CVE-2026-70638 (GCVE-0-2026-70638)
Vulnerability from cvelistv5 – Published: 2026-08-06 15:35 – Updated: 2026-08-14 16:51 X_Open Source
VLAI
EPSS
VEX
Title
llama.cpp b1886–b7445 Integer Overflow via new_1batch() in llama-android.cpp
Summary
llama.cpp builds b1886 through b7445 contain an integer overflow vulnerability in the LLaMA-Android JNI wrapper where the new_1batch() function multiplies sizeof(llama_seq_id) by an attacker-controlled n_seq_max parameter without overflow validation, causing heap buffer allocation to wrap and allocate insufficient memory. Attackers can exploit this by providing a crafted n_seq_max value through a malicious model file or JNI call to trigger heap corruption and achieve denial of service or arbitrary code execution on Android applications using the LLaMA-Android binding.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-07 15:17 UTC
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/ggml-org/llama.cpp/releases/ta… | release-notes |
| https://github.com/ggml-org/llama.cpp/commit/5c0d… | patch |
| https://github.com/Vladimir-tokarev-cyera/llama-c… | related |
| https://www.vulncheck.com/advisories/llama-cpp-b1… | third-party-advisory |
Impacted products
Date Public
2026-05-06 00:00
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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.