CVE-2025-0317
Ollama ≤ 0.3.14
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HSummary
CVE-2025-0317 is a high-severity Divide By Zero (CWE-369) vulnerability in Ollama Ollama. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked in the top 4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as NLP and Transformers; in the Data-Related Vulnerabilities risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SA-8 (Security and Privacy Engineering Principles) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
Ollama versions 0.3.14 and earlier contain a division-by-zero vulnerability in the ggufPadding function that processes uploaded GGUF model files. The flaw resides in the model's file-handling component and is tracked as CWE-369, with a CVSS 3.1 score of 7.5 indicating network attack vector, low complexity, and high availability impact.
An unauthenticated remote attacker can exploit the issue by uploading a crafted GGUF model to the Ollama server, triggering the division-by-zero error and crashing the service to achieve denial of service. No authentication or user interaction is required.
The vulnerability was disclosed via a Huntr bounty submission, though the reference contains no explicit details on patches or mitigation steps. EPSS scores remain low at a current value of 0.0209 with a peak of 0.0327, and no information on active exploitation is provided.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-6832
Vulnerability Data
A vulnerability in ollama/ollama versions <=0.3.14 allows a malicious user to upload and create a customized GGUF model file on the Ollama server. This can lead to a division by zero error in the ggufPadding function, causing the server to…
more
crash and resulting in a Denial of Service (DoS) attack.
- CWE(s)
AI Security AnalysisAI
- AI Category
- NLP and Transformers
- Risk Domain
- Data-Related Vulnerabilities
- OWASP Top 10 for LLMs 2025
- Classification Reason
- Matched keywords: ollama
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation (including static/dynamic analysis) finds divide-by-zero conditions after they have been coded.
Security engineering principles can require safe-arithmetic constructs or explicit guards that keep division operands nonzero.
Validating numeric inputs before use as divisors structurally blocks zero values from reaching division operations.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly include code analysis, input validation, and testing that prevent divide-by-zero errors.
Vulnerability identification processes can discover divide-by-zero flaws via static analysis or testing.
Routine patching and replacement can remediate divide-by-zero bugs present in deployed software.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development can detect divide-by-zero conditions before release.
Secure development lifecycle includes input validation and error-handling practices that can prevent divide-by-zero faults.
Application security requirements can mandate checks for zero denominators and safe arithmetic handling.
Secure architecture principles encourage defensive coding patterns that avoid arithmetic exceptions.
Secure coding standards directly require validation to prevent divide-by-zero and similar runtime faults.