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Sentinel RED is a self-hosted, modular suite that sends attack and quality probes at an LLM application and reports how it behaves. It targets prompt injection, hallucinations, data leakage, adversarial robustness, data poisoning, and policy compliance. Its vendor describes it as a testing tool, not a guarantee of security, and the evidence for its effectiveness currently comes from the vendor and its public repository rather than independent testing.
The name is shared with other projects, including an AWS sample harness and an unrelated agent action-gate. This article covers only Sentinel RED, the AI security and quality testing suite published at sentinelred.dev, with its source code at the public NenXMaster-AB/sentinel repository.
What Sentinel RED tests
The vendor’s homepage describes the product as a modular testing suite for LLM apps that measures prompt-injection resistance, detects hallucinations, probes data leakage, and produces actionable reports. The linked repository lists the same areas and adds data-poisoning probes, adversarial robustness, and policy compliance. These are documented product scope, not proof that the tool catches every issue in those categories.
| Area | Examples the vendor lists |
|---|---|
| Prompt injection | Direct and indirect injection, multi-turn escalation, encoding tricks |
| Hallucinations | Known-answer QA, citation checks |
| Data leakage | PII recall probes, credential leakage |
| Adversarial testing | Jailbreak fuzzing, tool-use abuse |
| Poisoning | Trigger probes |
| Compliance | Policy validation |
The homepage advertises “6 modules” and “85+ attack patterns.” Its sample live console refers to an 86-pattern attack library and shows example module scores. Treat those figures as the vendor’s own claims and illustrative interface content. They are not an independently verified inventory or a measured result for any particular application.
#1 Best Overall
How a test run works
The documented workflow has five stages:
- Configure a target. Point Sentinel RED at an API endpoint or a locally running model or application.
- Choose modules and depth. Select which of the six areas to run and how deep the probing goes.
- Run the suite. Start the test run from the dashboard or through the REST API.
- Inspect streamed results. Results stream in while the run is in progress.
- Generate a PDF report. Export the findings once the run finishes.
Provider credentials for model targets can be supplied as environment variables or entered in the dashboard settings. Keep them out of shared configuration files and screenshots.
Deploying it locally
The installation guide at sentinelred.dev/install recommends cloning the GitHub repository and starting the stack with Docker Compose. The dashboard then runs at localhost:3000. Use the exact repository URL from the installation page; the README contains a placeholder clone example that uses a different organization name.
Rank #2
You need Git and Docker with Compose available on the host. Expect to run several services at once, because the repository documents the following components:
- Backend: Python 3.12 or later, FastAPI, SQLAlchemy, and Celery for background jobs
- Data: PostgreSQL 16 with TimescaleDB, and Redis 7
- Frontend: React 18, TypeScript, Vite, and Tailwind
These versions come from the repository README. Check the current branch before following version-specific steps, because the stack may have changed since the README was written.
How Sentinel RED compares to Promptfoo and PyRIT
Sentinel’s own comparison page at sentinelred.dev/compare states, “There’s no single ‘best’ tool.” It presents the three tools as suited to different jobs. This is the vendor’s positioning, not an independent head-to-head test.
| Tool | Vendor-described strength | Typical fit |
|---|---|---|
| Sentinel RED | Unified suite with opinionated modules, common scoring, and reporting | Teams that want a ready-made test set, dashboard, and PDF reports |
| Promptfoo | Repeatable prompt, model, and RAG evaluation with CI regression | Teams that run the same checks on every change |
| PyRIT | Programmable framework for custom security-research workflows | Teams building their own attack logic |
When choosing among them, compare these points rather than looking for an automatic winner:
- Goal. Is it ongoing CI regression, or a broader red-team campaign?
- Interface. Do you want an opinionated UI and reports, or a programmable framework?
- Extensibility. How easily can you add attacks and custom adapters for your stack?
- Deployment and secrets. Is local or hosted operation required, and how are API keys handled?
- Maintenance and license. How active is the project, and does its license fit your use?
Licensing
The repository identifies its license as AGPL-3.0, not a permissive license. Under AGPL-3.0, if you modify the software and make it available to users over a network, you generally must offer those users the corresponding source of your modified version. Internal use and unmodified self-hosting carry different obligations. Have counsel review the terms against your deployment before you build it into a product or a service.
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Sentinel RED links to the OWASP Top 10 for Large Language Model Applications. OWASP’s project page at owasp.org/projects/top-10-for-large-language-model-applications explains that the work now sits within the broader OWASP GenAI Security Project and points to the latest Top 10. Use OWASP as a risk taxonomy. Check the current list before mapping Sentinel’s modules to its categories. Sentinel RED is not OWASP-certified, and nothing in the vendor material shows that it implements the full Top 10.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the public evidence covers
Most of the information about Sentinel RED comes from the vendor’s website and the public repository. The official changelog at sentinelred.dev/changelog lists two entries from February 2026: an internal JSX prototype on 2026-02-01 and a landing page and product positioning update on 2026-02-13. The changelog does not show release cadence, customers, production deployments, or independent validation of coverage or scores.
The GitHub repository was small and had one star when it was reviewed. Those counters change and do not indicate quality either way. Before relying on the tool for anything important, run it against a test application you control and judge the findings yourself.
Frequently Asked Questions
Can I run Sentinel RED in a CI pipeline?
The vendor’s homepage uses the phrase “CI-friendly,” and the REST API can create runs and poll them, so a pipeline job could in principle start a test and wait for the PDF report. The available documentation does not include a tested CI template, so you would need to build and verify that job yourself. If your main goal is repeatable regression checks in CI, the comparison above is the place to weigh Promptfoo against Sentinel RED.
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The Bottom Line
Sentinel RED is worth evaluating if you want a self-hosted, opinionated suite that covers injection, hallucination, leakage, robustness, poisoning, and compliance in one dashboard. Confirm the AGPL-3.0 license fits your use, run it against an application you own, and treat its scores and attack counts as the vendor’s own figures until you have verified them.
Quick Recap
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