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Python CVE-2026-34070

HIGH
Path Traversal (CWE-22)
2026-03-27 https://github.com/langchain-ai/langchain GHSA-qh6h-p6c9-ff54
7.5
CVSS 3.1
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CVSS VectorNVD

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
None
Availability
None

Lifecycle Timeline

3
Analysis Generated
Mar 27, 2026 - 19:45 vuln.today
Patch released
Mar 27, 2026 - 19:45 nvd
Patch available
CVE Published
Mar 27, 2026 - 19:45 nvd
HIGH 7.5

DescriptionNVD

Summary

Multiple functions in langchain_core.prompts.loading read files from paths embedded in deserialized config dicts without validating against directory traversal or absolute path injection. When an application passes user-influenced prompt configurations to load_prompt() or load_prompt_from_config(), an attacker can read arbitrary files on the host filesystem, constrained only by file-extension checks (.txt for templates, .json/.yaml for examples).

Note: The affected functions (load_prompt, load_prompt_from_config, and the .save() method on prompt classes) are undocumented legacy APIs. They are superseded by the dumpd/dumps/load/loads serialization APIs in langchain_core.load, which do not perform filesystem reads and use an allowlist-based security model. As part of this fix, the legacy APIs have been formally deprecated and will be removed in 2.0.0.

Affected component

Package: langchain-core File: langchain_core/prompts/loading.py Affected functions: _load_template(), _load_examples(), _load_few_shot_prompt()

Severity

High

The score reflects the file-extension constraints that limit which files can be read.

Vulnerable code paths

Config keyLoaded byReadable extensions
template_path, suffix_path, prefix_path_load_template().txt
examples (when string)_load_examples().json, .yaml, .yml
example_prompt_path_load_few_shot_prompt().json, .yaml, .yml

None of these code paths validated the supplied path against absolute path injection or .. traversal sequences before reading from disk.

Impact

An attacker who controls or influences the prompt configuration dict can read files outside the intended directory:

  • .txt files: cloud-mounted secrets (/mnt/secrets/api_key.txt), requirements.txt, internal system prompts
  • .json/.yaml files: cloud credentials (~/.docker/config.json, ~/.azure/accessTokens.json), Kubernetes manifests, CI/CD configs, application settings

This is exploitable in applications that accept prompt configs from untrusted sources, including low-code AI builders and API wrappers that expose load_prompt_from_config().

Proof of concept

python
from langchain_core.prompts.loading import load_prompt_from_config
# Reads /tmp/secret.txt via absolute path injection
config = {
    "_type": "prompt",
    "template_path": "/tmp/secret.txt",
    "input_variables": [],
}
prompt = load_prompt_from_config(config)
print(prompt.template)
# file contents disclosed
# Reads ../../etc/secret.txt via directory traversal
config = {
    "_type": "prompt",
    "template_path": "../../etc/secret.txt",
    "input_variables": [],
}
prompt = load_prompt_from_config(config)
# Reads arbitrary .json via few-shot examples
config = {
    "_type": "few_shot",
    "examples": "../../../../.docker/config.json",
    "example_prompt": {
        "_type": "prompt",
        "input_variables": ["input", "output"],
        "template": "{input}: {output}",
    },
    "prefix": "",
    "suffix": "{query}",
    "input_variables": ["query"],
}
prompt = load_prompt_from_config(config)

Mitigation

Update langchain-core to >= 1.2.22.

The fix adds path validation that rejects absolute paths and .. traversal sequences by default. An allow_dangerous_paths=True keyword argument is available on load_prompt() and load_prompt_from_config() for trusted inputs.

As described above, these legacy APIs have been formally deprecated. Users should migrate to dumpd/dumps/load/loads from langchain_core.load.

Credit

AnalysisAI

A path traversal vulnerability (CVSS 7.5). High severity vulnerability requiring prompt remediation. …

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RemediationAI

Within 24 hours: inventory all langchain-core deployments and identify which versions are in use (check requirements.txt, poetry.lock, or package.json); immediately restrict access to any APIs accepting user-supplied prompt configurations. Within 7 days: upgrade langchain-core to version 1.2.22 or later across all affected systems and validate patch application. …

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CVE-2026-34070 vulnerability details – vuln.today

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