CWE-502
AllowedDeserialization of Untrusted Data
Abstraction: Base · Status: Draft
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
4837 vulnerabilities reference this CWE, most recent first.
GHSA-34WM-4HW7-QFJV
Vulnerability from github – Published: 2026-01-01 09:30 – Updated: 2026-01-02 15:54A high-severity remote code execution vulnerability exists in feast-dev/feast version 0.53.0, specifically in the Kubernetes materializer job located at feast/sdk/python/feast/infra/compute_engines/kubernetes/main.py. The vulnerability arises from the use of yaml.load(..., Loader=yaml.Loader) to deserialize /var/feast/feature_store.yaml and /var/feast/materialization_config.yaml. This method allows for the instantiation of arbitrary Python objects, enabling an attacker with the ability to modify these YAML files to execute OS commands on the worker pod. This vulnerability can be exploited before the configuration is validated, potentially leading to cluster takeover, data poisoning, and supply-chain sabotage.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "feast"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.54.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-11157"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": true,
"github_reviewed_at": "2026-01-02T15:54:13Z",
"nvd_published_at": "2026-01-01T07:16:00Z",
"severity": "HIGH"
},
"details": "A high-severity remote code execution vulnerability exists in feast-dev/feast version 0.53.0, specifically in the Kubernetes materializer job located at `feast/sdk/python/feast/infra/compute_engines/kubernetes/main.py`. The vulnerability arises from the use of `yaml.load(..., Loader=yaml.Loader)` to deserialize `/var/feast/feature_store.yaml` and `/var/feast/materialization_config.yaml`. This method allows for the instantiation of arbitrary Python objects, enabling an attacker with the ability to modify these YAML files to execute OS commands on the worker pod. This vulnerability can be exploited before the configuration is validated, potentially leading to cluster takeover, data poisoning, and supply-chain sabotage.",
"id": "GHSA-34wm-4hw7-qfjv",
"modified": "2026-01-02T15:54:13Z",
"published": "2026-01-01T09:30:14Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-11157"
},
{
"type": "WEB",
"url": "https://github.com/feast-dev/feast/pull/5643"
},
{
"type": "WEB",
"url": "https://github.com/feast-dev/feast/commit/b2e37ff37953b68ae833f6874ab5bc510a4ca5fb"
},
{
"type": "PACKAGE",
"url": "https://github.com/feast-dev/feast"
},
{
"type": "WEB",
"url": "https://huntr.com/bounties/46d4d585-b968-4a76-80ce-872bc5525564"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
],
"summary": "Feast vulnerable to Deserialization of Untrusted Data"
}
GHSA-34WX-X2W9-VQM3
Vulnerability from github – Published: 2022-02-10 00:00 – Updated: 2023-12-22 13:51Jenkins 2.333 and earlier, LTS 2.319.2 and earlier is affected by the XStream library’s vulnerability CVE-2021-43859. This library is used by Jenkins to serialize and deserialize various XML files, like global and job config.xml, build.xml, and numerous others.
This allows attackers able to submit crafted XML files to Jenkins to be parsed as configuration, e.g. through the POST config.xml API, to cause a denial of service (DoS).
