ggml-org llama.cpp Vocabulary Implementation print_info heap-based overflow
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 4.1 | $0-$5k | 2.66 |
Summary
A vulnerability, which was classified as problematic, has been found in ggml-org llama.cpp. This impacts the function llama_vocab::impl::print_info of the component Vocabulary Implementation. Performing a manipulation results in heap-based overflow.
This vulnerability is cataloged as CVE-2025-71439. The attack must be initiated from a local position. There is no exploit available.
Applying a patch is the recommended action to fix this issue.
Details
A vulnerability was found in ggml-org llama.cpp (affected version unknown). It has been classified as problematic. This affects the function llama_vocab::impl::print_info of the component Vocabulary Implementation. The manipulation with an unknown input leads to a heap-based overflow vulnerability. CWE is classifying the issue as CWE-122. A heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc(). This is going to have an impact on availability. The summary by CVE is:
llama.cpp before b5649 contains a heap out-of-bounds read vulnerability in llama_vocab::impl::print_info() that allows attackers to crash model loading via oversized special token IDs. Attackers can supply a crafted GGUF model with a short tokenizer.ggml.tokens array, causing llama-cli or llama-server to read past id_to_token and crash.
The advisory is shared at github.com. This vulnerability is uniquely identified as CVE-2025-71439 since 10/27/2026. The exploitability is told to be easy. An attack has to be approached locally. It demands that the victim is doing some kind of user interaction. Technical details are known, but no exploit is available.
Applying the patch b5649 is able to eliminate this problem.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Product
Vendor
Name
Website
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 4.1VulDB Meta Temp Score: 4.1
VulDB Base Score: 2.8
VulDB Temp Score: 2.7
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 5.5
CNA Vector (VulnCheck): 🔒
CVSSv2
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Heap-based overflowCWE: CWE-122 / CWE-119
CAPEC: 🔒
ATT&CK: 🔒
Physical: Partially
Local: Yes
Remote: Partially
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: PatchStatus: 🔍
0-Day Time: 🔒
Patch: b5649
Timeline
10/27/2026 Advisory disclosed10/27/2026 CVE reserved
10/27/2026 VulDB entry created
10/27/2026 VulDB entry last update
Sources
Product: github.comAdvisory: github.com
Status: Confirmed
CVE: CVE-2025-71439 (🔒)
GCVE (CVE): GCVE-0-2025-71439
GCVE (VulDB): GCVE-100-427029
Entry
Created: 10/27/2026 02:26Changes: 10/27/2026 02:26 (76)
Complete: 🔍
Cache ID: 216::103
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
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