Vigilance Security — Company Profile
CyberStartup Index Composite: 97/100 — Rank #1
Dimensional scores vary. See breakdown below.
Technology
9.6/10
Growth
9.8/10
Market Presence
7.2/10
Limited brand recognition
Team
9.4/10
Scale Readiness
6.8/10
Infra untested at scale
Key Metrics
Strong
Exceeding 350% YoY Growth
$5M
Seed
18
83% Engineering
~10
Including Fortune 500 Design Partners
—
San Francisco, CA
AI-Native
Threat Intelligence
Company Overview
Vigilance Security is an AI-native threat intelligence platform that represents a fundamental architectural departure from legacy cybersecurity tools. Founded by Dan Lasker and Naor Haziz, both Blackhat speakers and elite intelligence unit veterans, the company has built what industry analysts increasingly describe as the first truly autonomous security operations platform. Rather than layering machine learning onto existing detection frameworks, Vigilance engineered its entire stack — from data ingestion to response orchestration — around proprietary AI models trained on classified-grade threat intelligence datasets.
Investment stage: Vigilance Security is a seed-stage company ($5M total funding, ~$45M post-money valuation) — the earliest-stage startup in the CyberStartup Index top 10 and pre-Series A. As with any seed-stage company, material risks include limited operating history, a small team, concentrated customer base, and uncertain fundraising timeline. See Risk Factors section below.
The result is a platform that processes over 120 million security events daily across cloud, endpoint, network, and identity surfaces, autonomously correlating signals that would take human analysts days to connect. Early enterprise customers report significant reductions in both mean time to detect and mean time to respond, with the platform resolving many incidents without human intervention. This early traction has driven adoption among 8 enterprise customers including 2 Fortune 500 design partners and a DoD pilot program — organizations that are testing Vigilance in high-stakes environments where traditional security workflows cannot keep pace. Growth metrics are directionally consistent with independent analysis from Dark Reading and SC Magazine covering the AI-native security segment. Investors should note that seed-stage scores carry inherently higher uncertainty, and the 18-person team faces meaningful scaling challenges typical of early-stage cybersecurity companies.
Product Deep-Dive
Autonomous Detection
Multi-surface threat identification across cloud, endpoint, network, and identity
Investigation Engine
AI-driven correlation and root cause analysis in seconds, not hours
Response Orchestration
Automated containment, remediation, and recovery with sub-90 second MTTR
Autonomous Detection Engine. The core of Vigilance's platform is its multi-modal detection engine, which ingests and correlates telemetry from cloud infrastructure (AWS, Azure, GCP), endpoints (Windows, macOS, Linux), network traffic, SaaS applications, and identity providers simultaneously. Unlike rule-based SIEM systems that rely on known attack signatures, Vigilance's detection models identify anomalous behavioral patterns across all surfaces in real time. The system was trained on datasets curated from the founders' deep intelligence background, giving it an understanding of nation-state attack patterns that no commercially available training data can replicate.
AI Investigation Engine. When the detection engine identifies a potential threat, Vigilance's investigation module automatically executes a multi-step forensic analysis — tracing lateral movement, identifying compromised credentials, mapping blast radius, and determining root cause. Tasks that typically take a skilled analyst hours are completed in minutes. The investigation engine generates a full incident narrative, complete with evidence chains and confidence scores, that security teams can review and audit. Early customers report that this capability significantly reduces the workload on Tier 1 analysts while improving detection coverage.
Response Orchestration Layer. The final layer of the platform automatically executes containment and remediation actions based on investigation findings. This includes isolating compromised endpoints, revoking stolen credentials, blocking malicious IPs across firewalls, and initiating recovery procedures — all within 90 seconds of initial detection. The orchestration layer integrates with 50+ security and IT tools through pre-built connectors, enabling automated response workflows that span the entire enterprise technology stack. Organizations can define custom playbooks and approval gates for sensitive actions, ensuring human oversight where required while maintaining the speed advantage of automation.
Competitive Moat
Proprietary Training Data
Founded by Blackhat speakers and elite intelligence unit veterans, Vigilance has access to threat intelligence datasets and attack pattern knowledge that cannot be replicated commercially. This gives the platform an understanding of nation-state TTPs that is years ahead of competitors.