{
"affected": [
{
"package": {
"ecosystem": "Maven",
"name": "org.jenkins-ci.main:jenkins-core"
},
"ranges": [
{
"events": [
{
"introduced": "2.320"
},
{
"fixed": "2.334"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Maven",
"name": "org.jenkins-ci.main:jenkins-core"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.319.3"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2022-0538"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": true,
"github_reviewed_at": "2022-06-20T22:50:31Z",
"nvd_published_at": "2022-02-09T14:15:00Z",
"severity": "MODERATE"
},
"details": "Jenkins 2.333 and earlier, LTS 2.319.2 and earlier is affected by the XStream library\u2019s vulnerability [CVE-2021-43859](https://x-stream.github.io/CVE-2021-43859.html). This library is used by Jenkins to serialize and deserialize various XML files, like global and job `config.xml`, `build.xml`, and numerous others.\n\nThis allows attackers able to submit crafted XML files to Jenkins to be parsed as configuration, e.g. through the `POST config.xml` API, to cause a denial of service (DoS).",
"id": "GHSA-34wx-x2w9-vqm3",
"modified": "2023-12-22T13:51:07Z",
"published": "2022-02-10T00:00:30Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-0538"
},
{
"type": "WEB",
"url": "https://github.com/jenkinsci/jenkins/commit/8276aef4cc3dd81810fe6bdf6fa48141632c4636"
},
{
"type": "WEB",
"url": "https://www.jenkins.io/security/advisory/2022-02-09/#SECURITY-2602"
},
{
"type": "WEB",
"url": "http://www.openwall.com/lists/oss-security/2022/02/09/1"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "DoS vulnerability in bundled XStream library in Jenkins Core"
}
GHSA-352X-HC2F-FWFF
Vulnerability from github – Published: 2022-05-24 16:56 – Updated: 2023-07-17 21:24In Pimcore before 5.7.1, an attacker with limited privileges can trigger execution of a .phar file via a phar:// URL in a filename parameter, because PHAR uploads are not blocked and are reachable within the phar://../../../../../../../../var/www/html/web/var/assets/ directory, a different vulnerability than CVE-2019-10867 and CVE-2019-16318.
{
"affected": [
{
"package": {
"ecosystem": "Packagist",
"name": "pimcore/pimcore"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "5.7.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2019-16317"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": true,
"github_reviewed_at": "2023-07-17T21:24:27Z",
"nvd_published_at": "2019-09-14T18:15:00Z",
"severity": "HIGH"
},
"details": "In Pimcore before 5.7.1, an attacker with limited privileges can trigger execution of a .phar file via a `phar://` URL in a filename parameter, because PHAR uploads are not blocked and are reachable within the `phar://../../../../../../../../var/www/html/web/var/assets/` directory, a different vulnerability than CVE-2019-10867 and CVE-2019-16318.",
"id": "GHSA-352x-hc2f-fwff",
"modified": "2023-07-17T21:24:27Z",
"published": "2022-05-24T16:56:12Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2019-16317"
},
{
"type": "WEB",
"url": "https://github.com/pimcore/pimcore/commit/6ee5d8536d0802e377594cbe39083e822710aab9"
},
{
"type": "WEB",
"url": "https://snyk.io/vuln/SNYK-PHP-PIMCOREPIMCORE-451599"
}
],
"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": "Pimcore RCE via PHAR upload"
}
GHSA-3533-R6PG-9GHX
Vulnerability from github – Published: 2025-09-09 18:31 – Updated: 2026-04-01 18:36Deserialization of Untrusted Data vulnerability in ThemeMove ThemeMove Core allows Object Injection. This issue affects ThemeMove Core: from n/a through 1.4.2.
{
"affected": [],
"aliases": [
"CVE-2025-53303"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-09-09T17:15:48Z",
"severity": "HIGH"
},
"details": "Deserialization of Untrusted Data vulnerability in ThemeMove ThemeMove Core allows Object Injection. This issue affects ThemeMove Core: from n/a through 1.4.2.",
"id": "GHSA-3533-r6pg-9ghx",
"modified": "2026-04-01T18:36:08Z",
"published": "2025-09-09T18:31:19Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-53303"
},
{
"type": "WEB",
"url": "https://patchstack.com/database/wordpress/plugin/thememove-core/vulnerability/wordpress-thememove-core-plugin-1-4-2-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:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-354X-P5RW-9F85
Vulnerability from github – Published: 2026-07-01 00:34 – Updated: 2026-07-01 00:34picklescan before 0.0.30 fails to detect the doctest.debug_script function when analyzing pickle files, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files embedding doctest.debug_script calls that bypass picklescan detection and execute arbitrary commands upon pickle.load invocation.
