VAR-201508-0529
Vulnerability from variot - Updated: 2025-04-13 23:42FortiOS 5.0.x before 5.0.12 and 5.2.x before 5.2.4 supports anonymous, export, RC4, and possibly other weak ciphers when using TLS to connect to FortiGuard servers, which allows man-in-the-middle attackers to spoof TLS content by modifying packets. Fortinet FortiOS is prone to a security-bypass weakness. Successfully exploiting this issue may allow attackers to obtain sensitive information by conducting a man-in-the-middle attack. This may lead to other attacks. FortiOS 5.2.0 through 5.2.3 and 5.0.0 through 5.0.11 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. Fortinet FortiOS versions 5.0.0 to 5.0.1 and 5.2.0 to 5.2.3 have a security vulnerability
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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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