Vulnerability-Lookup

CNVD-2025-22724

Vulnerability from cnvd - Published: 2025-09-28

Title

GPT Academic文件读取漏洞

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存在文件读取漏洞，该漏洞源于HotReload功能未能正确验证用户输入，攻击者可利用该漏洞从受害者服务器读取任意本地文件。

Severity

高

Patch Name

GPT Academic文件读取漏洞的补丁

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存在文件读取漏洞，该漏洞源于HotReload功能未能正确验证用户输入，攻击者可利用该漏洞从受害者服务器读取任意本地文件。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/db2167f5-f17f-491d-aeec-69ba55bf6427

Impacted products

Name
GPT Academic GPT Academic 3.83

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2024-10986",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2024-10986"
    }
  },
  "description": "GPT Academic\u662f\u4e00\u4e2a\u4e3a GPT/GLM \u7b49 LLM \u5927\u8bed\u8a00\u6a21\u578b\u63d0\u4f9b\u5b9e\u7528\u5316\u4ea4\u4e92\u7684\u63a5\u53e3\u3002 \n\nGPT Academic\u5b58\u5728\u6587\u4ef6\u8bfb\u53d6\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eHotReload\u529f\u80fd\u672a\u80fd\u6b63\u786e\u9a8c\u8bc1\u7528\u6237\u8f93\u5165\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u4ece\u53d7\u5bb3\u8005\u670d\u52a1\u5668\u8bfb\u53d6\u4efb\u610f\u672c\u5730\u6587\u4ef6\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-2025-22724",
  "openTime": "2025-09-28",
  "patchDescription": "GPT Academic\u662f\u4e00\u4e2a\u4e3a GPT/GLM \u7b49 LLM \u5927\u8bed\u8a00\u6a21\u578b\u63d0\u4f9b\u5b9e\u7528\u5316\u4ea4\u4e92\u7684\u63a5\u53e3\u3002 \r\n\r\nGPT Academic\u5b58\u5728\u6587\u4ef6\u8bfb\u53d6\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eHotReload\u529f\u80fd\u672a\u80fd\u6b63\u786e\u9a8c\u8bc1\u7528\u6237\u8f93\u5165\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u4ece\u53d7\u5bb3\u8005\u670d\u52a1\u5668\u8bfb\u53d6\u4efb\u610f\u672c\u5730\u6587\u4ef6\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\u6587\u4ef6\u8bfb\u53d6\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "GPT Academic GPT Academic 3.83"
  },
  "referenceLink": "https://huntr.com/bounties/db2167f5-f17f-491d-aeec-69ba55bf6427",
  "serverity": "\u9ad8",
  "submitTime": "2025-03-27",
  "title": "GPT Academic\u6587\u4ef6\u8bfb\u53d6\u6f0f\u6d1e"
}

CVE-2024-10986 (GCVE-0-2024-10986)

Vulnerability from cvelistv5 – Published: 2025-03-20 10:10 – Updated: 2025-10-15 12:50

Title

Local File Read (LFI) by Tarslip Symlink via arxiv_download() API in binary-husky/gpt_academic

Summary

GPT Academic version 3.83 is vulnerable to a Local File Read (LFI) vulnerability through its HotReload function. This function can download and extract tar.gz files from arxiv.org. Despite implementing protections against path traversal, the application overlooks the Tarslip triggered by symlinks. This oversight allows attackers to read arbitrary local files from the victim server.

Severity

8.8 (High)


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

SSVC

Exploitation: poc Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-03-20 17:49 UTC

CWE

CWE-59 - Improper Link Resolution Before File Access

Assigner

@huntr_ai mitre root

References

1 reference

URL	Tags
https://huntr.com/bounties/db2167f5-f17f-491d-aee…

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-2024-10986",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-03-20T17:49:16.725785Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-03-20T18:15:04.826Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
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          "vendor": "binary-husky",
          "versions": [
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              "status": "affected",
              "version": "unspecified",
              "versionType": "custom"
            }
          ]
        }
      ],
      "descriptions": [
        {
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        }
      ],
      "metrics": [
        {
          "cvssV3_0": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 8.8,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
            "version": "3.0"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
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      "providerMetadata": {
        "dateUpdated": "2025-10-15T12:50:15.584Z",
        "orgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
        "shortName": "@huntr_ai"
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          "url": "https://huntr.com/bounties/db2167f5-f17f-491d-aeec-69ba55bf6427"
        }
      ],
      "source": {
        "advisory": "db2167f5-f17f-491d-aeec-69ba55bf6427",
        "discovery": "EXTERNAL"
      },
      "title": "Local File Read (LFI) by Tarslip Symlink via arxiv_download() API in binary-husky/gpt_academic"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
    "assignerShortName": "@huntr_ai",
    "cveId": "CVE-2024-10986",
    "datePublished": "2025-03-20T10:10:55.368Z",
    "dateReserved": "2024-11-07T20:08:39.852Z",
    "dateUpdated": "2025-10-15T12:50:15.584Z",
    "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.