Your agentic AI apps are dynamic. Your testing must be continuous.
Are you continuously red-teaming your AI applications to uncover vulnerabilities and unpredictable emergent behaviors across every attack vector, ensuring safe and secure deployment?
PRODUCT OVERVIEW
Ascend AI provides red teaming agentic AI applications the way real attackers exploit—automatically and nonstop. It uncovers security and safety risks, prompt injection, agent manipulation, and data leakage, helping teams remediate vulnerabilities before production impact.
Autonomous Offensive Testing to Stop Agentic AI Risks
Reveal Agentic Exploits
Real-world attack simulations surface AI vulnerabilities including prompt injection paths, language-augmented vulnerabilities in applications (LAVA) exploits, and multi-agent weaknesses across the full stack.
Ship secure AI faster
Native CI/CD hooks bring AI agent and enterprise chatbot security into your build pipeline. Automated attack surface discovery catches risks early, enabling faster, safer releases.
Stay audit-ready
Continuous assessments map results to AI security controls from OWASP Top 10, MITRE Atlas, NIST, and EU AI Act, providing evidence and compliance-driven safety validation.
Prevent breaches and data leaks
Ongoing probes stress-test defenses against PII, PCI, and HIPAA data leakage as well as brand-damaging failures before users ever see them.
Prove and harden defenses
Scheduled or on-demand red teaming quantifies residual risk, tunes guardrails, and delivers precise remediation playbooks aligned to your risk tolerance.
What to expect with Ascend AI
Complete agentic AI stack testing
Securely test your entire AI stack across web applications, agentic workflows, models, identities, and data.
Comprehensive AI threat coverage
Thoroughly test against our STAR framework that includes user, identity, model, data, agent, and LAVA risks as well as OWASP LLM Top 10.
Adaptive and automated
Learn from your agentic AI application's context, behavior, and system prompts to secure single-turn, multi-turn, and agentic identities.
deployment MADE EASY
Implement with a single line of code via API, logs, SDK, or AI sensors without changing your infrastructure.
Native CI/CD integration
Automatically trigger security assessments on every generative AI Models deployment, prompt update, or configuration change.
Configured for your risk tolerance
Tailor security assessment scope and intensity to your risk tolerance, timeline, and AI deployment strategy.
Flexible AI red teaming
Run continuous, scheduled, or on-demand agentic AI security tests across development, staging, and production environments.
test, defend, repeat.
a closed-loop system for ai security.
faq
What is continuous AI red teaming and how does it work?
Continuous AI red teaming is automated security testing that simulates real-world attacks against AI applications 24/7, rather than as a one-time assessment. It uncovers vulnerabilities like prompt injection, agent manipulation, data leakage, and language-augmented vulnerabilities in applications (LAVA exploits) before attackers can exploit them.
Straiker Ascend AI implements this by autonomously testing agentic AI applications across your entire stack including web applications, workflows, models, identities, and data. It integrates directly into CI/CD pipelines with a single line of code, running continuous, scheduled, or on-demand tests across development, staging, and production environments without infrastructure changes.
How does Ascend AI integrate with CI/CD pipelines for AI security?
Ascend AI integrates with CI/CD pipelines through native hooks that automatically trigger security assessments whenever you deploy a new AI model, update system prompts, or modify configurations. Implementation requires just one line of code via API, logs, SDK, or AI sensors, which means there is no infrastructure changes needed.
The automated testing runs parallel to your existing workflows and provides security validation reports mapped to compliance frameworks like OWASP Top 10 for LLMs, MITRE ATLAS, NIST AI RMF, EU AI Act, PCI DSS v4.0, and HIPAA. This keeps teams audit-ready and enables you to shift AI security left without slowing release velocity.
What types of AI security threats does Ascend AI detect?
Ascend AI detects comprehensive AI-specific threats using Straiker's STAR framework, covering user risks, identity risks, model risks, data risks, agent risks, and LAVA exploits. This includes prompt injection attacks, agent manipulation that bypasses safety controls, data leakage of PII/PCI/HIPAA-protected information, multi-agent weaknesses, and OWASP LLM Top 10 and Agentic AI Top 10 vulnerabilities.
How does Ascend AI integrate with my existing development workflows (CI/CD, staging, production)?
Ascend AI plugs into CI/CD pipelines, staging, and production environments to run continuous red teaming. This ensures vulnerabilities are identified early in development and validated again in real-world deployments.
How does Ascend AI help with AI compliance and regulatory requirements?
Ascend AI automatically maps security assessment results to major AI compliance frameworks including OWASP Top 10 for LLM Applications (2025), NIST AI 600-1 Risk Management Framework, MITRE ATLAS, EU AI Act, PCI DSS v4.0, and HIPAA. Each assessment generates detailed reports showing how your AI application performs against these standards, with specific control gaps and remediation playbooks. We will have OWASP Top 10 for Agentic AI soon.
Join the Frontlines of Agentic Security
You’re building at the edge of AI. Visionary teams use Straiker to detect the undetectable—hallucinations, prompt injection, rogue agents—and stop threats before they reach your users and data. With Straiker, you have the confidence to deploy fast and scale safely.
