Ollama before 0.17.1 contains a heap out-of-bounds read vulnerability in the GGUF model loader. The /api/create endpoint accepts an attacker-supplied GGUF file in which the declared tensor offset and size exceed the file's actual length; during quantization in fs/ggml/gguf.go and server/quantization.go (WriteTo()), the server reads past the allocated heap buffer. The leaked memory contents may include environment variables, API keys, system prompts, and concurrent users' conversation data, and can be exfiltrated by uploading the resulting model artifact through the /api/push endpoint to an attacker-controlled registry. The /api/create and /api/push endpoints have no authentication in the upstream distribution. Default deployments bind to 127.0.0.1, but the documented OLLAMA_HOST=0.0.0.0 configuration is widely used in practice (large public-internet exposure observed).

ollama

Ollama for Windows contains a Remote Code Execution vulnerability in its update mechanism due to improper handling of attacker‑controlled HTTP response headers. When downloading updates, the application constructs local file paths using values derived from HTTP headers without validation. These values are passed directly to filepath.Join, allowing path traversal sequences (../) to be resolved and enabling files to be written outside the intended update staging directory. An attacker who can influence update responses can exploit this flaw to write arbitrary executables to attacker‑chosen locations accessible to the current user, including the Windows Startup directory. This allows execution of arbitrary executables. Critically, when chained with CVE‑2026‑42248 (Missing Signature Verification for Updates), an attacker can deliver malicious payloads that are written to sensitive locations and executed automatically. Because Ollama for Windows performs silent automatic updates and executes staged binaries without user interaction, this results in automatic and persistent code execution without user awareness. Maintainers of this project were notified early about this vulnerability, but didn't respond with the details of vulnerability or vulnerable version range. Versions from 0.12.10 to 0.17.5 were tested and confirmed as vulnerable, other versions were not tested but might also be vulnerable.

ollama · microsoft

Ollama for Windows does not perform integrity or authenticity verification of downloaded update executables. Unlike other platforms, the Windows implementation of the update verification routine unconditionally returns success so no digital signature or trust validation is performed before staging or executing update payloads, enabling attacker‑supplied executables to be accepted and later executed by the application. Critically, Ollama for Windows performs silent automatic updates, so the malicious payload may be installed automatically without user awareness. Maintainers of this project were notified early about this vulnerability, but didn't respond with the details of vulnerability or vulnerable version range. Versions from 0.12.10 to 0.17.5 were tested and confirmed as vulnerable, other versions were not tested but might also be vulnerable.

ollama · microsoft

A security flaw has been discovered in Ollama up to 0.20.2. This affects the function digestToPath of the file x/imagegen/transfer/transfer.go of the component Tensor Model Transfer Handler. The manipulation of the argument digest results in path traversal. The attack may be performed from remote. This attack is characterized by high complexity. The exploitability is reported as difficult. The exploit has been released to the public and may be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.

ollama

KubeAI is an AI inference operator for kubernetes. Prior to 0.23.2, the ollamaStartupProbeScript() function in internal/modelcontroller/engine_ollama.go constructs a shell command string using fmt.Sprintf with unsanitized model URL components (ref, modelParam). This shell command is executed via bash -c as a Kubernetes startup probe. An attacker who can create or update Model custom resources can inject arbitrary shell commands that execute inside model server pods. This vulnerability is fixed in 0.23.2.

kubeai

A flaw has been found in Ollama up to 0.18.1. This issue affects some unknown processing of the file server/download.go of the component Model Pull API. Executing a manipulation can lead to server-side request forgery. The attack can be launched remotely. The vendor was contacted early about this disclosure but did not respond in any way.

Wallos is an open-source, self-hostable personal subscription tracker. Prior to version 4.7.0, the patch introduced in commit e8a513591 (CVE-2026-30840) added SSRF protection to notification test endpoints but left three additional attack surfaces unprotected: the AI Ollama host parameter, the AI recommendations endpoint, and the notification cron job. An authenticated user can reach internal network services, cloud metadata endpoints (AWS IMDSv1, GCP, Azure IMDS), or localhost-bound services by supplying a crafted URL to any of these endpoints. This issue has been patched in version 4.7.0.

wallosapp

Ollama MCP Server execAsync Command Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Ollama MCP Server. Authentication is not required to exploit this vulnerability. The specific flaw exists within the implementation of the execAsync method. The issue results from the lack of proper validation of a user-supplied string before using it to execute a system call. An attacker can leverage this vulnerability to execute code in the context of the service account. Was ZDI-CAN-27683.

An issue in ollama v.0.12.10 allows a remote attacker to cause a denial of service via the fs/ggml/gguf.go, function readGGUFV1String reads a string length from untrusted GGUF metadata

ollama

An issue in ollama v.0.12.10 allows a remote attacker to cause a denial of service via the GGUF decoder

ollama

Ollama 0.11.5-rc0 through current version 0.13.5 contain a null pointer dereference vulnerability in the multi-modal model image processing functionality. When processing base64-encoded image data via the /api/chat endpoint, the application fails to validate that the decoded data represents valid media before passing it to the mtmd_helper_bitmap_init_from_buf function. This function can return NULL for malformed input, but the code does not check this return value before dereferencing the pointer in subsequent operations. A remote attacker can exploit this by sending specially crafted base64 image data that decodes to invalid media, causing a segmentation fault and crashing the runner process. This results in a denial of service condition where the model becomes unavailable to all users until the service is restarted.

ollama

A critical authentication bypass vulnerability exists in Ollama platform's API endpoints in versions prior to and including v0.12.3. The platform exposes multiple API endpoints without requiring authentication, enabling remote attackers to perform unauthorized model management operations.

ollama

An issue in Ollama v0.1.33 allows attackers to delete arbitrary files via sending a crafted packet to the endpoint /api/pull.

ollama

Cross-Domain Token Exposure in server.auth.getAuthorizationToken in Ollama 0.6.7 allows remote attackers to steal authentication tokens and bypass access controls via a malicious realm value in a WWW-Authenticate header returned by the /api/pull endpoint.

ollama

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.

ollama

open-webui v0.5.16 is vulnerable to SSRF in routers/ollama.py in function verify_connection.

openwebui

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 crash and resulting in a Denial of Service (DoS) attack.

ollama

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.

ollama

A vulnerability in ollama/ollama versions <=0.3.14 allows a malicious user to create a customized GGUF model file that, when uploaded and created on the Ollama server, can cause a crash due to an unchecked null pointer dereference. This can lead to a Denial of Service (DoS) attack via remote network.

ollama

A divide by zero vulnerability exists in ollama/ollama version v0.3.3. The vulnerability occurs when importing GGUF models with a crafted type for `block_count` in the Modelfile. This can lead to a denial of service (DoS) condition when the server processes the model, causing it to crash.

ollama

An Out-Of-Memory (OOM) vulnerability exists in the `ollama` server version 0.3.14. This vulnerability can be triggered when a malicious API server responds with a gzip bomb HTTP response, leading to the `ollama` server crashing. The vulnerability is present in the `makeRequestWithRetry` and `getAuthorizationToken` functions, which use `io.ReadAll` to read the response body. This can result in excessive memory usage and a Denial of Service (DoS) condition.

A vulnerability in Ollama versions <=0.3.14 allows a malicious user to create a customized gguf model file that can be uploaded to the public Ollama server. When the server processes this malicious model, it crashes, leading to a Denial of Service (DoS) attack. The root cause of the issue is an out-of-bounds read in the gguf.go file.

ollama