CVE-2021-22122 (GCVE-0-2021-22122)
Vulnerability from cvelistv5 – Published: 2021-02-08 15:55 – Updated: 2024-10-25 14:00Summary
An improper neutralization of input during web page generation in FortiWeb GUI interface 6.3.0 through 6.3.7 and version before 6.2.4 may allow an unauthenticated, remote attacker to perform a reflected cross site scripting attack (XSS) by injecting malicious payload in different vulnerable API end-points.
Severity
No CVSS data available.
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-10-23 13:59 UTC
CWE
- Execute unauthorized code or commands
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://fortiguard.com/advisory/FG-IR-20-122 | x_refsource_CONFIRM |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Fortinet | Fortinet FortiWeb |
Affected:
FortiWeb 6.3.0 through 6.3.7 and version before 6.2.4
|
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: b76124bf-1d91-45eb-8211-d9d3e340148b
Exploited: Yes
Timestamps
First Seen: 2025-12-28
Asserted: 2025-12-28
Scope
Notes: An improper neutralization of input during web page generation in FortiWeb GUI interface 6.3.0 through 6.3.7 and version before 6.2.4 may allow an... | Affected: Fortinet / Fortinet FortiWeb | CVSS: 6.1 (MEDIUM) | EPSS: 0.1052 | 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 | An improper neutralization of input during web page generation in FortiWeb GUI interface 6.3.0 through 6.3.7 and version before 6.2.4 may allow an... |
| Cve Id | CVE-2021-22122 |
| Vendor | Fortinet |
| Ghsa Id | None |
| Product | Fortinet FortiWeb |
| Added Date | 2025-12-28T00:00:00.000Z |
| Cvss Score | 6.1 |
| Epss Score | 0.1052 |
| Previous Ids | |
| Cvss Severity | MEDIUM |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.95634 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2021-22122 |
| 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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