CVE-2026-7482 is a high-risk vulnerability in Ollama that occurs during GGUF model file processing. The issue is caused by a heap-based out-of-bounds read, which may allow unintended memory data from the Ollama server process to be exposed. If exploited, an attacker could submit a crafted GGUF model file and potentially leak sensitive information such as API keys, environment variables, system prompts, internal instructions, and user conversation data. The risk is higher when Ollama APIs such as /api/create and /api/push are exposed without proper access control. This vulnerability affects Ollama versions prior to 0.17.1. Affected environments should upgrade to Ollama 0.17.1 or later, restrict external API access, and review exposed instances for suspicious model creation or data transfer activity. 1. Overview CVE-2026-7482 is a high-severity vulnerability discovered in Ollama, an open-source platform that enables users to run Large Language Models (LLMs) locally and in server environments. This flaw is classified as a Heap-based Out-of-Bounds Read, which occurs during the process of loading and parsing GGUF model files within Ollama. Attack Vector & Impact An attacker can trigger this vulnerability by uploading a specially crafted, malicious GGUF file to a vulnerable Ollama server. Successful exploitation allows unauthorized reading of the server process memory space. This can lead to the exposure of highly sensitive information, including environment variables, integrated API keys, system prompts, and chat histories of other users. Exposure Risks In certain Ollama deployment environments, APIs associated with model creation and uploading (such as /api/create and /api/push) may be exposed to the internet without proper authentication. In such scenarios, an attacker can cause severe data leakage simply by submitting a manipulated model file. Affected Versions & Mitigation This vulnerability affects all Ollama versions prior to 0.17.1. Vendors and security advisories strongly recommend that users immediately upgrade to version 0.17.1 or higher, where the patch has been applied. 2. Root Cause Analysis and Attack Vector Attack Flow and Accessibility Initial Access: CVE-2026-7482 can be exploited via exposed Ollama APIs without requiring any prior authentication. Remote attackers can easily access the vulnerability if the Ollama server is exposed to an external network or bound to 0.0.0.0. Exploitation Process: The attack begins when a perpetrator submits a malicious GGUF file containing manipulated metadata to the server. The attacker then requests model creation based on this file, triggering an out-of-bounds memory read within the server process. Exfiltration Mechanism: The leaked memory data is captured and embedded into the newly generated model artifact. The attacker can then exploit Ollama’s model registry push feature to exfiltrate this sensitive data to an external server or a registry under their control. Root Cause The core vulnerability stems from insufficient validation of GGUF file metadata and inadequate memory boundary checks. Ollama fails to cross-verify the tensor offset and size information declared in the GGUF file against the actual file size. Consequently, this allows the system to attempt to read data outside the file’s legitimate boundaries. When the model processing and quantization logic references the buffer—blindly trusting the declared metadata—it reads beyond the boundaries of the allocated heap buffer into other memory spaces within the server process. This results in a Heap-based Out-of-Bounds Read. Technical analyses indicate that this flaw specifically occurs within the WriteTo() function during the GGUF loading and quantization processes. Exfiltrated Data Targets Server memory data exposed through the out-of bounds read is incorporated into the resulting model artifacts. By pushing these artifacts to an external registry, attackers can exfiltrate highly sensitive information. Publicly available analyses highlight that the following types of data are at risk of exposure: System Control Information Critical environment variables, including API keys, authentication tokens, and database connection strings. AI Model Assets System prompts, internal instructions, and security policy configurations. User Data Prompts, chat histories, and outputs from external tool integrations belonging to other users. 3. Impact and Business Implications Threat Scale and Attack Indicators Global Exposure: Recent security research indicates that a significant number of Ollama servers worldwide are currently exposed to the internet. High-Severity Risk: CVE-2026-7482 is a Critical-rated vulnerability with a CVSS score of 9.1. Because it can be exploited without authentication, the risk is exceptionally high for any publicly exposed environment. Exploitation Potential: With Proof-of-Concept (PoC) exploits publicly available, there is a severe risk of automated scanning and large-scale, opportunistic attacks. Core Asset and Sensitive Data Leakage A successful exploitation allows attackers to exfiltrate critical information residing in the server’s memory. This includes: Environment Variables: API keys, authentication tokens, and database connection strings. Read more about [2026.05 Vulnerability Report] Ollama Memory Information Disclosure Vulnerability Analysis (CVE-2026-7482)[…]
