CVE-2025-24356 (GCVE-0-2025-24356)
Vulnerability from cvelistv5 – Published: 2025-01-27 17:31 – Updated: 2025-01-28 15:39
VLAI
EPSS
VEX
Title
UDP traffic amplification via fastd's fast reconnect feature
Summary
fastd is a VPN daemon which tunnels IP packets and Ethernet frames over UDP. When receiving a data packet from an unknown IP address/port combination, fastd will assume that one of its connected peers has moved to a new address and initiate a reconnect by sending a handshake packet. This "fast reconnect" avoids having to wait for a session timeout (up to ~90s) until a new connection is established. Even a 1-byte UDP packet just containing the fastd packet type header can trigger a much larger handshake packet (~150 bytes of UDP payload). Including IPv4 and UDP headers, the resulting amplification factor is roughly 12-13. By sending data packets with a spoofed source address to fastd instances reachable on the internet, this amplification of UDP traffic might be used to facilitate a Distributed Denial of Service attack. This vulnerability is fixed in v23.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-01-28 15:38 UTC
CWE
- CWE-405 - Asymmetric Resource Consumption (Amplification)
Assigner
References
8 references
| URL | Tags |
|---|---|
| https://github.com/neocturne/fastd/security/advis… | x_refsource_CONFIRM |
| https://github.com/neocturne/fastd/commit/1f233be… | x_refsource_MISC |
| https://github.com/neocturne/fastd/commit/3940150… | x_refsource_MISC |
| https://github.com/neocturne/fastd/commit/5f63fcf… | x_refsource_MISC |
| https://github.com/neocturne/fastd/commit/9df7e51… | x_refsource_MISC |
| https://github.com/neocturne/fastd/commit/c1a07b3… | x_refsource_MISC |
| https://github.com/neocturne/fastd/commit/ce1b79b… | x_refsource_MISC |
| https://github.com/neocturne/fastd/commit/d03a0a1… | x_refsource_MISC |
Impacted products
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"datePublished": "2025-01-27T17:31:38.541Z",
"dateReserved": "2025-01-20T15:18:26.988Z",
"dateUpdated": "2025-01-28T15:39:06.688Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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