CVE-2025-3677 (GCVE-0-2025-3677)
Vulnerability from cvelistv5 – Published: 2025-04-16 08:31 – Updated: 2025-04-21 11:28
VLAI
EPSS
VEX
Title
lm-sys fastchat apply_delta.py apply_delta_low_cpu_mem deserialization
Summary
A vulnerability classified as critical was found in lm-sys fastchat up to 0.2.36. This vulnerability affects the function split_files/apply_delta_low_cpu_mem of the file fastchat/model/apply_delta.py. The manipulation leads to deserialization. An attack has to be approached locally.
Severity
5.3 (Medium)
5.3 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-04-16 19:30 UTC
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.304966 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.304966 | signaturepermissions-required |
| https://vuldb.com/?submit.552755 | third-party-advisory |
| https://github.com/lm-sys/FastChat/issues/3713 | issue-tracking |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| lm-sys | fastchat |
Affected:
0.2.0
Affected: 0.2.1 Affected: 0.2.2 Affected: 0.2.3 Affected: 0.2.4 Affected: 0.2.5 Affected: 0.2.6 Affected: 0.2.7 Affected: 0.2.8 Affected: 0.2.9 Affected: 0.2.10 Affected: 0.2.11 Affected: 0.2.12 Affected: 0.2.13 Affected: 0.2.14 Affected: 0.2.15 Affected: 0.2.16 Affected: 0.2.17 Affected: 0.2.18 Affected: 0.2.19 Affected: 0.2.20 Affected: 0.2.21 Affected: 0.2.22 Affected: 0.2.23 Affected: 0.2.24 Affected: 0.2.25 Affected: 0.2.26 Affected: 0.2.27 Affected: 0.2.28 Affected: 0.2.29 Affected: 0.2.30 Affected: 0.2.31 Affected: 0.2.32 Affected: 0.2.33 Affected: 0.2.34 Affected: 0.2.35 Affected: 0.2.36 |
guessed |
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"status": "affected",
"version": "0.2.35"
},
{
"status": "affected",
"version": "0.2.36"
}
]
}
],
"credits": [
{
"lang": "en",
"type": "reporter",
"value": "ybdesire (VulDB User)"
},
{
"lang": "en",
"type": "analyst",
"value": "ybdesire (VulDB User)"
}
],
"descriptions": [
{
"lang": "en",
"value": "A vulnerability classified as critical was found in lm-sys fastchat up to 0.2.36. This vulnerability affects the function split_files/apply_delta_low_cpu_mem of the file fastchat/model/apply_delta.py. The manipulation leads to deserialization. An attack has to be approached locally."
},
{
"lang": "de",
"value": "In lm-sys fastchat bis 0.2.36 wurde eine Schwachstelle entdeckt. Sie wurde als kritisch eingestuft. Das betrifft die Funktion split_files/apply_delta_low_cpu_mem der Datei fastchat/model/apply_delta.py. Mit der Manipulation mit unbekannten Daten kann eine deserialization-Schwachstelle ausgenutzt werden. Die Umsetzung des Angriffs hat dabei lokal zu erfolgen."
}
],
"metrics": [
{
"cvssV4_0": {
"baseScore": 4.8,
"baseSeverity": "MEDIUM",
"vectorString": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N",
"version": "4.0"
}
},
{
"cvssV3_1": {
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
"version": "3.1"
}
},
{
"cvssV3_0": {
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"vectorString": "CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
"version": "3.0"
}
},
{
"cvssV2_0": {
"baseScore": 4.3,
"vectorString": "AV:L/AC:L/Au:S/C:P/I:P/A:P",
"version": "2.0"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-502",
"description": "Deserialization",
"lang": "en",
"type": "CWE"
}
]
},
{
"descriptions": [
{
"cweId": "CWE-20",
"description": "Improper Input Validation",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2025-04-21T11:28:25.222Z",
"orgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"shortName": "VulDB"
},
"references": [
{
"name": "VDB-304966 | lm-sys fastchat apply_delta.py apply_delta_low_cpu_mem deserialization",
"tags": [
"vdb-entry",
"technical-description"
],
"url": "https://vuldb.com/?id.304966"
},
{
"name": "VDB-304966 | CTI Indicators (IOB, IOC, IOA)",
"tags": [
"signature",
"permissions-required"
],
"url": "https://vuldb.com/?ctiid.304966"
},
{
"name": "Submit #552755 | lm-sys FastChat v0.2.3 to v0.2.36 Deserialization",
"tags": [
"third-party-advisory"
],
"url": "https://vuldb.com/?submit.552755"
},
{
"tags": [
"issue-tracking"
],
"url": "https://github.com/lm-sys/FastChat/issues/3713"
}
],
"timeline": [
{
"lang": "en",
"time": "2025-04-16T00:00:00.000Z",
"value": "Advisory disclosed"
},
{
"lang": "en",
"time": "2025-04-16T02:00:00.000Z",
"value": "VulDB entry created"
},
{
"lang": "en",
"time": "2025-04-21T13:30:23.000Z",
"value": "VulDB entry last update"
}
],
"title": "lm-sys fastchat apply_delta.py apply_delta_low_cpu_mem deserialization"
}
},
"cveMetadata": {
"assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"assignerShortName": "VulDB",
"cveId": "CVE-2025-3677",
"datePublished": "2025-04-16T08:31:04.475Z",
"dateReserved": "2025-04-16T01:03:15.592Z",
"dateUpdated": "2025-04-21T11:28:25.222Z",
"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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