CVE-2024-7314 (GCVE-0-2024-7314)
Vulnerability from cvelistv5 – Published: 2024-08-02 16:33 – Updated: 2025-11-22 12:13 X_Known Exploited VulnerabilityTitle
anji-plus AJ-Report Authentication Bypass
Summary
anji-plus AJ-Report is affected by an authentication bypass vulnerability. A remote and unauthenticated attacker can append ";swagger-ui" to HTTP requests to bypass authentication and execute arbitrary Java on the victim server. Exploitation evidence was observed by the Shadowserver Foundation on 2025-02-05 UTC.
Severity
9.8 (Critical)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-08-07 15:46 UTC
CWE
- CWE-288 - Authentication Bypass Using an Alternate Path or Channel
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://vulncheck.com/advisories/aj-report-swagger | third-party-advisory |
| https://xz.aliyun.com/t/14460 | technical-descriptionexploit |
| https://github.com/yuebusao/AJ-REPORT-EXPLOIT | exploit |
| https://github.com/vulhub/vulhub/tree/master/aj-r… | exploit |
Impacted products
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: b6ea528b-29f7-4589-9c5f-71f19493177b
Exploited: Yes
Timestamps
First Seen: 2026-01-24
Asserted: 2026-01-24
Scope
Notes: anji-plus AJ-Report Authentication Bypass | Affected: Anji-plus / AJ-Report | CVSS: 9.8 (CRITICAL) | EPSS: 0.5175 | Used in malware: unknown | Not yet in CISA KEV: True
Evidence
Type: Public Report
Signal: Successful Exploitation
Confidence: 70%
Source: previdian
Details
| Feed | Previdian (previdian.com) |
|---|---|
| Title | anji-plus AJ-Report Authentication Bypass |
| Cve Id | CVE-2024-7314 |
| Vendor | Anji-plus |
| Ghsa Id | None |
| Product | AJ-Report |
| Added Date | 2026-01-24T00:00:00.000Z |
| Cvss Score | 9.8 |
| Epss Score | 0.5175 |
| Previous Ids | |
| Cvss Severity | CRITICAL |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.98916 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2024-7314 |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | True |
References
Created: 2026-10-02 09:09 CEST
| Updated: 2026-10-02 09:09 CEST
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
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.
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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.
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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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.
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