CNVD-2024-46012

Vulnerability from cnvd - Published: 2024-11-26
VLAI
Title
PandasAI命令注入漏洞
Description
PandasAI是一个将数据操作分析库Pandas与AI相结合的数据处理应用,用户可以通过自然语言与数据进行交互,而无需编写复杂的代码。 PandasAI存在命令注入漏洞,攻击者可利用该漏洞执行恶意命令。目前暂无漏洞细节。
Severity
高
Formal description

厂商尚未提供漏洞修复方案,请关注厂商主页更新: https://github.com/gventuri/pandas-ai

Reference
https://github.com/gventuri/pandas-ai
Impacted products
Name
PandasAI PandasAI
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2024-9880"
    }
  },
  "description": "PandasAI\u662f\u4e00\u4e2a\u5c06\u6570\u636e\u64cd\u4f5c\u5206\u6790\u5e93Pandas\u4e0eAI\u76f8\u7ed3\u5408\u7684\u6570\u636e\u5904\u7406\u5e94\u7528\uff0c\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u81ea\u7136\u8bed\u8a00\u4e0e\u6570\u636e\u8fdb\u884c\u4ea4\u4e92\uff0c\u800c\u65e0\u9700\u7f16\u5199\u590d\u6742\u7684\u4ee3\u7801\u3002\n\nPandasAI\u5b58\u5728\u547d\u4ee4\u6ce8\u5165\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u6267\u884c\u6076\u610f\u547d\u4ee4\u3002\u76ee\u524d\u6682\u65e0\u6f0f\u6d1e\u7ec6\u8282\u3002",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0\uff1a\r\nhttps://github.com/gventuri/pandas-ai",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2024-46012",
  "openTime": "2024-11-26",
  "products": {
    "product": "PandasAI PandasAI"
  },
  "referenceLink": "https://github.com/gventuri/pandas-ai",
  "serverity": "\u9ad8",
  "submitTime": "2024-11-26",
  "title": "PandasAI\u547d\u4ee4\u6ce8\u5165\u6f0f\u6d1e"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.

Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

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.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

JSON
Events included in the timeline

Loading timeline…


    Loading…

    Loading…

    Loading…

    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.