Common Weakness Enumeration

CWE-502

Allowed

Deserialization of Untrusted Data

Abstraction: Base · Status: Draft

API response cwe.mitre.org

The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

4802 vulnerabilities reference this CWE, most recent first.

GHSA-R33W-FG8J-9C94

Vulnerability from github – Published: 2026-02-12 22:11 – Updated: 2026-02-12 22:11
VLAI
Summary
MagicLink: Insecure Deserialization of MagicLink Actions Leads to Remote Code Execution
Details

Description

MagicLink stores serialized action objects in the magic_links.action database column and deserializes them without integrity validation or class allowlisting in src/MagicLink.php and src/Actions/ResponseAction.php. An attacker with the ability to manipulate database records (e.g., via SQL injection or compromised admin access) could inject malicious serialized objects containing arbitrary closures, leading to Remote Code Execution (RCE) when the magic link is visited.

Resolution

The vulnerability has been mitigated through HMAC-signed serialization using the application key, class allowlisting restricted to ActionAbstract subclasses and framework classes, strict type validation preventing arbitrary object storage, and backward compatibility support for legacy data via allowed_classes in unserialize(). Implementation includes a new Serializable security class with signing/verification, refactored getter/setter methods in MagicLink.

Severity
8.8 (High)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
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{
  "affected": [
    {
      "package": {
        "ecosystem": "Packagist",
        "name": "cesargb/laravel-magiclink"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.25.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-02-12T22:11:56Z",
    "nvd_published_at": null,
    "severity": "HIGH"
  },
  "details": "## Description\n\nMagicLink stores serialized action objects in the `magic_links.action` database column and deserializes them without integrity validation or class allowlisting in [src/MagicLink.php](src/MagicLink.php#L59-L77) and [src/Actions/ResponseAction.php](src/Actions/ResponseAction.php#L64-L77). An attacker with the ability to manipulate database records (e.g., via SQL injection or compromised admin access) could inject malicious serialized objects containing arbitrary closures, leading to Remote Code Execution (RCE) when the magic link is visited.\n\n## Resolution\n\nThe vulnerability has been mitigated through HMAC-signed serialization using the application key, class allowlisting restricted to `ActionAbstract` subclasses and framework classes, strict type validation preventing arbitrary object storage, and backward compatibility support for legacy data via `allowed_classes` in `unserialize()`. Implementation includes a new [Serializable](src/Security/Serializable/Serializable.php) security class with signing/verification, refactored getter/setter methods in MagicLink.",
  "id": "GHSA-r33w-fg8j-9c94",
  "modified": "2026-02-12T22:11:56Z",
  "published": "2026-02-12T22:11:56Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/cesargb/laravel-magiclink/security/advisories/GHSA-r33w-fg8j-9c94"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/cesargb/laravel-magiclink"
    },
    {
      "type": "WEB",
      "url": "https://github.com/cesargb/laravel-magiclink/releases/tag/v2.25.1"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "MagicLink: Insecure Deserialization of MagicLink Actions Leads to Remote Code Execution"
}

GHSA-R38R-QP28-2M63

Vulnerability from github – Published: 2018-07-26 16:08 – Updated: 2024-10-21 21:29
VLAI
Summary
Code injection in rope
Details

base/oi/doa.py in the Rope library in CPython (aka Python) allows remote attackers to execute arbitrary code by leveraging an unsafe call to pickle.load.

Severity
9.8 (Critical)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
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{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "rope"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.11.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2014-3539"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2020-06-16T21:53:34Z",
    "nvd_published_at": null,
    "severity": "CRITICAL"
  },
  "details": "base/oi/doa.py in the Rope library in CPython (aka Python) allows remote attackers to execute arbitrary code by leveraging an unsafe call to pickle.load.",
  "id": "GHSA-r38r-qp28-2m63",
  "modified": "2024-10-21T21:29:55Z",
  "published": "2018-07-26T16:08:49Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2014-3539"
    },
    {
      "type": "WEB",
      "url": "https://github.com/python-rope/rope/commit/b01da7aab5cd02129941d2a900e6e5e3b5f7d4fb"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=1116485"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/rope/PYSEC-2018-100.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/python-rope/rope"
    },
    {
      "type": "WEB",
      "url": "http://www.openwall.com/lists/oss-security/2015/02/07/1"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Code injection in rope"
}

GHSA-R399-636X-V7F6

Vulnerability from github – Published: 2025-12-23 20:08 – Updated: 2025-12-24 01:08
VLAI
Summary
LangChain serialization injection vulnerability enables secret extraction
Details

Context

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.

