{
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "LangChain is a framework for building LLM-powered applications. Prior to @langchain/core versions 0.3.80 and 1.1.8, and prior to langchain versions 0.3.37 and 1.2.3, a serialization injection vulnerability exists in LangChain JS\u0027s toJSON() method (and subsequently when string-ifying objects using JSON.stringify(). The method did not escape objects with \u0027lc\u0027 keys when serializing free-form data in kwargs. The \u0027lc\u0027 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. This issue has been patched in @langchain/core versions 0.3.80 and 1.1.8, and langchain versions 0.3.37 and 1.2.3"
    }
  ],
  "id": "CVE-2025-68665",
  "lastModified": "2025-12-24T15:16:02.797",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 8.6,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "CHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 4.0,
        "source": "security-advisories@github.com",
        "type": "Secondary"
      }
    ]
  },
  "published": "2025-12-23T23:15:45.097",
  "references": [
    {
      "source": "security-advisories@github.com",
      "url": "https://github.com/langchain-ai/langchainjs/commit/e5063f9c6e9989ea067dfdff39262b9e7b6aba62"
    },
    {
      "source": "security-advisories@github.com",
      "url": "https://github.com/langchain-ai/langchainjs/releases/tag/%40langchain%2Fcore%401.1.8"
    },
    {
      "source": "security-advisories@github.com",
      "url": "https://github.com/langchain-ai/langchainjs/releases/tag/langchain%401.2.3"
    },
    {
      "source": "security-advisories@github.com",
      "url": "https://github.com/langchain-ai/langchainjs/security/advisories/GHSA-r399-636x-v7f6"
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "url": "https://github.com/langchain-ai/langchainjs/security/advisories/GHSA-r399-636x-v7f6"
    }
  ],
  "sourceIdentifier": "security-advisories@github.com",
  "vulnStatus": "Received",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-502"
        }
      ],
      "source": "security-advisories@github.com",
      "type": "Secondary"
    }
  ]
}

{
  "affected": [
    {
      "package": {
        "ecosystem": "npm",
        "name": "@langchain/core"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "1.0.0"
            },
            {
              "fixed": "1.1.8"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "npm",
        "name": "@langchain/core"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.3.80"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "npm",
        "name": "langchain"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "1.0.0"
            },
            {
              "fixed": "1.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "npm",
        "name": "langchain"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.3.37"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-68665"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-12-23T20:08:48Z",
    "nvd_published_at": "2025-12-23T23:15:45Z",
    "severity": "HIGH"
  },
  "details": "## Context\n\nA serialization injection vulnerability exists in LangChain JS\u0027s `toJSON()` method (and subsequently when string-ifying objects using `JSON.stringify()`. The method did not escape objects with `\u0027lc\u0027` keys when serializing free-form data in kwargs. The `\u0027lc\u0027` 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.\n\n### Attack surface\n\nThe core vulnerability was in `Serializable.toJSON()`: this method failed to escape user-controlled objects containing `\u0027lc\u0027` 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.\n\nThis escaping bug enabled several attack vectors:\n\n1. **Injection via user data**: Malicious LangChain object structures could be injected through user-controlled fields like `metadata`, `additional_kwargs`, or `response_metadata`\n2. **Secret extraction**: Injected secret structures could extract environment variables when `secretsFromEnv` was enabled (which had no explicit default, effectively defaulting to `true` behavior)\n3. **Class instantiation via import maps**: Injected constructor structures could instantiate any class available in the provided import maps with attacker-controlled parameters\n\n**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\u2014an `allowedObjects` parameter is not necessary because users control which classes are available through the import maps they provide.\n\n**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.\n\n## Who is affected?\n\nApplications are vulnerable if they:\n\n1. **Serialize untrusted data via `JSON.stringify()` on Serializable objects, then deserialize with `load()`** \u2014 Trusting your own serialization output makes you vulnerable if user-controlled data (e.g., from LLM responses, metadata fields, or user inputs) contains `\u0027lc\u0027` key structures.