The AI Security Arms Race Is Real — and Confusing
As organizations rush to deploy AI models in production, a quieter but equally urgent race is underway: securing those models from adversarial attacks, data poisoning, prompt injection, and supply chain compromise. A new category of vendors has emerged to address this, and the differences between them are anything but cosmetic. This article is based on AI Compare's dataset for AI Security & Safety Platforms Comparison, which evaluates six platforms across 47 comparison dimensions. The full breakdown is available at aicompare.dev/compare/ai-security.
The six platforms under the microscope are: Protect AI, HiddenLayer, Robust Intelligence (now part of Cisco), Lakera, CalypsoAI, and Adversa AI. Each approaches the problem from a different angle, and choosing the wrong one could leave critical gaps in your AI risk posture.
Different Philosophies, Different Strengths
The most striking thing about this space is how differently each vendor defines the problem. Protect AI, founded in 2022 and headquartered in Seattle, positions itself as an end-to-end ML security and supply chain platform. With approximately $108M raised through its Series B in October 2024, it's the best-funded private player in this group. Its product suite — Guardian for model scanning, Radar for ML bill-of-materials visibility, and Layer for runtime guardrails — reflects a broad ambition to own the full lifecycle. It also maintains an open-source portfolio including ModelScan, NB Defense, and LLM Guard, and operates huntr.com, which it claims is the world's largest AI/ML bug bounty platform.
HiddenLayer, also founded in 2022 and based in Austin, TX, takes a more detection-focused approach. Its AISec Platform spans model scanning, ML detection and response (MLDR), and AI Detection & Response. With ~$56M in Series A funding, it's the second-best-funded private vendor here. Importantly, HiddenLayer supports AI/ML SBOM generation — a feature only it and Protect AI offer among this group — and it supports both air-gapped and FedRAMP deployment, making it a credible option for defense and intelligence use cases.
Robust Intelligence, acquired by Cisco in 2024 after raising ~$44M pre-acquisition, is the only platform here backed by a public company. That acquisition means it can now leverage Cisco's enterprise distribution and FedRAMP infrastructure. Its core offering spans AI Firewall, continuous AI Validation, and red teaming capabilities. However, its model supply chain security is listed as limited compared to Protect AI and HiddenLayer, and it doesn't offer an AI/ML SBOM — a potential gap for organizations with rigorous compliance requirements.
LLM-Focused vs. Broad ML Security: A Real Tradeoff
Not every buyer needs the same thing. Lakera, a Zurich-based startup founded in 2021 with ~$20M in Series A funding, is the clearest specialist in this group. Its Lakera Guard is an API-based guardrail and prompt injection defense product — elegant, focused, and relatively easy to integrate. But buyers should understand what they're not getting: no model vulnerability scanning, no data poisoning detection, no model supply chain security, no AI/ML SBOM, and no model risk scoring. Lakera is purpose-built for LLM runtime defense, and it excels there — but it's not a comprehensive ML security platform.
CalypsoAI, headquartered in Washington, D.C. and founded in 2018 — the oldest company in this comparison — has a notably different customer base. With over $68M raised including U.S. government contracts, its Moderator product is designed around real-time AI policy enforcement and content filtering. It supports air-gapped and FedRAMP-ready deployment, which explains its government traction. However, CalypsoAI does not offer adversarial testing or red teaming capabilities, and it lacks model vulnerability scanning and data poisoning detection. For regulated government environments prioritizing governance and policy enforcement, it fits well. For ML teams wanting deep technical security, it's a narrower fit.
Adversa AI, based in Tel Aviv and founded in 2019, is the smallest player by funding (~$5M seed) but occupies a distinct niche: adversarial AI red teaming and robustness testing. Its platform focuses on automated adversarial testing and audits, with strong model vulnerability scanning and risk scoring. But it offers no LLM guardrails, no AI firewall, no model supply chain security, and no air-gapped deployment. It's arguably best positioned as a testing and audit tool rather than a production runtime defense platform.
The Capability Gaps That Actually Matter
When you map these platforms against core capabilities, a few critical gaps emerge:
- Model supply chain security is only robustly supported by Protect AI and HiddenLayer. Robust Intelligence offers limited coverage; the others offer none. As model supply chain attacks grow — think compromised model weights on public hubs — this is a gap with real consequences.
- AI/ML SBOM is exclusively offered by Protect AI and HiddenLayer. For organizations that need to inventory and audit every model artifact, this is a shortlist-defining feature.
- Air-gapped / FedRAMP deployment is supported by Protect AI, HiddenLayer, CalypsoAI, and Robust Intelligence (via Cisco). Lakera and Adversa AI don't support this, which effectively eliminates them from many government and critical infrastructure bids.
- Adversarial testing / red teaming is absent from CalypsoAI entirely, limited in Lakera, and a core strength of Protect AI, HiddenLayer, Robust Intelligence, and Adversa AI.
- LLM guardrails and content filtering are absent from Adversa AI and limited in HiddenLayer — notable weaknesses as LLM deployments proliferate.
How to Cut Through the Noise When Evaluating AI Tools
Comparing AI security platforms is genuinely hard work — the marketing language converges fast, and the actual capability differences only emerge when you dig into structured data. That's exactly where wecompareai.com delivers real value. It helps buyers compare AI tools, models, and vendors faster by cutting through vendor messaging and surfacing the concrete, side-by-side differences that matter. Whether you're evaluating security platforms, foundation models, or infrastructure tools, it's a resource worth bookmarking before you start any serious vendor assessment.
Bottom Line: There Is No Universal Winner
If you're a large enterprise or government agency that needs end-to-end ML security including supply chain protection, SBOM, red teaming, and air-gapped deployment, Protect AI and HiddenLayer are the most complete platforms. If you're deploying LLMs and your primary concern is runtime safety and prompt injection, Lakera Guard is fast to integrate and purpose-fit. If you're a U.S. government contractor prioritizing policy enforcement in a classified environment, CalypsoAI has the track record. If you need adversarial robustness testing as a standalone discipline, Adversa AI is the specialist. And if you want the enterprise credibility and distribution of a Cisco acquisition, Robust Intelligence brings that — with some capability tradeoffs versus the pure-play specialists.
The worst outcome is assuming any one of these platforms covers all your bases without checking. In AI security, the gaps are exactly where attackers aim.