All analysis was generated autonomously, without human review. Scores are analytical opinions drawn from the cited public sources, without hands-on testing. They are not audits, certifications, investment reports, purchasing advice, or evaluations of quality.
NVIDIA's garak is one of the most widely used open-source scanners for large-language-model weaknesses, and because it is free it is a credibility play for NVIDIA rather than a business. It runs a library of over a hundred known attack probes at a model and reports what got through. It earns no revenue, so its return is the standing it buys in AI security rather than a product line. That design has a ceiling. garak leans on a curated library of known-class probes, and an independent comparison notes it does not generate the novel, application-specific attacks an application-aware tool like Promptfoo produces. It leads on breadth and research pedigree while rivals compete on tailoring attacks to each deployment.
How well the company can compete in its security market, scored across eight dimensions against public evidence.
| Dimension | Score |
|---|---|
| Problem Clarity How precisely the company defines its problem, with evidence the problem exists at the scale claimed. | 3/5 |
| Capability Depth How specific the technical capabilities are, with evidence beyond marketing claims such as docs, demos, and third-party validation. | 4/5 |
| Market Timing Whether the market is ready for this product, with evidence that buyers are actively seeking solutions. | 3/5 |
| Team Credibility Demonstrated domain expertise with public signals such as prior exits, publications, and industry recognition. | 3/5 |
| GTM Proof Evidence of actual traction (customers, revenue signals, partnerships) beyond stated intentions. | 2/5 |
| Funding Efficiency Whether funding matches go-to-market ambition, with signs of capital-efficient growth. | 2/5 |
| Category Clarity Whether the company creates or fits a recognizable category that buyers can quickly place in their stack. | 4/5 |
| Incumbent Defensibility How vulnerable the core value proposition is to absorption as a feature by a platform vendor. | 2/5 |
Unlock the Full Analysis
This analysis is part of the NVIDIA profile. The reasoning for the scores, the strategy deep dive, the business risks, and more. One purchase covers the NVIDIA strategy synthesis and all 2 analyzed product lines (NeMo Guardrails, garak), plus any lines we analyze later during your access. AI access comes with the purchase, so your AI tools can read the full profile too. You keep 12 months of access.
One-time purchase: $40 for the full NVIDIA profile.
UnlockReading several? Unlock the entire catalog.
A closer look at this line's product strategy, measuring how defensible it is against market forces and examining the eight areas behind it.
pivot urgently
| Dimension | Score |
|---|---|
| Value Delivery Does the product sell software as the product, or judgment, trust, or accountability with software as the delivery mechanism. | 1/3 |
| Switching Cost How expensive leaving is for a customer: data portability, integrations, learned workflows, network effects, regulatory data residency. | 1/3 |
| Compliance Moat Whether certifications, liability acceptance, or audit trails block an easy replacement. | 1/3 |
| Problem Complexity Whether the product requires ML, optimization, real-time systems, or years of specialized expertise. | 2/3 |
| Buyer Profile Whether buyers are SMB operators, mid-market IT teams, or regulated enterprises and governments with procurement gates. | 1/3 |
| Layer Whether the product is an end-user application, a platform with application features, or infrastructure other applications depend on. | 1/3 |
| Proprietary Data, Content, or IP Whether the product accumulates datasets, content licenses, or IP that a rival cannot recreate from scratch. | 1/3 |
Unlock the Full Analysis
This analysis is part of the NVIDIA profile. The reasoning for the scores, the strategy deep dive, the business risks, and more. One purchase covers the NVIDIA strategy synthesis and all 2 analyzed product lines (NeMo Guardrails, garak), plus any lines we analyze later during your access. AI access comes with the purchase, so your AI tools can read the full profile too. You keep 12 months of access.
One-time purchase: $40 for the full NVIDIA profile.
UnlockReading several? Unlock the entire catalog.
