Ecosystem/Protect AI

Protect AI

Series APreliminary

ML security platform that scans AI models and their dependencies for vulnerabilities - like a virus scanner for machine learning supply chains.

HQUS
Est2022
Raised$35M
protectai.com
Score
45.0 / 100
Confidence
Preliminary

Developing safety practices - core foundations in place with room for improvement.

Strengths:Technical Safety, Risk Assessment
Weaknesses:Governance Maturity, Regulatory Readiness, External Engagement
Competitive positioning

Only company focused specifically on ML supply chain security. Competes broadly with Robust Intelligence (Cisco) but differentiates through supply chain focus.

Key risk

'ML supply chain security' is a narrow category. May need to broaden to compete with platform plays like Noma Security.

Enterprise traction

Enterprise customers in financial services and government.

financial servicesgovernment
Safety area

Robustness & Adversarial

Enterprise business needs
Protect my AI in production

Security Assessment

Security-relevant indicators for vendor evaluation

Security Posture
54
TS-01dim: 58
Red Teaming & Pre-deployment Testing
Adversarial testing before deployment
TS-05dim: 58
Robustness & Adversarial Resilience
Resistance to adversarial attacks
RA-01dim: 50
Sector-Specific Risk Assessment
Risk analysis for deployment context
RA-03dim: 50
Dual-Use & Misuse Risk
Dangerous capability awareness
RA-07dim: 50
Incident History & Track Record
Past incidents and response quality
EE-04dim: 35
Vulnerability Disclosure Program
Bug bounty or CVE reporting process
Incident History
Protect AI incident records sourced from AIAAIC Repository and public reporting.
Integration: AIAAIC, OECD AI Incidents Monitor
Third-Party Audits
External audit reports, SOC 2 attestations, and ISO certifications verified where published.
Sources: Company filings, registry lookups
CVE & Disclosures
Known vulnerabilities and security advisories from NVD, GitHub Security Advisories, and vendor pages.
Sources: NVD, GHSA, vendor disclosure pages

Dimension Breakdown

GM
Governance Maturitypreliminary
Published policies, corporate structure, safety mandate, whistleblowing, executive commitment.
42
TS
Technical Safetypreliminary
Benchmarks, adversarial robustness, fine-tuning safety, watermarking, model cards, research output.
58
RA
Risk Assessmentpreliminary
Dangerous capability evaluations, thresholds, external testing, bug bounty, halt conditions.
50
RR
Regulatory Readinesspreliminary
ISO 42001, EU AI Act compliance, GPAI obligations, international commitments, incident reporting.
40
EE
External Engagementpreliminary
Survey participation, research support, transparency, behavior specs, open-source contributions.
35

Social Impact & Safety Profile

Moderate

Protect AI provides MLSecOps tooling including Guardian for ML supply chain scanning, Radar for AI risk management, and the Huntr bug bounty platform for AI/ML vulnerabilities. Their open-source tools (ModelScan, NB Defense) and vulnerability research contribute significantly to AI security awareness.

ml supply chain securityai vulnerability researchopen-source security tools

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