CVE-2025-0315: Ollama: GGUF model upload causes memory exhaustion DoS
HIGH PoC AVAILABLE CISA: TRACK*Any attacker with network access to an Ollama instance can crash it by uploading a crafted GGUF model file—no credentials required by default. If your org runs Ollama for internal LLM inference, patch to >0.3.14 immediately or place the API behind an authenticated reverse proxy. Exposed Ollama instances on internal dev networks are at high risk given the zero-auth, low-complexity exploit path.
Risk Assessment
High. The combination of network-accessible vector, zero authentication required, and low attack complexity makes this trivially exploitable by anyone who can reach the Ollama API port (default 11434). Ollama is routinely deployed without network restrictions in AI dev environments and on developer workstations, expanding the attack surface significantly. Availability impact is complete for the instance; confidentiality and integrity are unaffected. No active exploitation confirmed, but CVSS 7.5 and trivial reproducibility make this a priority patch.
Affected Systems
| Package | Ecosystem | Vulnerable Range | Patched |
|---|---|---|---|
| ollama | pip | — | No patch |
Do you use ollama? You're affected.
Severity & Risk
Attack Surface
Recommended Action
6 steps-
Patch: Upgrade Ollama beyond version 0.3.14 as soon as a patched release is available; monitor the official GitHub releases page.
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Network isolation: Restrict Ollama API (port 11434) to localhost or trusted internal subnets via firewall rules immediately.
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Auth proxy: Place a reverse proxy with authentication (nginx + OAuth2 proxy, Caddy with auth middleware) in front of any network-accessible Ollama instance.
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Restrict upload access: Audit and limit who can call /api/create and model push endpoints to administrators only.
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Detection: Alert on rapid memory growth in Ollama processes, OOM killer events targeting Ollama, or unexpected model creation API calls from non-admin principals.
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Workaround if patching is delayed: Disable the model creation endpoint at the network layer if untrusted users have API access.
CISA SSVC Assessment
Source: CISA Vulnrichment (SSVC v2.0). Decision based on the CISA Coordinator decision tree.
Classification
Compliance Impact
This CVE is relevant to:
Frequently Asked Questions
What is CVE-2025-0315?
Any attacker with network access to an Ollama instance can crash it by uploading a crafted GGUF model file—no credentials required by default. If your org runs Ollama for internal LLM inference, patch to >0.3.14 immediately or place the API behind an authenticated reverse proxy. Exposed Ollama instances on internal dev networks are at high risk given the zero-auth, low-complexity exploit path.
Is CVE-2025-0315 actively exploited?
Proof-of-concept exploit code is publicly available for CVE-2025-0315, increasing the risk of exploitation.
How to fix CVE-2025-0315?
1. Patch: Upgrade Ollama beyond version 0.3.14 as soon as a patched release is available; monitor the official GitHub releases page. 2. Network isolation: Restrict Ollama API (port 11434) to localhost or trusted internal subnets via firewall rules immediately. 3. Auth proxy: Place a reverse proxy with authentication (nginx + OAuth2 proxy, Caddy with auth middleware) in front of any network-accessible Ollama instance. 4. Restrict upload access: Audit and limit who can call /api/create and model push endpoints to administrators only. 5. Detection: Alert on rapid memory growth in Ollama processes, OOM killer events targeting Ollama, or unexpected model creation API calls from non-admin principals. 6. Workaround if patching is delayed: Disable the model creation endpoint at the network layer if untrusted users have API access.
What systems are affected by CVE-2025-0315?
This vulnerability affects the following AI/ML architecture patterns: LLM inference servers, model serving, local AI deployments, agent frameworks, RAG pipelines.
What is the CVSS score for CVE-2025-0315?
CVE-2025-0315 has a CVSS v3.1 base score of 7.5 (HIGH). The EPSS exploitation probability is 0.11%.
Technical Details
NVD Description
A vulnerability in ollama/ollama <=0.3.14 allows a malicious user to create a customized GGUF model file, upload it to the Ollama server, and create it. This can cause the server to allocate unlimited memory, leading to a Denial of Service (DoS) attack.
Exploitation Scenario
An attacker enumerates internal network services and discovers an Ollama instance on port 11434—common in AI dev environments where developers run local LLMs. Using the Ollama REST API (no authentication required by default), the attacker crafts a malicious GGUF file with a manipulated header that declares tensor metadata requiring terabytes of memory allocation. They POST this file to the /api/create endpoint. The Ollama server parses the GGUF header and attempts to allocate the declared memory without bounds validation, triggering OOM and crashing the process. All dependent services—RAG pipelines, agent frameworks, internal chatbots relying on this inference endpoint—go offline instantly. The attacker can automate resubmission to prevent service recovery, creating a sustained DoS condition.
Weaknesses (CWE)
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H References
- huntr.com/bounties/da414d29-b55a-496f-b135-17e0fcec67bc Exploit 3rd Party
Timeline
Related Vulnerabilities
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Same package: ollama CVE-2024-37032 8.8 Ollama: path traversal enables RCE via model blob API
Same package: ollama CVE-2024-39720 8.2 Ollama: OOB read in GGUF parser enables remote DoS
Same package: ollama
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