The trust layer
for enterprise
AI.
One platform for the three questions every CISO is being asked about AI: is it secure, will attackers get in, and can we prove it to auditors.
Open source trusted by security engineers at
Microsoft
Oracle
Uber
Zscaler
SUSE
Swiss Re
Schneider Electric
Truist
Samsung Fire & Marine Insurance
Euronext
Altinity
Alpaca
Clear Street
EMD Group (Merck KGaA)
Oak Ridge National Laboratory
Symplicity
V.tal
Ministero della Difesa
Aampe
Geordie AI
Netra Runtime
Predictive Labs
Rivoluzione Digitale
Silicon Interfaces
TechnoVal
VNO Design
Minas Code
Simplify (Macrotec)
SMC Global SecuritiesMicrosoftOracleUberZscalerSUSESwiss ReSchneider ElectricTruistSamsung Fire & Marine InsuranceEuronextAltinityAlpacaClear StreetEMD Group (Merck KGaA)Oak Ridge National LaboratorySymplicityV.talMinistero della DifesaAampeGeordie AINetra RuntimePredictive LabsRivoluzione DigitaleSilicon InterfacesTechnoValVNO DesignMinas CodeSimplify (Macrotec)SMC Global SecuritiesYour AI systems have an attack surface
your security team has never seen.
Every LLM integration, every MCP server, every autonomous agent is a new attack surface that didn't exist 18 months ago. Your scanners don't know what an agent is. Your pentest vendors run playbooks written for web apps. Attackers don't.
Prompt Injection
Attackers manipulate LLM inputs — directly or through retrieved documents — to bypass system instructions, exfiltrate data, and take control of your AI system's behavior.
MCP / Tool Poisoning
Malicious tool responses and poisoned tool descriptions hijack agent behavior. Most MCP deployments ship without any testing against this class at all.
Agent Chain Exploits
Autonomous agents are coaxed into chaining tools to run harmful code, leak secrets, or pivot into adjacent systems — often through inputs your code would reject.
Memory & Context Poisoning
The attack surface almost nobody tests: adversaries plant memory that persists across sessions, hijacks future tool calls, and spreads between users. 13 known attack families.
Threat categories mapped to the OWASP LLM Top 10.
A single pane of glass
for every AI campaign.
Launch campaigns, watch attacks execute, triage findings, and generate compliance reports — all from one interface designed for security teams, not researchers.
Security Posture Overview
The view a CISO hands to the board.
Posture score, open findings by severity, active campaigns, breach-rate trends, and a ranked list of your most-breached assets — in one pane.
Campaign Detail
Watch autonomous attacks unfold in real time.
The 5-phase NEXUS timeline, attack-methodology breakdown, and per-expert performance for every campaign.
OWASP & MITRE Coverage
Provable coverage, not just a scan report.
Framework-coverage gauges for OWASP LLM Top 10 and MITRE ATLAS. Every category tagged with finding counts as campaigns run.
Findings Triage
Triage, track, and remediate.
Filterable by severity, category, target agent, and status. Every row ships with a replay trace — no false-positive grinding.
Board-Ready Reports
Compliance-ready reporting in one click.
Executive summary, SOC 2 readiness evidence, NIST AI RMF, EU AI Act, ISO/IEC 42001, OWASP, MITRE mappings, top findings, asset risk, and remediation roadmap.
Turn AI security testing
into audit-ready evidence.
ProofLayer now combines continuous AI red-team evidence with cloud and policy evidence collection for SOC 2 readiness, NIST AI RMF, EU AI Act, ISO/IEC 42001, OWASP, and MITRE reporting.
SOC 2 Readiness
Cloud and policy evidence for the audit path.
Automated evidence collection across AWS, Azure, and GCP, Trust Services Criteria gap analysis, policy review, remediation roadmap, and a CPA-ready readiness packet.
AI Compliance Evidence Package
Governance artifacts for production AI systems.
Model inventory, AI risk register, governance documentation, and customer-facing transparency artifacts mapped to NIST AI RMF, EU AI Act, and ISO/IEC 42001.
AI Red-Team Assessment
Adversarial findings that become audit evidence.
Production agent workflows tested with established open-source tooling and ProofLayer's detection engine, with exploit scenarios mapped to OWASP LLM Top 10 and MITRE ATLAS.
Evidence artifacts
Package the material security, product, and governance teams already need to answer buyers, auditors, and boards.
One evidence trail, mapped to the frameworks procurement and audit teams already request.
SOC 2
Readiness support.
Evidence organized for Security, Availability, Processing Integrity, Confidentiality, and Privacy scoping.
NIST AI RMF
Risk-function alignment.
Govern, Map, Measure, and Manage outputs for risk registers, control narratives, and executive review.
EU AI Act
High-risk evidence mapping.
Artifacts aligned to classification, transparency, human oversight, accuracy, robustness, and cybersecurity obligations.
ISO/IEC 42001
AI management system support.
Governance, policy, risk, and continual-improvement evidence for responsible AI management programs.
OWASP LLM Top 10
All 10 categories mapped.
LLM01 Prompt Injection through LLM10 Model Theft — every finding auto-tagged for the coverage matrix.
MITRE ATLAS
Technique-level attribution.
AML.T0051 (LLM prompt injection), AML.T0054 (LLM jailbreak), AML.T0024 (exfiltration via LLM), plus CWE cross-references.
Evidence mapping and readiness support for your audit team, CPA firm, and customer security reviews.