VulnerabilityPublished 24 Mar 2026Updated 25 Mar 2026

CVE-2026-33298: ggml-org llama.cpp · Heap-based Buffer Overflow

Affects ggml-org llama.cppSource CVE Database V5

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Not known to be exploited · CVSS 7.8 High : upgrade to b7824 soon.

Data as of 29 Oct 2026, 19:04 UTC

CVSS 3.1 base score

7.8High

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.4% chance of exploitation in 30 days – higher than 42% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in b7824

CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

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

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Local: The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Either: the attacker exploits the vulnerability by accessing the target system locally (e.g., keyboard, console), or remotely (e.g., SSH); or the attacker relies on User Interaction by another person to perform actions required to exploit the vulnerability (e.g., tricking a legitimate user into opening a malicious document).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
User Interaction: Required: Successful exploitation of this vulnerability requires a user to take some action before the vulnerability can be exploited.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: High: There is total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact.
Integrity: High: There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the impacted component.
Availability: High: There is total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 24 Mar 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 29 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Upgrade ggml-org llama.cpp to b7824.

Affected software

Product	Affected	Fixed in
ggml-orgllama.cpp	Affected <b7824	Fixed in b7824

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

Organizations should immediately update llama.cpp to version b7824 or later, which contains the patch fixing the integer overflow and buffer overflow issues. Until updates can be applied, implement strict validation and sanitization of GGUF files before processing, including verifying tensor dimensions and file integrity to prevent malformed inputs. Restrict access to systems running llama.cpp to trusted users and environments to reduce the risk of malicious file processing. Employ runtime protections such as memory safety tools (e.g., ASLR, DEP) and sandboxing to limit the impact of potential exploitation. Monitor logs and system behavior for anomalies indicative of exploitation attempts. Educate users about the risks of processing untrusted model files and enforce policies to avoid loading models from unverified sources. Regularly review and apply security advisories from ggml-org and related communities.

Description

CVE-2026-33298 is a high-severity heap-based buffer overflow vulnerability in the ggml-org llama.cpp library, affecting versions prior to b7824. The flaw arises from an integer overflow in the ggml_nbytes function when processing crafted GGUF files with malicious tensor dimensions, causing memory size miscalculations. This leads to a heap buffer overflow during tensor processing, enabling potential remote code execution via memory corruption. Exploitation requires local access and user interaction but no privileges. The vulnerability impacts confidentiality, integrity, and availability of affected systems. A fix is included in version b7824. No known exploits are currently reported in the wild. Organizations using llama.cpp for LLM inference should urgently update to the patched version to mitigate risk.

Impact

This vulnerability poses a significant risk to organizations deploying llama.cpp for LLM inference, especially those processing untrusted GGUF files. Successful exploitation can lead to remote code execution, allowing attackers to execute arbitrary code with the privileges of the affected application. This can result in data breaches, system compromise, lateral movement within networks, and disruption of AI services. Given the increasing adoption of LLMs in various sectors including technology, research, and enterprise AI solutions, the impact can be widespread. Systems running vulnerable versions may be targeted to gain footholds or disrupt AI-driven workflows. The requirement for user interaction and local access somewhat limits remote exploitation but does not eliminate risk, particularly in environments where users process third-party or untrusted model files. The absence of known exploits in the wild provides a window for mitigation before active attacks emerge.

CWE-122Heap-based Buffer Overflow (opens in a new tab)
Variant weaknessLikelihood of exploit: HighCWE Top 25 (2025): #16
The product writes past the end of a buffer that was allocated on the heap.
Pre-design: Use a language or compiler that performs automatic bounds checking.
Architecture and Design
Use an abstraction library to abstract away risky APIs. Not a complete solution.
Operation · Build and Compilation · Environment Hardening
Use automatic buffer overflow detection mechanisms that are offered by certain compilers or compiler extensions. Examples include: the Microsoft Visual Studio /GS flag, Fedora/Red Hat FORTIFY_SOURCE GCC flag, StackGuard, and ProPolice, which provide various mechanisms including canary-based detection and range/index…
OWASP Cheat Sheets
XML Security (opens in a new tab)
Mass Assignment (opens in a new tab)
OWASP ASVS 4.0.3
V13.3.1 (opens in a new tab)
V5.1.4 (opens in a new tab)
V5.1.3 (opens in a new tab)
Attack patterns
Forced Integer Overflow (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).
CWE-190Integer Overflow or Wraparound (opens in a new tab)
Base weaknessLikelihood of exploit: Medium
The product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. This occurs when an integer value is incremented to a value that is too large to store in the associated representation. When this occurs, the value may become a very small or negative number.
Requirements
Ensure that all protocols are strictly defined, such that all out-of-bounds behavior can be identified simply, and require strict conformance to the protocol.
Requirements · Language Selection
Use a language that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
Architecture and Design · Libraries or Frameworks
Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
OWASP Cheat Sheets
XML Security (opens in a new tab)
Mass Assignment (opens in a new tab)
OWASP ASVS 4.0.3
V5.4.3 (opens in a new tab)
V13.3.1 (opens in a new tab)
V5.1.4 (opens in a new tab)
Attack patterns
Forced Integer Overflow (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 31 Mar 2026, 20:27 UTC

WeaknessesCWE-122, CWE-190

Technical details

References

Community reviews

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