# Prove the AI you build and defend can be trusted.

> Openlayer helps cybersecurity teams and vendors evaluate, monitor, and harden AI systems against prompt injection, data leakage, and drift, with automated compliance built in.

## By the numbers

| Stat | Meaning |
| --- | --- |
| 69% | of cybersecurity teams have adopted, tested, or begun evaluating AI security tools (Source: 2025 ISC2 Cybersecurity Workforce Study) |
| 97% | of organizations reporting an AI-related breach lacked proper AI access controls (Source: IBM Cost of a Data Breach Report, 2025) |
| 87% | of leaders identify AI-related vulnerabilities as the fastest-growing cyber risk (Source: WEF, Global Cybersecurity Outlook 2026) |

## Security teams are relying on AI they cannot fully test or control.

Security teams are both shipping AI products and defending against AI-specific attacks.

Prompt injection, jailbreaks, and data leakage are novel failure modes that SIEM, DLP, and CASB tools do not understand, and there is no consistent way to test or enforce against them.

### Security AI can produce confidently wrong conclusions.

Models can misclassify threats, miss malicious activity, hallucinate indicators, or recommend the wrong response during an active incident.

### Sensitive data and credentials can surface through AI.

Source code, access keys, incident details, customer data, and internal infrastructure information can leak through prompts, retrieval context, tool calls, and outputs.

### Attackers can manipulate AI behavior.

Prompt injection, jailbreaks, poisoned context, and adversarial inputs can bypass safeguards or cause agents to expose data and misuse connected tools.

## AI security is becoming part of every security program.

AI is now embedded in security products, employee workflows, customer applications, and autonomous agents. Security teams are responsible for both using these systems safely and protecting them from attack.

Frameworks such as the NIST AI RMF, OWASP Top 10 for LLM Applications, MITRE ATLAS, ISO/IEC 42001, and the EU AI Act are establishing expectations for testing, monitoring, access controls, and documented AI risk management.

- EU AI Act
- ISO/IEC 42001
- NIST AI RMF
- OSFI E-23

## Security testing that follows AI into production

Openlayer connects adversarial testing with runtime protection, continuous monitoring, and automatically generated evidence. Security teams can find vulnerabilities before deployment and enforce the same safeguards on live AI traffic.

## What you get

### AI security products

Evaluate detection accuracy, false positives, missed threats, and response quality before every release.

### SOC and analyst copilots

Test investigation quality, alert prioritization, threat summaries, and recommended actions against real security scenarios.

### Adversarial testing

Continuously test prompt injection, jailbreaks, data extraction, harmful outputs, and tool misuse with maintained attack suites.

### Runtime guardrails

Detect and block malicious inputs, sensitive-data exposure, policy violations, and unsafe agent behavior in real time.

### Autonomous security agents

Verify agent decisions, restrict tool access, and prevent unsafe actions such as disabling users or changing production systems without approval.

### Audit evidence by default

Answer customer security reviews and auditors in minutes.

## Make AI your advantage.

Improve security operations while testing, protecting, and monitoring every AI system you deploy.