Attack surface

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.

Who is affected?

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.

Impact

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:

  • Affects the serialization path—applications trusting their own serialization output are vulnerable
  • Enables secret extraction when combined with secretsFromEnv: true
  • LLM responses in additional_kwargs can be controlled via prompt injection

Exploit example

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!

Security hardening changes

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 stack overflow.
  3. Escape mechanism in toJSON(): User-controlled objects containing 'lc' keys are now wrapped in {"__lc_escaped__": {...}} during serialization and unwrapped as plain data during deserialization.
  4. JSDoc security warnings: All import map options (importMap, optionalImportsMap, optionalImportEntrypoints) now include security warnings about never populating them from user input.

Migration guide

No changes needed for most users

If you're deserializing standard LangChain types (messages, documents, prompts) using the core import map, your code will work without changes:

import { load } from "@langchain/core/load";

// Works with default settings
const obj = await load(serializedData);

For secrets from environment

secretsFromEnv now defaults to false, and missing secrets throw an error. If you need to load secrets:

import { load } from "@langchain/core/load";

// Provide secrets explicitly (recommended)
const obj = await load(serializedData, {
  secretsMap: { OPENAI_API_KEY: process.env.OPENAI_API_KEY },
});

// Or explicitly opt-in to load from env (only use with trusted data)
const obj = await load(serializedData, { secretsFromEnv: true });

Warning: Only enable secretsFromEnv if you trust the serialized data. Untrusted data could extract any environment variable.

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're aware of missing secrets rather than silently receiving null values.

For deeply nested structures

If you have legitimate deeply nested data that exceeds the default depth limit of 50:

import { load } from "@langchain/core/load";

const obj = await load(serializedData, { maxDepth: 100 });

For custom import maps

If you provide custom import maps, ensure they only contain trusted modules:

import { load } from "@langchain/core/load";
import * as myModule from "./my-trusted-module";

// GOOD - explicitly include only trusted modules
const obj = await load(serializedData, {
  importMap: { my_module: myModule },
});

// BAD - never populate from user input
const obj = await load(serializedData, {
  importMap: userProvidedImports, // DANGEROUS!
});
Severity
8.6 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Show details on source website
To clipboard 

{
  "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"
}

GHSA-R3GR-CXRF-HG25

Vulnerability from github – Published: 2021-12-09 19:15 – Updated: 2024-06-25 13:47
VLAI
Summary
Serialization gadgets exploit in jackson-databind
Details

FasterXML jackson-databind 2.x before 2.9.10.8 mishandles the interaction between serialization gadgets and typing, related to org.apache.commons.dbcp2.datasources.SharedPoolDataSource.

Severity
8.1 (High)
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
Show details on source website
To clipboard 

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 2.9.10.7"
      },
      "package": {
        "ecosystem": "Maven",
        "name": "com.fasterxml.jackson.core:jackson-databind"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.9.10.8"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2020-35491"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502",
      "CWE-913"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-04-08T21:05:38Z",
    "nvd_published_at": "2020-12-17T19:15:00Z",
    "severity": "HIGH"
  },
  "details": "FasterXML jackson-databind 2.x before 2.9.10.8 mishandles the interaction between serialization gadgets and typing, related to org.apache.commons.dbcp2.datasources.SharedPoolDataSource.",
  "id": "GHSA-r3gr-cxrf-hg25",
  "modified": "2024-06-25T13:47:22Z",
  "published": "2021-12-09T19:15:11Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-35491"
    },
    {
      "type": "WEB",
      "url": "https://github.com/FasterXML/jackson-databind/issues/2986"
    },
    {
      "type": "WEB",
      "url": "https://github.com/FasterXML/jackson-databind/commit/41b8bdb5ccc1d8edb71acf1c8234da235a24249d"
    },
    {
      "type": "WEB",
      "url": "https://cowtowncoder.medium.com/on-jackson-cves-dont-panic-here-is-what-you-need-to-know-54cd0d6e8062"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/FasterXML/jackson-databind"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2021/04/msg00025.html"
    },
    {
      "type": "WEB",
      "url": "https://security.netapp.com/advisory/ntap-20210122-0005"
    },
    {
      "type": "WEB",
      "url": "https://www.oracle.com//security-alerts/cpujul2021.html"
    },
    {
      "type": "WEB",
      "url": "https://www.oracle.com/security-alerts/cpuApr2021.html"
    },
    {
      "type": "WEB",
      "url": "https://www.oracle.com/security-alerts/cpuapr2022.html"
    },
    {
      "type": "WEB",
      "url": "https://www.oracle.com/security-alerts/cpujan2022.html"
    },
    {
      "type": "WEB",
      "url": "https://www.oracle.com/security-alerts/cpujul2022.html"
    },
    {
      "type": "WEB",
      "url": "https://www.oracle.com/security-alerts/cpuoct2021.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Serialization gadgets exploit in jackson-databind"
}

