CVE-2025-1975: Ollama: DoS via malicious manifest in /api/pull
UNKNOWN PoC AVAILABLE CISA: TRACK*Ollama 0.5.11 crashes when processing a crafted model manifest through the /api/pull endpoint due to missing array index validation. Any user with network access to your Ollama instance can take down your LLM inference service. Update immediately and restrict /api/pull to trusted networks or authenticated users.
What is the risk?
Risk is HIGH for organizations running Ollama in shared or network-accessible environments. Ollama ships with no authentication by default, meaning any network-reachable instance is trivially exploitable. The crash is deterministic — a single malformed request suffices. In DevOps and MLOps pipelines where Ollama runs as a shared inference backend, this translates directly to service disruption across dependent AI workloads. No evidence of active exploitation yet, but the exploit surface is large given Ollama's adoption in enterprise AI labs.
What systems are affected?
| Package | Ecosystem | Vulnerable Range | Patched |
|---|---|---|---|
| Ollama | pip | — | No patch |
Do you use Ollama? You're affected.
How severe is it?
What should I do?
5 steps-
PATCH
Upgrade Ollama beyond 0.5.11 immediately. Check https://github.com/ollama/ollama/releases for the fixed version.
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NETWORK ISOLATION
Restrict Ollama port (default 11434) to localhost or trusted subnets only using firewall rules. Never expose Ollama directly to the internet.
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AUTHENTICATION PROXY
Place a reverse proxy (nginx, Caddy) with authentication in front of Ollama if multi-user access is required.
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DETECTION
Alert on repeated 5xx errors or unexpected Ollama process restarts. Monitor for anomalous POST /api/pull requests from unexpected sources.
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WORKAROUND (if patching is not immediate): Disable or firewall the /api/pull endpoint if model pulling is not required at runtime.
What does CISA's SSVC say?
Source: CISA Vulnrichment (SSVC v2.0). Decision based on the CISA Coordinator decision tree.
How is it classified?
Which compliance frameworks are affected?
This CVE is relevant to:
Frequently Asked Questions
What is CVE-2025-1975?
Ollama 0.5.11 crashes when processing a crafted model manifest through the /api/pull endpoint due to missing array index validation. Any user with network access to your Ollama instance can take down your LLM inference service. Update immediately and restrict /api/pull to trusted networks or authenticated users.
Is CVE-2025-1975 actively exploited?
Proof-of-concept exploit code is publicly available for CVE-2025-1975, increasing the risk of exploitation.
How to fix CVE-2025-1975?
1. PATCH: Upgrade Ollama beyond 0.5.11 immediately. Check https://github.com/ollama/ollama/releases for the fixed version. 2. NETWORK ISOLATION: Restrict Ollama port (default 11434) to localhost or trusted subnets only using firewall rules. Never expose Ollama directly to the internet. 3. AUTHENTICATION PROXY: Place a reverse proxy (nginx, Caddy) with authentication in front of Ollama if multi-user access is required. 4. DETECTION: Alert on repeated 5xx errors or unexpected Ollama process restarts. Monitor for anomalous POST /api/pull requests from unexpected sources. 5. WORKAROUND (if patching is not immediate): Disable or firewall the /api/pull endpoint if model pulling is not required at runtime.
What systems are affected by CVE-2025-1975?
This vulnerability affects the following AI/ML architecture patterns: model serving, LLM inference, RAG pipelines, agent frameworks, local AI deployments.
What is the CVSS score for CVE-2025-1975?
No CVSS score has been assigned yet.
What is the AI security impact?
Affected AI Architectures
MITRE ATLAS Techniques
AML.T0029 Denial of AI Service AML.T0034 Cost Harvesting AML.T0049 Exploit Public-Facing Application Compliance Controls Affected
What are the technical details?
Original Advisory
A vulnerability in the Ollama server version 0.5.11 allows a malicious user to cause a Denial of Service (DoS) attack by customizing the manifest content and spoofing a service. This is due to improper validation of array index access when downloading a model via the /api/pull endpoint, which can lead to a server crash.
Exploitation Scenario
An attacker with network access to an Ollama instance — an insider, compromised developer machine, or lateral movement from another host — sends a POST request to /api/pull with a crafted manifest payload that includes malformed array indices. The Ollama server attempts to access an out-of-bounds array index during manifest parsing, triggering a panic/crash. The attacker can repeat this after each restart to maintain a persistent DoS condition, effectively taking down any AI application stack dependent on that Ollama instance (chatbots, RAG pipelines, agentic workflows).
Weaknesses (CWE)
CWE-129 — Improper Validation of Array Index: The product uses untrusted input when calculating or using an array index, but the product does not validate or incorrectly validates the index to ensure the index references a valid position within the array.
- [Architecture and Design] Use an input validation framework such as Struts or the OWASP ESAPI Validation API. Note that using a framework does not automatically address all input validation problems; be mindful of weaknesses that could arise from misusing the framework itself (CWE-1173).
- [Architecture and Design] For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server. Even though client-side checks provide minimal benefits with respect to server-side security, they are still useful. First, they can support intrusion detection. If the server receives input that should have been rejected by the client, then it may be an indication of an attack. Second, client-side error-checking can provide helpful feedback to the user about the expectations for valid input. Third, there may be a reduction in server-side processing time for accidental input errors, although this is typically a small savings.
Source: MITRE CWE corpus.
References
- huntr.com/bounties/921ba5d4-f1d0-4c66-9764-4f72dffe7acd Exploit 3rd Party
- github.com/ARPSyndicate/cve-scores Exploit
Timeline
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