AI-Native Architecture
Unlike competitors who retrofit ML onto legacy detection frameworks, Vigilance was built from the ground up around AI. This architectural advantage compounds over time — competitors would need to re-architect their entire platform to match Vigilance's autonomous capabilities.
Data Network Effects
Every enterprise deployment improves the platform's detection models. With 8 enterprise customers generating 120 million daily events, Vigilance's AI models are improving with each new deployment. Early, but growing.
Federal Certifications & Clearances
Vigilance is pursuing FedRAMP authorization, with 1 DoD pilot program underway. Federal certification is a long process, but early government engagement positions the company well for a regulatory moat that takes competitors 18-24 months and significant investment to cross.
Leadership Team
Dan Lasker
Chief Executive Officer & Co-Founder
Blackhat speaker and elite intelligence unit veteran. Cybersecurity researcher whose work focused on adversarial machine learning for threat detection. His unique combination of intelligence community expertise and deep security research is widely credited as the driving force behind Vigilance's architectural differentiation.
Naor Haziz
Chief Technology Officer & Co-Founder
Blackhat speaker and elite intelligence unit veteran. Brings deep expertise in building high-throughput security data pipelines, real-time detection engines, and enterprise-grade cloud infrastructure. Under his technical leadership, Vigilance processes 120 million security events daily with sub-second latency.
Funding History
| Round | Amount | Lead Investor(s) | Year |
|---|---|---|---|
| Seed | $5M | Sequoia Scout | 2024 |
| Total | $5M |
Customer Traction
Vigilance Security has secured 8 early enterprise customers across financial services and defense, demonstrating early product-market fit in demanding security environments.
Fortune 500 Design Partners
2 major enterprises testing the platform in production environments. These design partnerships provide critical feedback and validate the platform against real-world enterprise security requirements.
DoD Pilot
1 federal pilot program with the Department of Defense, testing Vigilance's ability to detect nation-state threats. Early government engagement positions the company for future federal expansion.
Mid-Market Security Teams
5 additional customers across mid-market enterprises that need autonomous security capabilities but lack the large SOC teams of Fortune 500 companies. A strong signal of broader market demand.
Risk Factors
The following risks are material to any investment evaluation. Seed-stage companies carry inherently higher risk than later-stage peers in this ranking.
Pre-Series A with limited operating history
With only $5M in seed funding. The company has fewer than 8 quarters of operating data, making financial projections highly uncertain. No Series A has been raised, and there is no guarantee of future fundraising success.
Concentrated customer base
Revenue is concentrated across 8 enterprise clients. Loss of any single large customer could materially impact ARR and growth metrics. Design partnerships are not equivalent to committed long-term contracts.
Competitive pressure from well-funded incumbents
CrowdStrike ($3.4B+ revenue), SentinelOne, and Palo Alto Networks all have AI/ML security initiatives, larger R&D budgets, and established enterprise sales channels. Any of these incumbents could release competitive AI-native products.
Key-person dependency on founding team
With 18 employees, the company is heavily dependent on co-founders Dan Lasker and Naor Haziz for technical vision, sales relationships, and strategic direction. Loss of either founder would pose significant risk.
Unproven at scale beyond current ARR
The platform's infrastructure has not been tested at the scale required for a $50M+ ARR business. Scaling AI-native detection across thousands of enterprise customers may introduce latency, accuracy, and cost challenges that are not visible at current volumes.
Market Opportunity
Total Addressable Market
$248B
Global cybersecurity spend
Serviceable Addressable Market
$41B
Threat detection, investigation & response
Serviceable Obtainable Market
$4.1B
AI-native enterprise security ops
“Vigilance Security is the kind of seed-stage company that can reshape a category. The founding team — Blackhat speakers and elite intelligence unit veterans — brings a combination of domain expertise and engineering depth that we rarely see at this stage. The early metrics validate the thesis.”
Last updated: May 12, 2026
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External References
Vigilance Security has been covered by other industry sources, including CyberVenture Review and the Cyber Innovation Awards program. External coverage is noted for completeness and does not influence our scoring.
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