GHSA-R438-MXG9-X66P

Vulnerability from github – Published: 2024-06-19 06:30 – Updated: 2024-06-19 06:30
VLAI
Details

The Universal Slider plugin for WordPress is vulnerable to PHP Object Injection in all versions up to, and including, 1.6.5 via deserialization of untrusted input 'fsl_get_gallery_value' function. This makes it possible for authenticated attackers, with Contributor-level access and above, to inject a PHP Object. No known POP chain is present in the vulnerable software. If a POP chain is present via an additional plugin or theme installed on the target system, it could allow the attacker to delete arbitrary files, retrieve sensitive data, or execute code.

Severity
5.4 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:N
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2024-5649"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-06-19T04:15:13Z",
    "severity": "MODERATE"
  },
  "details": "The Universal Slider plugin for WordPress is vulnerable to PHP Object Injection in all versions up to, and including, 1.6.5 via deserialization of untrusted input \u0027fsl_get_gallery_value\u0027 function. This makes it possible for authenticated attackers, with Contributor-level access and above, to inject a PHP Object. No known POP chain is present in the vulnerable software. If a POP chain is present via an additional plugin or theme installed on the target system, it could allow the attacker to delete arbitrary files, retrieve sensitive data, or execute code.",
  "id": "GHSA-r438-mxg9-x66p",
  "modified": "2024-06-19T06:30:35Z",
  "published": "2024-06-19T06:30:35Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-5649"
    },
    {
      "type": "WEB",
      "url": "https://plugins.trac.wordpress.org/browser/fusion-slider/trunk/fusion-slider.php#L692"
    },
    {
      "type": "WEB",
      "url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/8f8bd107-5459-4093-8593-deedec6ffcd6?source=cve"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:N",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-R469-7RXF-6JMG

Vulnerability from github – Published: 2025-08-27 18:31 – Updated: 2026-04-01 18:35
VLAI
Details

Deserialization of Untrusted Data vulnerability in enituretechnology Small Package Quotes – USPS Edition allows Object Injection. This issue affects Small Package Quotes – USPS Edition: from n/a through 1.3.9.

Severity
7.2 (High)
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2025-58218"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-08-27T18:15:50Z",
    "severity": "HIGH"
  },
  "details": "Deserialization of Untrusted Data vulnerability in enituretechnology Small Package Quotes \u2013 USPS Edition allows Object Injection. This issue affects Small Package Quotes \u2013 USPS Edition: from n/a through 1.3.9.",
  "id": "GHSA-r469-7rxf-6jmg",
  "modified": "2026-04-01T18:35:58Z",
  "published": "2025-08-27T18:31:56Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-58218"
    },
    {
      "type": "WEB",
      "url": "https://patchstack.com/database/wordpress/plugin/small-package-quotes-usps-edition/vulnerability/wordpress-small-package-quotes-usps-edition-plugin-1-3-9-php-object-injection-vulnerability?_s_id=cve"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-R477-VJ9R-595H

Vulnerability from github – Published: 2024-01-08 18:30 – Updated: 2026-04-28 21:33
VLAI
Details

Deserialization of Untrusted Data vulnerability in Gecka Gecka Terms Thumbnails.This issue affects Gecka Terms Thumbnails: from n/a through 1.1.

