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CVE-2024-48307 (GCVE-0-2024-48307)

Vulnerability from cvelistv5 – Published: 2024-10-31 00:00 – Updated: 2024-10-31 18:33
VLAI Shadowserver Previdian
Summary
JeecgBoot v3.7.1 was discovered to contain a SQL injection vulnerability via the component /onlDragDatasetHead/getTotalData.
Severity
9.8 (Critical)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
SSVC
Exploitation: poc Automatable: yes Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-10-31 18:32 UTC
CWE
  • n/a
  • CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
Assigner
References
Impacted products
Vendor Product Version CPE status
jeecg jeecgboot Affected: 3.7.1
    cpe:2.3:a:jeecg:jeecgboot:*:*:*:*:*:*:*:*
Create a notification for this product.
Shadowserver
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 6213ab03-e46d-47dd-9e5d-5e258949593d

Vulnerability ID: CVE-2024-48307

Status: Confirmed

Status Updated: 2026-07-20 00:00 UTC

Exploited: Yes

Characteristics
Severity: 98.0
Timestamps
First Seen: 2024-12-24
Asserted: 2024-12-24
Last Seen: 2026-07-20
Scope
Asset Exposure: ['internet-facing']
Notes: Affected: JEECG / jeecg-boot | Class: other-software | Severity: Critical (CVSS 9.8) | IoT: no | In CISA KEV: no | Honeypot connections on 2026-07-20: 1
Evidence

Type: Honeypot

Signal: In The Wild Attempts

Confidence: 70%

Source: shadowserver

Details
1D 1
Iot no
Feed Shadowserver Foundation honeypot/exploited-vulnerabilities
Type http-scan
Class other-software
7D Avg 0
Vendor JEECG
30D Avg 4
90D Avg 3
Product jeecg-boot
Cisa Kev no
Connections 1
Observation Date 2026-07-20
Vulnerability Class CVSS
Vulnerability Score 9.8
Vulnerability Severity Critical
References
Created: 2026-06-30 09:22 UTC | Updated: 2026-07-22 01:00 UTC
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: bc9e25fc-7e82-48d2-935d-744c9d03c7f3

Vulnerability ID: CVE-2024-48307

Status: Confirmed

Status Updated: 2025-06-26 00:00 UTC

Exploited: Yes

Timestamps
First Seen: 2025-06-26
Asserted: 2025-06-26
Scope
Notes: KEVIntel entry: JeecgBoot v3.7.1 was discovered to contain a SQL injection vulnerability via the component /onlDragDatasetHead/getTotalData. | Affected: JeecgBoot / JeecgBoot | CVSS: 9.8 (CRITICAL) | Used in malware: unknown | Not yet in CISA KEV: True
Evidence

Type: Public Report

Signal: Successful Exploitation

Confidence: 70%

Source: kevintel

Details
Feed KEVIntel (kevintel.com)
Title JeecgBoot v3.7.1 was discovered to contain a SQL injection vulnerability via the component /onlDragDatasetHead/getTotalData.
Vendor JeecgBoot
Product JeecgBoot
Added Date 2025-06-26T00:00:00.000Z
Cvss Score 9.8
Epss Score None
Cvss Severity CRITICAL
Epss Percentile None
Used In Malware unknown
Ahead Of Cisa Kev None
Not Yet In Cisa Kev True
References
Created: 2026-06-23 14:03 UTC | Updated: 2026-07-10 06:14 UTC
Show details on NVD website
To clipboard 

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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.


Detection rules are retrieved from Rulezet.


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.