Screener/Nightfall AI

Nightfall AI

AI-powered data loss prevention platform protecting sensitive data across SaaS, AI, and cloud environments.

HQ🇺🇸 US
Est2017
Size51-200
nightfall.ai
Score
52.0 / 100
Evidence
5 items
Confidence
medium

Strong safety posture with established governance frameworks and active risk management.

Strengths:Governance Maturity, Technical Safety, Regulatory Readiness, External Engagement
Weaknesses:Risk Assessment
Focus Areas
data loss preventiondlpgenai securitysensitive data detection
Table of Contents

Security Assessment

Security-relevant indicators for vendor evaluation

Security Posture
53
TS-01dim: 58
Red Teaming & Pre-deployment Testing
Adversarial testing before deployment
TS-05dim: 58
Robustness & Adversarial Resilience
Resistance to adversarial attacks
RA-01dim: 48
Sector-Specific Risk Assessment
Risk analysis for deployment context
RA-03dim: 48
Dual-Use & Misuse Risk
Dangerous capability awareness
RA-07dim: 48
Incident History & Track Record
Past incidents and response quality
EE-04dim: 54
Vulnerability Disclosure Program
Bug bounty or CVE reporting process
Incident History
Nightfall 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.
50
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.
48
RR
Regulatory Readinesspreliminary
ISO 42001, EU AI Act compliance, GPAI obligations, international commitments, incident reporting.
50
EE
External Engagementpreliminary
Survey participation, research support, transparency, behavior specs, open-source contributions.
54

Social Impact & Safety Profile

Moderate

Nightfall AI provides data loss prevention using machine learning to detect sensitive data (PII, secrets, credentials) across cloud services, AI tools, and communication platforms. Increasingly focused on preventing data leakage through GenAI tools like ChatGPT and Copilot.

data loss preventiongenai data protectionsensitive data detection

Peer Comparison

Securiti AI
B55

Data Security

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Harmonic Security
B-50

Data Security

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Confident Security
C+47

Robustness & Adversarial

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Enclave Markets
C42

Data Security

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Data Sources & Methodology

Scoring methodology v0.1 · 40 indicators · 6 frameworks

Last assessment: 2026-03-23 · Confidence: medium · Evidence: 5 items

NIST AI RMF · EU AI Act · ISO 42001 · FLI AI Safety Index · MLCommons AILuminate · METR

How is this company scored? →Full methodologyView in Screener

Scores reflect publicly available information. A low score may indicate limited transparency rather than poor safety practices.