Severity
9.9 (Critical)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2023-52219"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-01-08T18:15:52Z",
    "severity": "CRITICAL"
  },
  "details": "Deserialization of Untrusted Data vulnerability in Gecka Gecka Terms Thumbnails.This issue affects Gecka Terms Thumbnails: from n/a through 1.1.",
  "id": "GHSA-r477-vj9r-595h",
  "modified": "2026-04-28T21:33:46Z",
  "published": "2024-01-08T18:30:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-52219"
    },
    {
      "type": "WEB",
      "url": "https://patchstack.com/database/vulnerability/gecka-terms-thumbnails/wordpress-gecka-terms-thumbnails-plugin-1-1-php-object-injection-vulnerability?_s_id=cve"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-R54C-2XMF-2CF3

Vulnerability from github – Published: 2025-07-31 14:05 – Updated: 2025-07-31 14:06
VLAI
Summary
MS SWIFT Deserialization RCE Vulnerability
Details

This appears to be a security vulnerability report describing a remote code execution (RCE) exploit in the ms-swift framework through malicious pickle deserialization in adapter model files. The vulnerability allows arbitrary command execution when loading specially crafted adapter models from ModelScope.

This occurs when using machine torch version < 2.6.0, while ms-swift accepts torch version >= 2.0

I. Detailed Description: 1. Install ms-swift

pip install ms-swift -U
  1. Start web-ui
swift web-ui --lang en

  1. After startup, you can access http://localhost:7860/ through your browser to see the launched fine-tuning framework program

  2. Upload an adapter model repository (cyjhhh/lora_adapter_4_llama3) on ModelScope, where the lora/adapter_model.bin file is generated through the following code:

import torch, pickle, os

class MaliciousPayload:
   def __reduce__(self):
       return (os.system, ("touch /tmp/malicious.txt",))  # Arbitrary command

malicious_data = {
   "v_head.summary.weight": MaliciousPayload(),
   "v_head.summary.bias": torch.randn(10)
}

if __name__ == "__main__":
   with open("adapter_model.bin", "wb") as f:
       pickle.dump(malicious_data, f)

  1. First training submission: First, fill in the required parameters in the LLM Training interface, including Model id and Dataset Code, and configure the following in the Other params section of Advanced settings

  2. Click Begin to submit. You can see the backend command running as follows

  3. By reading the ms-swift source code, swift.llm.model.utils#safe_snapshot_download() and modelscope.hub.utils.utils#get_cache_dir(), we can see that adapters are downloaded locally to the path ~/.cache/modelscope. Therefore, the complete local path for the specified remote adapters after download is:

~/.cache/modelscope/hub/models/cyjhhh/lora_adapter_4_llama3

Wait for the first submission program until the adapters download is complete, then you can click "kill running task" on the page to terminate the first training

  1. Second training submission, configure the page parameters as follows

Click submit to see the backend command running as follows

  1. After waiting for a while, you can see that torch.load() loaded the malicious adapter_model.bin file and successfully executed the command. Related execution information can also be seen in the log file corresponding to --logging_dir

  2. Note (Prerequisites) Requires machine torch version < 2.6.0, while ms-swift accepts torch version >= 2.0

II. Vulnerability Proof: 1. Remote downloaded adapter malicious model: [lora_adapter_4_llama3](https://www.modelscope.cn/models/cyjhhh/lora_adapter_4_llama3/files) 2. For the second training submission, it's recommended to follow the parameters shown in the screenshots above for reproduction, as it will validate the target modules specified in the base model and adapter config. If they don't match, the program will terminate early. It's also recommended to select the same dataset content as shown in the screenshots 3. This report only reproduces RCE for one entry point (single path). In reality, there are more than one path in the code that can cause deserialization RCE

III. Fix Solution:

SWIFT has disabled torch.load operations from 3.7 or later.

