Vulnerability-Lookup

PYSEC-2026-75

Vulnerability from pysec - Published: 2026-01-12 23:15 - Updated: 2026-05-20 09:19

Details

LangChain versions up to and including 0.3.1 contain a regular expression denial-of-service (ReDoS) vulnerability in the MRKLOutputParser.parse() method (libs/langchain/langchain/agents/mrkl/output_parser.py). The parser applies a backtracking-prone regular expression when extracting tool actions from model output. An attacker who can supply or influence the parsed text (for example via prompt injection in downstream applications that pass LLM output directly into MRKLOutputParser.parse()) can trigger excessive CPU consumption by providing a crafted payload, causing significant parsing delays and a denial-of-service condition.

Severity

7.5 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Impacted products

Name	purl
langchain-exa	pkg:pypi/langchain-exa

Aliases

CVE-2024-58340

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "langchain-exa",
        "purl": "pkg:pypi/langchain-exa"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.0.0a1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.0.1",
        "0.1.0",
        "0.2.0",
        "0.2.1",
        "0.3.0",
        "0.3.1"
      ]
    }
  ],
  "aliases": [
    "CVE-2024-58340"
  ],
  "details": "LangChain versions up to and including 0.3.1 contain a regular expression denial-of-service (ReDoS) vulnerability in the MRKLOutputParser.parse() method (libs/langchain/langchain/agents/mrkl/output_parser.py). The parser applies a backtracking-prone regular expression when extracting tool actions from model output. An attacker who can supply or influence the parsed text (for example via prompt injection in downstream applications that pass LLM output directly into MRKLOutputParser.parse()) can trigger excessive CPU consumption by providing a crafted payload, causing significant parsing delays and a denial-of-service condition.",
  "id": "PYSEC-2026-75",
  "modified": "2026-05-20T09:19:04.132922Z",
  "published": "2026-01-12T23:15:51.780Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://www.langchain.com/"
    },
    {
      "type": "ADVISORY",
      "url": "https://www.vulncheck.com/advisories/langchain-mrkloutputparser-redos"
    },
    {
      "type": "REPORT",
      "url": "https://huntr.com/bounties/e7ece02c-d4bb-4166-8e08-6baf4f8845bb"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/langchain-ai/langchain"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2024-58340 (GCVE-0-2024-58340)

Vulnerability from cvelistv5 – Published: 2026-01-12 23:05 – Updated: 2026-07-14 22:54

Title

LangChain <= 0.3.1 MRKLOutputParser ReDoS

Summary

Severity

8.7 (High)


                        
                          CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

SSVC

Exploitation: poc Automatable: yes Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-01-13 16:21 UTC

CWE

CWE-1333 - Inefficient Regular Expression Complexity

Assigner

VulnCheck mitre root Scorecard

References

4 references

URL	Tags
https://huntr.com/bounties/e7ece02c-d4bb-4166-8e0…	technical-descriptionexploit
https://www.langchain.com/	product
https://github.com/langchain-ai/langchain	product
https://www.vulncheck.com/advisories/langchain-mr…	third-party-advisory

Impacted products

1 product

Vendor	Product	Version
LangChain AI	LangChain	Affected: 0 , ≤ 0.3.1 (semver) cpe:2.3:a:langchain:langchain_core::::::python::*

Credits

LifeTeam2024

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2024-58340",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-01-13T16:21:27.783338Z",
                "version": "2.0.3"
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        "providerMetadata": {
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      }
    ],
    "cna": {
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          "packageURL": "pkg:github/langchain-ai/langchain",
          "product": "LangChain",
          "repo": "https://github.com/langchain-ai/langchain",
          "vendor": "LangChain AI",
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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

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PYSEC-2026-75

CVE-2024-58340 (GCVE-0-2024-58340)

Tags

Sightings

Nomenclature

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