Vulnerability-Lookup

CNVD-2025-22732

Vulnerability from cnvd - Published: 2025-09-28

Title

GPT Academic拒绝服务漏洞（CNVD-2025-22732）

Description

GPT Academic是一个为GPT/GLM等LLM大语言模型提供实用化交互的接口。 GPT Academic存在拒绝服务漏洞，该漏洞源于文件上传功能存在安全问题，攻击者可利用该漏洞导致拒绝服务。

Severity

中

Patch Name

GPT Academic拒绝服务漏洞（CNVD-2025-22732）的补丁

Patch Description

GPT Academic是一个为GPT/GLM等LLM大语言模型提供实用化交互的接口。 GPT Academic存在拒绝服务漏洞，该漏洞源于文件上传功能存在安全问题，攻击者可利用该漏洞导致拒绝服务。目前，供应商发布了安全公告及相关补丁信息，修复了此漏洞。

Formal description

厂商已发布了漏洞修复程序，请及时关注更新： https://github.com/binary-husky/gpt_academic/releases/tag/version3.91

Reference

https://huntr.com/bounties/78afc15c-7db7-42fe-90f5-a0480a2ec222

Impacted products

Name
GPT Academic GPT Academic 3.83

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2024-11033",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2024-11033"
    }
  },
  "description": "GPT Academic\u662f\u4e00\u4e2a\u4e3aGPT/GLM\u7b49LLM\u5927\u8bed\u8a00\u6a21\u578b\u63d0\u4f9b\u5b9e\u7528\u5316\u4ea4\u4e92\u7684\u63a5\u53e3\u3002\n\nGPT Academic\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u6587\u4ef6\u4e0a\u4f20\u529f\u80fd\u5b58\u5728\u5b89\u5168\u95ee\u9898\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\u3002",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://github.com/binary-husky/gpt_academic/releases/tag/version3.91",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2025-22732",
  "openTime": "2025-09-28",
  "patchDescription": "GPT Academic\u662f\u4e00\u4e2a\u4e3aGPT/GLM\u7b49LLM\u5927\u8bed\u8a00\u6a21\u578b\u63d0\u4f9b\u5b9e\u7528\u5316\u4ea4\u4e92\u7684\u63a5\u53e3\u3002\r\n\r\nGPT Academic\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u6587\u4ef6\u4e0a\u4f20\u529f\u80fd\u5b58\u5728\u5b89\u5168\u95ee\u9898\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\u3002\u76ee\u524d\uff0c\u4f9b\u5e94\u5546\u53d1\u5e03\u4e86\u5b89\u5168\u516c\u544a\u53ca\u76f8\u5173\u8865\u4e01\u4fe1\u606f\uff0c\u4fee\u590d\u4e86\u6b64\u6f0f\u6d1e\u3002",
  "patchName": "GPT Academic\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff08CNVD-2025-22732\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "GPT Academic GPT Academic 3.83"
  },
  "referenceLink": "https://huntr.com/bounties/78afc15c-7db7-42fe-90f5-a0480a2ec222",
  "serverity": "\u4e2d",
  "submitTime": "2025-03-27",
  "title": "GPT Academic\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff08CNVD-2025-22732\uff09"
}

CVE-2024-11033 (GCVE-0-2024-11033)

Vulnerability from cvelistv5 – Published: 2025-03-20 10:10 – Updated: 2025-03-20 18:20

Title

Denial of Service (DoS) in binary-husky/gpt_academic

Summary

A Denial of Service (DoS) vulnerability exists in the file upload feature of binary-husky/gpt_academic version 3.83. The vulnerability is due to improper handling of form-data with a large filename in the file upload request. An attacker can exploit this vulnerability by sending a payload with an excessively large filename, causing the server to become overwhelmed and unavailable for legitimate users.

Severity

6.5 (Medium)


                        
                          CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

SSVC

Exploitation: poc Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-03-20 17:48 UTC

CWE

CWE-400 - Uncontrolled Resource Consumption

Assigner

@huntr_ai mitre root

References

1 reference

URL	Tags
https://huntr.com/bounties/78afc15c-7db7-42fe-90f…

Impacted products

1 product

Vendor	Product	Version
binary-husky	binary-husky/gpt_academic	Affected: unspecified , ≤ latest (custom)

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2024-11033",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-03-20T17:48:27.049670Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-03-20T18:20:33.613Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "binary-husky/gpt_academic",
          "vendor": "binary-husky",
          "versions": [
            {
              "lessThanOrEqual": "latest",
              "status": "affected",
              "version": "unspecified",
              "versionType": "custom"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "A Denial of Service (DoS) vulnerability exists in the file upload feature of binary-husky/gpt_academic version 3.83. The vulnerability is due to improper handling of form-data with a large filename in the file upload request. An attacker can exploit this vulnerability by sending a payload with an excessively large filename, causing the server to become overwhelmed and unavailable for legitimate users."
        }
      ],
      "metrics": [
        {
          "cvssV3_0": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 6.5,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
            "version": "3.0"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-400",
              "description": "CWE-400 Uncontrolled Resource Consumption",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-03-20T10:10:30.878Z",
        "orgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
        "shortName": "@huntr_ai"
      },
      "references": [
        {
          "url": "https://huntr.com/bounties/78afc15c-7db7-42fe-90f5-a0480a2ec222"
        }
      ],
      "source": {
        "advisory": "78afc15c-7db7-42fe-90f5-a0480a2ec222",
        "discovery": "EXTERNAL"
      },
      "title": "Denial of Service (DoS) in binary-husky/gpt_academic"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
    "assignerShortName": "@huntr_ai",
    "cveId": "CVE-2024-11033",
    "datePublished": "2025-03-20T10:10:30.878Z",
    "dateReserved": "2024-11-08T21:50:06.063Z",
    "dateUpdated": "2025-03-20T18:20:33.613Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

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.

Detection rules are retrieved from Rulezet.

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.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.