{
"affected": [],
"aliases": [
"CVE-2025-71368"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-06-30T23:16:51Z",
"severity": "HIGH"
},
"details": "picklescan before 0.0.30 fails to detect the doctest.debug_script function when analyzing pickle files, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files embedding doctest.debug_script calls that bypass picklescan detection and execute arbitrary commands upon pickle.load invocation.",
"id": "GHSA-354x-p5rw-9f85",
"modified": "2026-07-01T00:34:01Z",
"published": "2026-07-01T00:34:01Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/mmaitre314/picklescan/security/advisories/GHSA-fqq6-7vqf-w3fg"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-71368"
},
{
"type": "WEB",
"url": "https://www.vulncheck.com/advisories/picklescan-arbitrary-code-execution-via-undetected-doctest-debug-script"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"type": "CVSS_V4"
}
]
}
GHSA-356Q-QCQM-44CG
Vulnerability from github – Published: 2026-06-17 18:35 – Updated: 2026-06-17 18:35Unauthenticated PHP Object Injection in NeoBeat <= 1.7 versions.
{
"affected": [],
"aliases": [
"CVE-2026-39557"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-06-17T13:20:20Z",
"severity": "HIGH"
},
"details": "Unauthenticated PHP Object Injection in NeoBeat \u003c= 1.7 versions.",
"id": "GHSA-356q-qcqm-44cg",
"modified": "2026-06-17T18:35:49Z",
"published": "2026-06-17T18:35:49Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-39557"
},
{
"type": "WEB",
"url": "https://patchstack.com/database/wordpress/theme/neobeat/vulnerability/wordpress-neobeat-theme-1-7-php-object-injection-vulnerability?_s_id=cve"
}
],
"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"
}
]
}
GHSA-358M-FQ53-HP87
Vulnerability from github – Published: 2025-06-29 00:30 – Updated: 2025-06-30 21:21In Akka through 2.10.6, akka-cluster-metrics uses Java serialization for cluster metrics.
{
"affected": [
{
"package": {
"ecosystem": "Maven",
"name": "com.typesafe.akka:akka-cluster-metrics_3"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"last_affected": "2.10.6"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "Maven",
"name": "com.typesafe.akka:akka-cluster-metrics_2.13"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"last_affected": "2.10.6"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-53393"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": true,
"github_reviewed_at": "2025-06-30T21:21:59Z",
"nvd_published_at": "2025-06-28T23:15:21Z",
"severity": "MODERATE"
},
"details": "In Akka through 2.10.6, akka-cluster-metrics uses Java serialization for cluster metrics.",
"id": "GHSA-358m-fq53-hp87",
"modified": "2025-06-30T21:21:59Z",
"published": "2025-06-29T00:30:19Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-53393"
},
{
"type": "WEB",
"url": "https://github.com/akka/akka/pull/32748"
},
{
"type": "WEB",
"url": "https://github.com/akka/akka/commit/d69a082abfa26ccc076f090a6486ccfee9d7c481"
},
{
"type": "PACKAGE",
"url": "https://github.com/akka/akka"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:L/I:L/A:L",
"type": "CVSS_V3"
}
],
"summary": "akka-cluster-metrics uses Java serialization for cluster metrics"
}
GHSA-35CH-876F-6MW7
Vulnerability from github – Published: 2025-05-14 03:30 – Updated: 2025-05-14 03:30The Uncanny Automator plugin for WordPress is vulnerable to PHP Object Injection in all versions up to, and including, 6.4.0.1 via deserialization of untrusted input in the automator_api_decode_message() function. This makes it possible for authenticated attackers, with Subscriber-level access and above, to inject a PHP Object. The additional presence of a POP chain allows attackers to delete arbitrary files.
{
"affected": [],
"aliases": [
"CVE-2025-3623"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-05-14T03:15:33Z",
"severity": "HIGH"
},
"details": "The Uncanny Automator plugin for WordPress is vulnerable to PHP Object Injection in all versions up to, and including, 6.4.0.1 via deserialization of untrusted input in the automator_api_decode_message() function. This makes it possible for authenticated attackers, with Subscriber-level access and above, to inject a PHP Object. The additional presence of a POP chain allows attackers to delete arbitrary files.",
"id": "GHSA-35ch-876f-6mw7",
"modified": "2025-05-14T03:30:31Z",
"published": "2025-05-14T03:30:31Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-3623"
},
{
"type": "WEB",
"url": "https://automatorplugin.com/knowledge-base/uncanny-automator-changelog/#6-4-0-2-2025-04-18"
},
{
"type": "WEB",
"url": "https://plugins.trac.wordpress.org/browser/uncanny-automator/trunk/src/core/lib/helpers/class-automator-recipe-helpers.php#L540"
},
{
"type": "WEB",
"url": "https://plugins.trac.wordpress.org/changeset/3276577/uncanny-automator/trunk/src/core/lib/helpers/class-automator-recipe-helpers.php"
},
{
"type": "WEB",
"url": "https://wordpress.org/plugins/uncanny-automator/#developers"
},
{
"type": "WEB",
"url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/00bcfd8f-9785-449a-a0ea-16e2583d684a?source=cve"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-35QX-QJJJ-9PFH
Vulnerability from github – Published: 2025-08-22 18:31 – Updated: 2025-08-22 21:31OperaMasks SDK ELite Script Engine v0.5.0 was discovered to contain a deserialization vulnerability.