\n2. **Deserialize untrusted data with `load()`** \u2014 Directly deserializing untrusted data that may contain injected `\u0027lc\u0027` structures.\n3. **Use LangGraph checkpoints** \u2014 Checkpoint serialization/deserialization paths may be affected.\n\nThe 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.\n\n## Impact\n\nAttackers 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.\n\nKey severity factors:\n\n- Affects the serialization path\u2014applications trusting their own serialization output are vulnerable\n- Enables secret extraction when combined with `secretsFromEnv: true`\n- LLM responses in `additional_kwargs` can be controlled via prompt injection\n\n## Exploit example\n\n```typescript\nimport { load } from \"@langchain/core/load\";\n\n// Attacker injects secret structure into user-controlled data\nconst attackerPayload = JSON.stringify({\n  user_data: {\n    lc: 1,\n    type: \"secret\",\n    id: [\"OPENAI_API_KEY\"],\n  },\n});\n\nprocess.env.OPENAI_API_KEY = \"sk-secret-key-12345\";\n\n// With secretsFromEnv: true, the secret is extracted\nconst deserialized = await load(attackerPayload, { secretsFromEnv: true });\n\nconsole.log(deserialized.user_data); // \"sk-secret-key-12345\" - SECRET LEAKED!\n```\n\n## Security hardening changes\n\nThis patch introduces the following changes to `load()`:\n\n1. **`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`.\n2. **New `maxDepth` parameter** (defaults to `50`): Protects against denial-of-service attacks via deeply nested JSON structures that could cause stack overflow.\n3. **Escape mechanism in `toJSON()`**: User-controlled objects containing `\u0027lc\u0027` keys are now wrapped in `{\"__lc_escaped__\": {...}}` during serialization and unwrapped as plain data during deserialization.\n4. **JSDoc security warnings**: All import map options (`importMap`, `optionalImportsMap`, `optionalImportEntrypoints`) now include security warnings about never populating them from user input.\n\n## Migration guide\n\n### No changes needed for most users\n\nIf you\u0027re deserializing standard LangChain types (messages, documents, prompts) using the core import map, your code will work without changes:\n\n```typescript\nimport { load } from \"@langchain/core/load\";\n\n// Works with default settings\nconst obj = await load(serializedData);\n```\n\n### For secrets from environment\n\n`secretsFromEnv` now defaults to `false`, and missing secrets throw an error. If you need to load secrets:\n\n```typescript\nimport { load } from \"@langchain/core/load\";\n\n// Provide secrets explicitly (recommended)\nconst obj = await load(serializedData, {\n  secretsMap: { OPENAI_API_KEY: process.env.OPENAI_API_KEY },\n});\n\n// Or explicitly opt-in to load from env (only use with trusted data)\nconst obj = await load(serializedData, { secretsFromEnv: true });\n```\n\n\u003e **Warning:** Only enable `secretsFromEnv` if you trust the serialized data. Untrusted data could extract any environment variable.\n\n\u003e **Note:** If a secret reference is encountered but not found in `secretsMap` (and `secretsFromEnv` is `false` or the secret is not in the environment), an error is thrown. This fail-safe behavior ensures you\u0027re aware of missing secrets rather than silently receiving `null` values.\n\n### For deeply nested structures\n\nIf you have legitimate deeply nested data that exceeds the default depth limit of 50:\n\n```typescript\nimport { load } from \"@langchain/core/load\";\n\nconst obj = await load(serializedData, { maxDepth: 100 });\n```\n\n### For custom import maps\n\nIf you provide custom import maps, ensure they only contain trusted modules:\n\n```typescript\nimport { load } from \"@langchain/core/load\";\nimport * as myModule from \"./my-trusted-module\";\n\n// GOOD - explicitly include only trusted modules\nconst obj = await load(serializedData, {\n  importMap: { my_module: myModule },\n});\n\n// BAD - never populate from user input\nconst obj = await load(serializedData, {\n  importMap: userProvidedImports, // DANGEROUS!\n});\n```",
  "id": "GHSA-r399-636x-v7f6",
  "modified": "2025-12-24T01:08:11Z",
  "published": "2025-12-23T20:08:48Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/langchain-ai/langchainjs/security/advisories/GHSA-r399-636x-v7f6"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-68665"
    },
    {
      "type": "WEB",
      "url": "https://github.com/langchain-ai/langchainjs/commit/e5063f9c6e9989ea067dfdff39262b9e7b6aba62"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/langchain-ai/langchainjs"
    },
    {
      "type": "WEB",
      "url": "https://github.com/langchain-ai/langchainjs/releases/tag/%40langchain%2Fcore%401.1.8"
    },
    {
      "type": "WEB",
      "url": "https://github.com/langchain-ai/langchainjs/releases/tag/langchain%401.2.3"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ],
  "summary": "LangChain serialization injection vulnerability enables secret extraction"
}