VAR-201906-0817
Vulnerability from variot - Updated: 2024-11-23 22:21A buffer overflow vulnerability in Fortinet FortiOS 6.0.0 through 6.0.4, 5.6.0 through 5.6.7, 5.4 and earlier versions and FortiProxy 2.0.0, 1.2.8 and earlier versions under SSL VPN web portal allows a non-authenticated attacker to perform a Denial-of-service attack via special craft message payloads. Fortinet FortiOS Contains a buffer error vulnerability.Denial of service (DoS) May be in a state. FortinetFortiOS is a set of Fortinet security operating systems dedicated to the FortiGate network security platform. The system provides users with multiple security features such as firewall, anti-virus, IPSec/SSLVPN, web content filtering and anti-spam. A buffer overflow vulnerability exists in FortinetFort iOS version 6.0.0 to 6.0.4, 5.6.0 to 5.6.7, and 5.4 and earlier. The vulnerability stems from a network system or product that does not properly validate data boundaries when performing operations on memory, causing erroneous read and write operations to be performed on other associated memory locations. An attacker could exploit the vulnerability to cause a buffer overflow or heap overflow. Fortinet FortiOS is prone to a buffer-overflow vulnerability. Attackers can exploit this issue to cause denial-of-service conditions. The following versions are vulnerable: FortiOS 6.0.0 through 6.0.4 FortiOS 5.6.0 through 5.6.7 FortiOS 5.4 and prior
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Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
How durations are calculated
Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.
Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.
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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.
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.