{
"affected": [],
"aliases": [
"CVE-2025-52287"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-08-22T18:15:35Z",
"severity": "HIGH"
},
"details": "OperaMasks SDK ELite Script Engine v0.5.0 was discovered to contain a deserialization vulnerability.",
"id": "GHSA-35qx-qjjj-9pfh",
"modified": "2025-08-22T21:31:15Z",
"published": "2025-08-22T18:31:24Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-52287"
},
{
"type": "WEB",
"url": "https://gist.github.com/ChangeYourWay/5bf54a234611f14fba1af03ad91e62f8"
},
{
"type": "WEB",
"url": "https://github.com/ChangeYourWay/post/blob/main/ELite"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
GHSA-3644-Q5CJ-C5C7
Vulnerability from github – Published: 2026-05-13 15:29 – Updated: 2026-06-08 23:54Description
The LangSmith SDK's prompt pull methods (pull_prompt / pull_prompt_commit in Python, pullPrompt / pullPromptCommit in JS/TS) fetch and deserialize prompt manifests from the LangSmith Hub. These manifests may contain serialized LangChain objects and model configuration that affect runtime behavior. When pulling a public prompt by owner/name identifier, the manifest content is controlled by an external party, but prior versions of the SDK did not distinguish this from pulling a prompt within the caller's own organization.
Prompt manifests can intentionally configure a model with a custom base URL, default headers, model name, or other constructor arguments. These are supported features, but they also mean the prompt contents should be treated as executable configuration rather than plain text. A prompt can also include serialized LangChain Runnable or PromptTemplate objects with attacker-controlled constructor kwargs, or secret references that, if secrets_from_env is enabled, read environment variables at deserialization time.
Applications are exposed when all of the following are true:
- The application calls
pull_promptorpull_prompt_commit(Python) orpullPromptorpullPromptCommit(JS/TS) with a publicowner/nameprompt identifier. - The prompt was published or modified by an untrusted or compromised account.
- The application uses the pulled prompt without independently validating its contents.
Applications that only pull prompts from their own organization (referenced by name only, without an owner/ prefix) are not affected by the public prompt trust boundary issue described above. However, same-organization prompts carry their own risk. If an attacker gains write access to the organization (for example, through a leaked LANGSMITH_API_KEY or a compromised team member account), they can push a malicious prompt that is pulled and deserialized without any additional warning.
Impact
An attacker who publishes a malicious prompt to LangSmith Hub may be able to affect applications that pull that prompt by owner/name. If the prompt manifest reaches the SDK's deserialization path, the SDK will instantiate the referenced LangChain objects with the attacker-supplied constructor arguments rather than treating the manifest as inert data.
Realistic impacts include:
- Server-side request forgery (SSRF), outbound request redirection, and interception of LLM traffic if a prompt manifest configures an LLM client with an attacker-controlled
base_url, proxy, or equivalent endpoint-setting parameter. In typical deployments, redirected requests may include prompt contents, system prompts, retrieved context, model parameters, provider credentials, or other secrets and may disclose them to the attacker-controlled endpoint. - Prompt injection or behavior manipulation if a manifest embeds attacker-controlled system messages, prompt templates, or model parameters that alter the application's behavior.
- Additional deserialization risk when
include_model=Trueis passed, because this expands the allowlist to partner integration classes. This is not the default, but it materially increases risk when pulling prompts from outside the caller's organization.
