VAR-201710-1426
Vulnerability from variot - Updated: 2025-04-20 23:42A Cross-Site-Scripting (XSS) vulnerability in Fortinet FortiOS 5.4.0 to 5.4.5 and 5.6.0 allows a remote unauthenticated attacker to execute arbitrary javascript code via webUI "Login Disclaimer" redir parameter. Fortinet FortiOS Contains a cross-site scripting vulnerability.Information may be obtained and information may be altered. Fortinet FortiOS is prone to a cross-site scripting vulnerability because it fails to properly sanitize user-supplied input. This may allow the attacker to steal cookie-based authentication credentials and launch other attacks. Fortinet FortiOS 5.6.0 and 5.4.0 through 5.4.5 are vulnerable. Fortinet FortiOS is a set of security operating systems developed by Fortinet Corporation for the FortiGate network security platform. The system provides users with various security functions such as firewall, anti-virus, IPSec/SSL VPN, Web content filtering and anti-spam
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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
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