), the injected structures were treated as legitimate LangChain objects rather than plain user data.
This escaping bug enabled several attack vectors:
1. Injection via user data: Malicious LangChain object structures could be injected through user-controlled fields like metadata, additional_kwargs, or response_metadata
2. Secret extraction: Injected secret structures could extract environment variables when secretsFromEnv was enabled (which had no explicit default, effectively defaulting to true behavior)
3. Class instantiation via import maps: Injected constructor structures could instantiate any class available in the provided import maps with attacker-controlled parameters
Note on import maps: Classes must be explicitly included in import maps to be instantiatable. The core import map includes standard types (messages, prompts, documents), and users can extend this via importMap and optionalImportsMap options. This architecture naturally limits the attack surface—an allowedObjects parameter is not necessary because users control which classes are available through the import maps they provide.
Security hardening: This patch fixes the escaping bug in toJSON() and introduces new restrictive defaults in load(): secretsFromEnv now explicitly defaults to false, and a maxDepth parameter protects against DoS via deeply nested structures. JSDoc security warnings have been added to all import map options.
Applications are vulnerable if they:
1. Serialize untrusted data via JSON.stringify() on Serializable objects, then deserialize with load() — Trusting your own serialization output makes you vulnerable if user-controlled data (e.g., from LLM responses, metadata fields, or user inputs) contains 'lc' key structures.
2. Deserialize untrusted data with load() — Directly deserializing untrusted data that may contain injected 'lc' structures.
3. Use LangGraph checkpoints — Checkpoint serialization/deserialization paths may be affected.
The most common attack vector is through LLM response fields like additional_kwargs or response_metadata, which can be controlled via prompt injection and then serialized/deserialized in streaming operations.
Attackers who control serialized data can extract environment variable secrets by injecting {"lc": 1, "type": "secret", "id": ["ENV_VAR"]} to load environment variables during deserialization (when secretsFromEnv: true). They can also instantiate classes with controlled parameters by injecting constructor structures to instantiate any class within the provided import maps with attacker-controlled parameters, potentially triggering side effects such as network calls or file operations.
Key severity factors:
secretsFromEnv: trueadditional_kwargs can be controlled via prompt injection```typescript
import { load } from "@langchain/core/load";
// Attacker injects secret structure into user-controlled data
const attackerPayload = JSON.stringify({
user_data: {
lc: 1,
type: "secret",
id: ["OPENAI_API_KEY"],
},
});
process.env.OPENAI_API_KEY = "sk-secret-key-12345";
// With secretsFromEnv: true, the secret is extracted
const deserialized = await load(attackerPayload, { secretsFromEnv: true });
console.log(deserialized.user_data); // "sk-secret-key-12345" - SECRET LEAKED!
```
This patch introduces the following changes to load():
1. secretsFromEnv default changed to false: Disables automatic secret loading from environment variables. Secrets not found in secretsMap now throw an error instead of being loaded from process.env. This fail-safe behavior ensures missing secrets are caught immediately rather than silently continuing with null.
2. New maxDepth parameter (defaults to 50): Protects against denial-of-service attacks via deeply nested JSON structures that could cause
This issue can be reached over the network, attack complexity is low, an attacker needs no privileges on the target. No user interaction is required. The scope is changed, meaning a successful attack can affect components beyond the vulnerable one. Rated impact: confidentiality high, integrity none, availability none.
The score comes from this vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
CVE-2025-68665 is classified as CWE-502: Deserialization of Untrusted Data. Serialised data from an untrusted source is reconstructed into objects, which can trigger code during the process.
CVE-2025-68665 is recorded against 4 packages.
Published on 23 December 2025 and last revised on 4 February 2026. No public exploit is currently recorded for this entry. A vendor advisory or fix has been published. Record sourced from NVD.
github.com (Web)
nvd.nist.gov (Advisory)
github.com (Web)
github.com (Package)
github.com (Web)
github.com (Web)
@langchain/core has other advisories on record. If you are patching this one, these are worth checking on the same host:
These advisories are the same class of weakness (CWE-502: Deserialization of Untrusted Data) in other software:
Each distribution ships its own build and its own fixed version. Pick the one you run:
Details
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Affected Packages
| Software | From version | Fixed in |
|---|---|---|
| @langchain/core | — | — |
| langchain | — | — |
| langchain.js | 1.0.0 | 1.2.3 |
| langchain\/core | 1.0.0 | 1.1.8 |
References
Similar Threats
Site Security Check
CVE-2025-68665 is rated CVSS 8.6 High. BotEraser scans your installation against known CVE records and tells you whether this vulnerability applies to the versions you actually run.
Scan My Site Free →No credit card required · Results in minutes
ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the vulnerabilities listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.
Stay up to date with the latest from Boteraser.
We use cookies to improve your experience on our site. By using our site, you consent to cookies.
Manage your cookie preferences below:
Essential cookies enable basic functions and are necessary for the proper function of the website.
CloudFlare provides web performance and security solutions, enhancing site speed and protecting against threats.
Service URL: developers.cloudflare.com (opens in a new window)
These cookies are needed for adding comments on this website.
These cookies are used for managing login functionality on this website.
Statistics cookies collect information anonymously. This information helps us understand how visitors use our website.
Google Analytics is a powerful tool that tracks and analyzes website traffic for informed marketing decisions.
Service URL: policies.google.com (opens in a new window)
You can find more information in our Cookie Policy and Privacy Policy.