Remediation
The LangSmith SDK now blocks pulling public prompts by owner/name by default. Callers must explicitly opt in by passing dangerously_pull_public_prompt=True (Python) or dangerouslyPullPublicPrompt: true (JS/TS) to acknowledge the trust boundary. This flag should only be set after reviewing and trusting the prompt contents, not merely the publishing account.
Upgrade to LangSmith SDK Python >= 0.8.0 or JS/TS >= 0.6.0.
Guidance for prompt pull methods
The prompt pull methods (pull_prompt / pull_prompt_commit in Python, pullPrompt / pullPromptCommit in JS/TS) should be used only with trusted prompts. Do not pull public prompts by owner/name from untrusted or unreviewed sources without understanding that the manifest contents will be deserialized and may affect runtime behavior.
When pulling prompts that include model configuration (include_model=True in Python, includeModel: true in JS/TS), the deserialization allowlist expands to include partner integration classes. Because this mode is not the default and is often unnecessary for third-party prompts, prefer the default (false) when pulling prompts from sources outside your organization.
Avoid passing secrets_from_env=True (Python) when pulling untrusted prompts. This parameter allows prompt manifests to read environment variables during deserialization. Only use it with trusted prompts from your own organization.
Same-organization prompts
Prompts pulled from the caller's own organization (referenced by name only, without an owner/ prefix) are not gated by the new dangerously_pull_public_prompt flag, but they are not inherently safe. If an attacker gains write access to the organization (for example, through a leaked LANGSMITH_API_KEY or a compromised team member account), they can push a malicious prompt that redirects LLM traffic to attacker-controlled infrastructure and may disclose any credentials attached to those requests.
The security of same-organization prompts follows a shared responsibility model. The LangSmith SDK enforces trust boundaries for public prompts pulled from external accounts, but it cannot protect against compromised credentials or accounts within the caller's own organization. Securing API keys, managing team member access, and reviewing prompt contents before production deployment are the responsibility of the organization. Organizations should treat prompts as executable configuration and apply the same review and audit practices they would apply to application code.
Credits
First reported by @Moaaz-0x.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "langsmith"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.8.0"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "npm",
"name": "langsmith"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.6.0"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "langchain-classic"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.0.7"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "langchain"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.3.30"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-45134"
],
"database_specific": {
"cwe_ids": [
"CWE-502"
],
"github_reviewed": true,
"github_reviewed_at": "2026-05-13T15:29:30Z",
"nvd_published_at": "2026-05-27T20:16:38Z",
"severity": "HIGH"
},
"details": "## Description\n\nThe LangSmith SDK\u0027s prompt pull methods (`pull_prompt` / `pull_prompt_commit` in Python, `pullPrompt` / `pullPromptCommit` in JS/TS) fetch and deserialize prompt manifests from the LangSmith Hub. These manifests may contain serialized LangChain objects and model configuration that affect runtime behavior. When pulling a public prompt by `owner/name` identifier, the manifest content is controlled by an external party, but prior versions of the SDK did not distinguish this from pulling a prompt within the caller\u0027s own organization.\n\nPrompt manifests can intentionally configure a model with a custom base URL, default headers, model name, or other constructor arguments. These are supported features, but they also mean the prompt contents should be treated as executable configuration rather than plain text. A prompt can also include serialized LangChain `Runnable` or `PromptTemplate` objects with attacker-controlled constructor kwargs, or secret references that, if `secrets_from_env` is enabled, read environment variables at deserialization time.\nApplications are exposed when all of the following are true:\n\n- The application calls `pull_prompt` or `pull_prompt_commit` (Python) or `pullPrompt` or `pullPromptCommit` (JS/TS) with a public `owner/name` prompt identifier.\n- The prompt was published or modified by an untrusted or compromised account.\n- The application uses the pulled prompt without independently validating its contents.\n\nApplications that only pull prompts from their own organization (referenced by name only, without an `owner/` prefix) are not affected by the public prompt trust boundary issue described above. However, same-organization prompts carry their own risk. If an attacker gains write access to the organization (for example, through a leaked `LANGSMITH_API_KEY` or a compromised team member account), they can push a malicious prompt that is pulled and deserialized without any additional warning.