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AI / ML CVE-2026-21869

HIGH
Out-of-bounds Write (CWE-787)
2026-01-08 security-advisories@github.com
8.8
CVSS 3.1 · GitHub Advisory
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Severity by source

GitHub Advisory PRIMARY
8.8 HIGH
AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
SUSE
HIGH
qualitative
Red Hat
8.1 HIGH
qualitative

Primary rating from GitHub Advisory.

CVSS VectorGitHub Advisory

Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

Lifecycle Timeline

3
Analysis Generated
Mar 12, 2026 - 21:54 vuln.today
PoC Detected
Feb 02, 2026 - 19:12 vuln.today
Public exploit code
CVE Published
Jan 08, 2026 - 00:16 nvd
HIGH 8.8

DescriptionGitHub Advisory

llama.cpp is an inference of several LLM models in C/C++. In commits 55d4206c8 and prior, the n_discard parameter is parsed directly from JSON input in the llama.cpp server's completion endpoints without validation to ensure it's non-negative. When a negative value is supplied and the context fills up, llama_memory_seq_rm/add receives a reversed range and negative offset, causing out-of-bounds memory writes in the token evaluation loop. This deterministic memory corruption can crash the process or enable remote code execution (RCE). There is no fix at the time of publication.

AnalysisAI

Llama.cpp server endpoints fail to validate the n_discard parameter from JSON input, allowing negative values that trigger out-of-bounds memory writes when the context buffer fills. This memory corruption vulnerability affects LLM inference operations and can be exploited remotely without authentication to crash the service or achieve code execution; public exploit code exists and no patch is currently available.

Technical ContextAI

Classified as CWE-787 (Out-of-bounds Write). Affects Llama.Cpp. llama.cpp is an inference of several LLM models in C/C++. In commits 55d4206c8 and prior, the n_discard parameter is parsed directly from JSON input in the llama.cpp server's completion endpoints without validation to ensure it's non-negative. When a negative value is supplied and the context fills up, llama_memory_seq_rm/add receives a reversed range and negative offset, causing out-of-bounds memory writes in the token evaluation loop. This deterministic memory corruption can crash the process

RemediationAI

Monitor vendor advisories for a patch. Enable ASLR, DEP/NX, and stack canaries where possible. Restrict network access to the affected service where possible.

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Vendor StatusVendor

SUSE

Severity: High

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CVE-2026-21869 vulnerability details – vuln.today

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