Author

Severity
6.6 (Medium)
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "ms-swift"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "last_affected": "3.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-07-31T14:05:13Z",
    "nvd_published_at": null,
    "severity": "MODERATE"
  },
  "details": "This appears to be a security vulnerability report describing a remote code execution (RCE) exploit in the ms-swift framework through malicious pickle deserialization in adapter model files. The vulnerability allows arbitrary command execution when loading specially crafted adapter models from ModelScope.\n\nThis occurs when using machine torch version \u003c 2.6.0, while ms-swift accepts torch version \u003e= 2.0\n\n**I. Detailed Description:**\n1. Install ms-swift\n```\npip install ms-swift -U\n```\n\n2. Start web-ui\n```\nswift web-ui --lang en\n```\n\n3. After startup, you can access [http://localhost:7860/](http://localhost:7860/) through your browser to see the launched fine-tuning framework program\n\n4. Upload an adapter model repository (cyjhhh/lora_adapter_4_llama3) on ModelScope, where the lora/adapter_model.bin file is generated through the following code:\n```python\nimport torch, pickle, os\n\nclass MaliciousPayload:\n   def __reduce__(self):\n       return (os.system, (\"touch /tmp/malicious.txt\",))  # Arbitrary command\n\nmalicious_data = {\n   \"v_head.summary.weight\": MaliciousPayload(),\n   \"v_head.summary.bias\": torch.randn(10)\n}\n\nif __name__ == \"__main__\":\n   with open(\"adapter_model.bin\", \"wb\") as f:\n       pickle.dump(malicious_data, f)\n```\n\n5. First training submission: First, fill in the required parameters in the LLM Training interface, including Model id and Dataset Code, and configure the following in the Other params section of Advanced settings\n\n6. Click Begin to submit. You can see the backend command running as follows\n\n7. By reading the ms-swift source code, swift.llm.model.utils#safe_snapshot_download() and modelscope.hub.utils.utils#get_cache_dir(), we can see that adapters are downloaded locally to the path ~/.cache/modelscope. Therefore, the complete local path for the specified remote adapters after download is:\n```\n~/.cache/modelscope/hub/models/cyjhhh/lora_adapter_4_llama3\n```\nWait for the first submission program until the adapters download is complete, then you can click \"kill running task\" on the page to terminate the first training\n\n8. Second training submission, configure the page parameters as follows\n\nClick submit to see the backend command running as follows\n\n9. After waiting for a while, you can see that torch.load() loaded the malicious adapter_model.bin file and successfully executed the command. Related execution information can also be seen in the log file corresponding to --logging_dir\n\n10. Note (Prerequisites)\nRequires machine torch version \u003c 2.6.0, while ms-swift accepts torch version \u003e= 2.0\n\n**II. Vulnerability Proof:**\n1. Remote downloaded adapter malicious model: [[lora_adapter_4_llama3](https://www.modelscope.cn/models/cyjhhh/lora_adapter_4_llama3/files)](https://www.modelscope.cn/models/cyjhhh/lora_adapter_4_llama3/files)\n2. For the second training submission, it\u0027s recommended to follow the parameters shown in the screenshots above for reproduction, as it will validate the target modules specified in the base model and adapter config. If they don\u0027t match, the program will terminate early. It\u0027s also recommended to select the same dataset content as shown in the screenshots\n3. This report only reproduces RCE for one entry point (single path). In reality, there are more than one path in the code that can cause deserialization RCE\n\n**III. Fix Solution:**\n```\nSWIFT has disabled torch.load operations from 3.7 or later.\n```\n\n## Author\n\n* Discovered by: [TencentAISec](https://github.com/TencentAISec)\n* Contact: *[security@tencent.com](mailto:security@tencent.com)*",
  "id": "GHSA-r54c-2xmf-2cf3",
  "modified": "2025-07-31T14:06:13Z",
  "published": "2025-07-31T14:05:13Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/modelscope/ms-swift/security/advisories/GHSA-r54c-2xmf-2cf3"
    },
    {
      "type": "WEB",
      "url": "https://github.com/modelscope/ms-swift/commit/cc47463bcd25a8720437cf945130f43052eec5e4"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/modelscope/ms-swift"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P",
      "type": "CVSS_V4"
    }
  ],
  "summary": "MS SWIFT Deserialization RCE Vulnerability"
}

GHSA-R57W-P77G-3J43

Vulnerability from github – Published: 2023-04-10 15:30 – Updated: 2025-02-11 18:31
VLAI
Details

The WP Meta SEO WordPress plugin before 4.5.5 does not validate image file paths before attempting to manipulate the image files, leading to a PHAR deserialization vulnerability. Furthermore, the plugin contains a gadget chain which may be used in certain configurations to achieve remote code execution.