\n\n## Impact\n\nAn attacker who publishes a malicious prompt to LangSmith Hub may be able to affect applications that pull that prompt by `owner/name`. If the prompt manifest reaches the SDK\u0027s deserialization path, the SDK will instantiate the referenced LangChain objects with the attacker-supplied constructor arguments rather than treating the manifest as inert data.\n\nRealistic impacts include:\n\n- Server-side request forgery (SSRF), outbound request redirection, and interception of LLM traffic if a prompt manifest configures an LLM client with an attacker-controlled `base_url`, proxy, or equivalent endpoint-setting parameter. In typical deployments, redirected requests may include prompt contents, system prompts, retrieved context, model parameters, provider credentials, or other secrets and may disclose them to the attacker-controlled endpoint.\n- Prompt injection or behavior manipulation if a manifest embeds attacker-controlled system messages, prompt templates, or model parameters that alter the application\u0027s behavior.\n- Additional deserialization risk when `include_model=True` is passed, because this expands the allowlist to partner integration classes. This is not the default, but it materially increases risk when pulling prompts from outside the caller\u0027s organization.\n\n## Remediation\n\nThe LangSmith SDK now blocks pulling public prompts by `owner/name` by default. Callers must explicitly opt in by passing `dangerously_pull_public_prompt=True` (Python) or `dangerouslyPullPublicPrompt: true` (JS/TS) to acknowledge the trust boundary. This flag should only be set after reviewing and trusting the prompt contents, not merely the publishing account.\n\nUpgrade to LangSmith SDK **Python \u003e= 0.8.0** or **JS/TS \u003e= 0.6.0**.\n\n### Guidance for prompt pull methods\n\nThe prompt pull methods (`pull_prompt` / `pull_prompt_commit` in Python, `pullPrompt` / `pullPromptCommit` in JS/TS) should be used only with trusted prompts. Do not pull public prompts by `owner/name` from untrusted or unreviewed sources without understanding that the manifest contents will be deserialized and may affect runtime behavior.\n\nWhen pulling prompts that include model configuration (`include_model=True` in Python, `includeModel: true` in JS/TS), the deserialization allowlist expands to include partner integration classes. Because this mode is not the default and is often unnecessary for third-party prompts, prefer the default (`false`) when pulling prompts from sources outside your organization.\n\nAvoid passing `secrets_from_env=True` (Python) when pulling untrusted prompts. This parameter allows prompt manifests to read environment variables during deserialization. Only use it with trusted prompts from your own organization.\n\n### Same-organization prompts\n\nPrompts pulled from the caller\u0027s own organization (referenced by name only, without an `owner/` prefix) are not gated by the new `dangerously_pull_public_prompt` flag, but they are not inherently safe. If an attacker gains write access to the organization (for example, through a leaked `LANGSMITH_API_KEY` or a compromised team member account), they can push a malicious prompt that redirects LLM traffic to attacker-controlled infrastructure and may disclose any credentials attached to those requests.\n\nThe security of same-organization prompts follows a shared responsibility model. The LangSmith SDK enforces trust boundaries for public prompts pulled from external accounts, but it cannot protect against compromised credentials or accounts within the caller\u0027s own organization. Securing API keys, managing team member access, and reviewing prompt contents before production deployment are the responsibility of the organization. Organizations should treat prompts as executable configuration and apply the same review and audit practices they would apply to application code.\n\n## Credits\n\nFirst reported by @Moaaz-0x.",
"id": "GHSA-3644-q5cj-c5c7",
"modified": "2026-06-08T23:54:03Z",
"published": "2026-05-13T15:29:30Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/langchain-ai/langsmith-sdk/security/advisories/GHSA-3644-q5cj-c5c7"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-45134"
},
{
"type": "PACKAGE",
"url": "https://github.com/langchain-ai/langsmith-sdk"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:L/A:N",
"type": "CVSS_V3"
}
],
"summary": "LangSmith SDK: Public prompt pull deserializes untrusted manifests without trust boundary warning"
}
Mitigation
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
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
Explicitly define a final object() to prevent deserialization.
Mitigation
- 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
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
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
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.