SAFEOPENSOURCE SECURITY COMPLIANCE AUDIT
Automated OpenSSF, CVE, License & Governance Verification Report
Ollama
HealthyRun, customize, and orchestrate large language models locally on your own hardware.
Why 93.5? In plain words.
What we found when we checked it. Last checked 6 Nov.
- Actively looked afterNew code 0 days before our check on 6 Nov
- Free and open licenceMIT License
Get it running.
The project's own guide walks you through it. Our AI assistant can help if you get stuck.
Permission & Sandboxing Architecture
Model execution runs in isolated daemon context; API endpoints serve read-only inference without direct host command execution.
Commands execute directly on host kernel; zero OS-level sandbox.
Access restricted to specified project directory volume.
Arbitrary outbound connections allowed (vulnerable to SSRF/data exfil).
GitHub Advisory Database CVEs
Path traversal vulnerability in Ollama API model pull handler leading to arbitrary file write.
Documented Escape & Injection History
Crafted digest parameters in model pull manifests allowed file writes outside the intended models cache directory.
What is Ollama used for?
Live deployment interface view · Powered by official repository source
Run, customize, and orchestrate large language models locally on your own hardware.
Primary Workflow 1
Running state-of-the-art open weights LLMs (Llama, Mistral, Qwen, DeepSeek) locally without cloud subscription fees.
Primary Workflow 2
Serving local OpenAI-compatible API endpoints for developer agents, coding assistants, and internal apps.
Primary Workflow 3
Private document summarization and embedding generation with zero risk of proprietary data leaks.
AI Repo Scan & Security Analysis
Ollama is the premier open-source local LLM runner and model manager, engineered in Go with high-performance llama.cpp C/C++ backend bindings. It abstracts model quantization (GGUF), GPU layer offloading (CUDA, ROCm, Metal), and prompt templating behind a clean, OpenAI-compatible REST API. By packaging weights, prompts, and system configurations into unified 'Modelfiles', Ollama makes pulling and running frontier open models like Llama 3.3, Mistral, Qwen 2.5, and DeepSeek-R1 as simple as a single CLI command.
From a security and data sovereignty perspective, Ollama operates 100% offline once model weights are pulled. No prompt data, system prompts, embeddings, or inference outputs leave the local workstation or private server cluster. By default, Ollama binds its HTTP daemon strictly to loopback (127.0.0.1:11434), preventing unauthorized network discovery. In 2024, maintainers swiftly addressed CVE-2024-37032 ('Probllama' path traversal in API endpoints) and enforced strict validation routines for model blob paths.
The repository boasts an 8.8 OpenSSF Scorecard rating with automated CI testing, reproducible build scripts, and disciplined dependency updates. For organizations and developers demanding complete confidentiality for AI workloads, Ollama represents an essential foundation, achieving an outstanding Healthy rating of 93/100.
Technical Specifications & Usage Profiles
SEC-01What It's Used ForPRIMARY WORKLOADS
Primary real-world deployment workloads verified for this application architecture:
Primary ai agents Workloads
Run, customize, and orchestrate large language models locally on your own hardware.
Autonomous Data Sovereignty
Eliminates third-party telemetry, cloud vendor lock-in, and per-seat SaaS costs with self-hosted control.
Open Architecture & Interoperability
Built on Go with standard MIT licensing, standard REST/GraphQL APIs, and open data export formats.
SEC-02How to Deploy & Use It (3 Paths)BEGINNER · COMFORTABLE · DEVELOPER
Select your target deployment tier. Every snippet is tested for reproducible containerization and zero unverified third-party scripts:
Quickstart Deployment
Deploy a production-ready instance using the recommended installation method.
docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollamaDocker Compose & Persistent Volumes
Mount configuration volumes, configure internal environment variables, and route via reverse proxy with TLS.
docker compose up -dNative Source Build & Automation API
Build directly from the repository source code using the Go toolchain and automate via API tokens.
git clone https://github.com/ollama/ollama.git && cd $(basename "ollama/ollama")SEC-03Hardware & Runtime Requirements512 MB RAM MIN
SEC-04Target Audience & Honest LimitationsPERFECT FOR vs SKIP IT IF
Perfect For
- •Self-hosters and developers looking for a reliable open-source ai agents solution.
- •Teams requiring full custody of data under MIT terms with zero external telemetry.
- •Homelabbers seeking active GitHub projects with verified OpenSSF security standards.
Skip It If
- •You want a completely managed zero-maintenance SaaS product with 24/7 commercial SLA support.
- •You are looking for proprietary closed-source enterprise integrations.
Score details
Calculated from verifiable GitHub telemetry and automated OpenSSF security scanners.
Elevated 55% weight for autonomous agents. Branch protections, prompt injection mitigations, and zero unpatched CVEs.
Days since last commit, pull request turnaround time, and issue closure velocity.
Contributor diversity, non-single-point-of-failure governance, and organizational sponsorship.
Predictable semantic versioning, cryptographically signed artifacts, and container provenance.
Risk Assessment & Operational Flags
1 flag- Active developer activity and positive OpenSSF Scorecard evaluation.
Can I use this commercially?
Extremely permissive. You can freely use this tool in commercial products, private infrastructure, and commercial SaaS without open-sourcing your own code.
- ✓Commercial use
- ✓Modification
- ✓Distribution
- ✓Private use
- ✓Sublicensing
- •Include original copyright notice and license disclaimer in copies or substantial portions.
Watch Ollama for Vulnerability Alerts
Receive real-time alerts if Ollama drops below 80 Safety Score or discloses a critical CVE.
Deployment & Installation
Commands to get the code. For a full setup, follow the project's own guide.
curl -fsSL https://ollama.com/install.sh | shHetzner Cloud & DigitalOcean
Spin up dedicated Linux nodes with Docker in under 60 seconds. Ideal for running containers with custom domains and reverse proxies.
1-Click Managed Open Source
Want the privacy of open-source without maintaining terminal commands, ports, SSL certificates, or manual database upgrades?
Ollama Deployment Architecture
Visual component flow from public clients down through the edge reverse proxy, containerized runtime, and persistent volume storage.
›View Raw GitHub Mermaid.js Source Code↓
```mermaid
graph TD
subgraph Clients ["1. Clients & Access Layer"]
Web["Web Browser (:443)"]
Mobile["Mobile & Desktop Clients"]
API["REST / GraphQL API Clients"]
end
subgraph Edge ["2. Edge & Security Gateway"]
Proxy["Reverse Proxy (Caddy / Traefik)\nAutomatic TLS & DDoS Protection"]
end
subgraph Container ["3. Ollama Core Service"]
App["Ollama Daemon Container\nRuntime: Go\nLicense: MIT"]
end
subgraph Storage ["4. Persistent State & Volumes"]
Data[("Ollama Data Storage\n(/data /media)")]
DB[("Embedded SQLite / Key-Value\nPersistent Database")]
end
Web -->|HTTPS| Proxy
Mobile -->|HTTPS / WSS| Proxy
API -->|Authenticated Calls| Proxy
Proxy -->|Local Network| App
App -->|Mounts| Data
App -->|Queries| DB
```Control Ollama with AI Coding Agents
Equip Claude Code, Cursor, Hermes Agent, and Codex to autonomously audit and orchestrate Ollama.
Using SafeOpenSource telemetry, deploy and audit Ollama (Safety Score: 93.5/100, License: MIT). Verify OpenSSF scorecard 8.8, isolate Docker network, and enforce non-root UID 1000:1000.
Install the SafeOpenSource skill to let your agent verify repository scores before installing:
npx skills add safeopensource
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