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | NVIDIA/garak repository “garak checks if an LLM can be made to fail in a way we don't want. garak probes for hallucination, data leakage, prompt injection, jailbreaks, and many other weaknesses. If you know nmap or Metasploit, garak does similar things for LLMs.” | official | 2026-06-27 |
| s2 | GitHub API: NVIDIA/garak repository metrics “stargazers_count: 8242, forks_count: 1049, license: Apache-2.0, created_at: 2023-05-10, pushed_at: 2026-06-26” | official | 2026-06-27 |
| s3 | garak: A Framework for Security Probing Large Language Models “garak: A Framework for Security Probing Large Language Models. Authors: Leon Derczynski, Erick Galinkin, Jeffrey Martin, Subho Majumdar, Nanna Inie. This paper introduces garak, the Generative AI Red-teaming and Assessment Kit.” | research | 2026-06-27 |
| s4 | Fujitsu Research comparative evaluation of LLM red-teaming tools (RAIE 2025) “Garak excels in vulnerability coverage with over 20 specific attack-evaluation pairs, focusing on jailbreak attacks grounded in established research. It focuses on static attacks and static evaluators. High error rates in the evaluator component are evident across all tools.” | research | 2026-06-27 |
| s5 | netguardia: The best AI red-teaming tools of 2026 “Garak is the most mature open-source LLM scanner. These are static, research-backed attacks, which is both the strength and the constraint, Garak finds known classes of vulnerabilities consistently, but it doesn't generate novel attacks tuned to your specific application.” | press | 2026-06-27 |
| s6 | Help Net Security: garak open-source LLM vulnerability scanner “Garak is a free, open-source tool designed to test these weaknesses. It checks for problems like hallucinations, prompt injections, jailbreaks, and toxic outputs. Garak is available for free on GitHub.” | press | 2026-06-27 |
| s7 | Databricks engineering tutorial: applying NVIDIA's garak to LLMs on Databricks “NVIDIA's AI Red Team introduced Garak, the Generative AI Red-teaming and Assessment Kit. Garak is an open-source tool designed to probe LLMs for vulnerabilities. The probe corpus consists of more than 150 different attacks.” | other | 2026-06-27 |
| s8 | Promptfoo vs garak comparison (Promptfoo is now part of OpenAI) “Garak focuses on known LLM exploits. Approach: Curated library of research-backed attacks. Attack Generation: Static with buff perturbations. Agent Security: Limited. License: Apache-2.0.” | other | 2026-06-27 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | NVIDIA/garak repository “garak checks if an LLM can be made to fail in a way we don't want. garak probes for hallucination, data leakage, prompt injection, jailbreaks, and many other weaknesses. If you know nmap or Metasploit, garak does similar things for LLMs.” | official | 2026-06-27 |
| s2 | GitHub API: NVIDIA/garak repository metrics “stargazers_count: 8242, forks_count: 1049, license: Apache-2.0, created_at: 2023-05-10, pushed_at: 2026-06-26” | official | 2026-06-27 |
| s3 | garak: A Framework for Security Probing Large Language Models “garak: A Framework for Security Probing Large Language Models. Authors: Leon Derczynski, Erick Galinkin, Jeffrey Martin, Subho Majumdar, Nanna Inie. This paper introduces garak, the Generative AI Red-teaming and Assessment Kit.” | research | 2026-06-27 |
| s4 | Fujitsu Research comparative evaluation of LLM red-teaming tools (RAIE 2025) “Garak excels in vulnerability coverage with over 20 specific attack-evaluation pairs, focusing on jailbreak attacks grounded in established research. It focuses on static attacks and static evaluators. High error rates in the evaluator component are evident across all tools.” | research | 2026-06-27 |
| s5 | netguardia: The best AI red-teaming tools of 2026 “Garak is the most mature open-source LLM scanner. These are static, research-backed attacks, which is both the strength and the constraint, Garak finds known classes of vulnerabilities consistently, but it doesn't generate novel attacks tuned to your specific application.” | press | 2026-06-27 |
| s6 | Help Net Security: garak open-source LLM vulnerability scanner “Garak is a free, open-source tool designed to test these weaknesses. It checks for problems like hallucinations, prompt injections, jailbreaks, and toxic outputs. Garak is available for free on GitHub.” | press | 2026-06-27 |
| s7 | Databricks engineering tutorial: applying NVIDIA's garak to LLMs on Databricks “NVIDIA's AI Red Team introduced Garak, the Generative AI Red-teaming and Assessment Kit. Garak is an open-source tool designed to probe LLMs for vulnerabilities. The probe corpus consists of more than 150 different attacks.” | other | 2026-06-27 |
| s8 | Promptfoo vs garak comparison (Promptfoo is now part of OpenAI) “Garak focuses on known LLM exploits. Approach: Curated library of research-backed attacks. Attack Generation: Static with buff perturbations. Agent Security: Limited. License: Apache-2.0.” | other | 2026-06-27 |
This site is an experimental research aid created by Zeltser Security Corp. All its data gathering and analysis was performed autonomously without human review, and it can contain errors of fact, interpretation, and judgment that a human reviewer might catch.
The analyses are statements of opinion, not statements of fact. Machine analysis produced the scores, summaries, and matrix placements by weighing the public sources each page cites, and reasonable people can weigh the same sources differently. Where a page states a fact, it cites the public source and the date it was checked, and the statement is only as accurate as that source. Unless a profile expressly says otherwise, the analysis involves no hands-on testing and no independent validation of any company's products or services.
Nothing here is professional, security, legal, financial, investment, or purchasing advice, and nothing here is a recommendation to invest in, do business with, or avoid any company. Inclusion of a company is not an endorsement, and absence of a company is not a judgment about it. Reading this site creates no advisory or client relationship. Verify any detail you plan to act on against the vendor's current materials.
The content is provided "as is" and "as available," with all warranties disclaimed, express or implied, including merchantability, fitness for a particular purpose, accuracy, and non-infringement. No entry is warranted to be complete, current, or correct. Companies change, vendors update their claims, sources can be wrong, and automated analysis can misread them.
To the fullest extent permitted by law, the operator, Zeltser Security Corp, is not liable for any damages that arise from using this site or relying on its content, including direct, indirect, incidental, special, and consequential damages and lost profits, even if advised that such damages were possible. If you are dissatisfied with the site or disagree with these terms, your remedy is to stop using it.
Entries link to vendor pages, press coverage, and other external sites that Zeltser Security Corp does not control and is not responsible for. A link is not an affiliation with the destination or an endorsement of it. Product and company names and trademarks are the property of their owners, used here nominatively to identify the companies described. Short quotations from cited sources appear for identification and commentary.
Do not republish its content or share access without the operator's permission.