Severity
8.8 (High)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2023-1381"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-04-10T15:15:00Z",
    "severity": "HIGH"
  },
  "details": "The WP Meta SEO WordPress plugin before 4.5.5 does not validate image file paths before attempting to manipulate the image files, leading to a PHAR deserialization vulnerability. Furthermore, the plugin contains a gadget chain which may be used in certain configurations to achieve remote code execution.",
  "id": "GHSA-r57w-p77g-3j43",
  "modified": "2025-02-11T18:31:00Z",
  "published": "2023-04-10T15:30:25Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-1381"
    },
    {
      "type": "WEB",
      "url": "https://blog.wpscan.com/uncovering-a-phar-deserialization-vulnerability-in-wp-meta-seo-and-escalating-to-rce"
    },
    {
      "type": "WEB",
      "url": "https://wpscan.com/vulnerability/f140a928-d297-4bd1-8552-bfebcedba536"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-R587-34PX-PC2P

Vulnerability from github – Published: 2026-03-05 06:30 – Updated: 2026-03-10 18:31
VLAI
Details

Deserialization of Untrusted Data vulnerability in maximsecudeal Secudeal Payments for Ecommerce secudeal-payments-for-ecommerce allows Object Injection.This issue affects Secudeal Payments for Ecommerce: from n/a through <= 1.1.

Severity
8.6 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2026-22471"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-03-05T06:16:20Z",
    "severity": "HIGH"
  },
  "details": "Deserialization of Untrusted Data vulnerability in maximsecudeal Secudeal Payments for Ecommerce secudeal-payments-for-ecommerce allows Object Injection.This issue affects Secudeal Payments for Ecommerce: from n/a through \u003c= 1.1.",
  "id": "GHSA-r587-34px-pc2p",
  "modified": "2026-03-10T18:31:14Z",
  "published": "2026-03-05T06:30:25Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22471"
    },
    {
      "type": "WEB",
      "url": "https://patchstack.com/database/Wordpress/Plugin/secudeal-payments-for-ecommerce/vulnerability/wordpress-secudeal-payments-for-ecommerce-plugin-1-1-php-object-injection-vulnerability?_s_id=cve"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L",
      "type": "CVSS_V3"
    }
  ]
}
Mitigation
Architecture and Design Implementation

If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.

Mitigation
Implementation

When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.

Mitigation
Implementation

Explicitly define a final object() to prevent deserialization.

Mitigation
Architecture and Design Implementation
  • Make fields transient to protect them from deserialization.
  • An attempt to serialize and then deserialize a class containing transient fields will result in NULLs where the transient data should be. This is an excellent way to prevent time, environment-based, or sensitive variables from being carried over and used improperly.
Mitigation
Implementation

Avoid having unnecessary types or gadgets (a sequence of instances and method invocations that can self-execute during the deserialization process, often found in libraries) available that can be leveraged for malicious ends. This limits the potential for unintended or unauthorized types and gadgets to be leveraged by the attacker. Add only acceptable classes to an allowlist. Note: new gadgets are constantly being discovered, so this alone is not a sufficient mitigation.

Mitigation
Architecture and Design Implementation

Employ cryptography of the data or code for protection. However, it's important to note that it would still be client-side security. This is risky because if the client is compromised then the security implemented on the client (the cryptography) can be bypassed.

Mitigation MIT-29
Operation

Strategy: Firewall

Use an application firewall that can detect attacks against this weakness. It can be beneficial in cases in which the code cannot be fixed (because it is controlled by a third party), as an emergency prevention measure while more comprehensive software assurance measures are applied, or to provide defense in depth [REF-1481].

CAPEC-586: Object Injection

An adversary attempts to exploit an application by injecting additional, malicious content during its processing of serialized objects. Developers leverage serialization in order to convert data or state into a static, binary format for saving to disk or transferring over a network. These objects are then deserialized when needed to recover the data/state. By injecting a malformed object into a vulnerable application, an adversary can potentially compromise the application by manipulating the deserialization process. This can result in a number of unwanted outcomes, including remote code execution.

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