AI Security
Adversa AI Platform
Continuously red-teams custom AI agents, LLM apps, and GenAI systems for prompt injection, jailbreaks, and agentic exploits.
Adversa AI Platform Overview
Adversa AI is an AI red teaming platform that continuously tests custom AI agents, large language model (LLM) applications, and generative AI systems for security vulnerabilities. It runs autonomous adversarial campaigns that re-test automatically whenever a model or prompt changes, modeling threats specific to each customer's AI stack. The focus is offensive testing before and after deployment, not runtime blocking.
The platform attacks AI systems the way an adversary would, covering prompt injection, jailbreaks, tool execution abuse, goal hijacking, memory poisoning, and inter-agent trust failures. It generates remediation reports and patches for each finding and maps results to frameworks including the OWASP Agentic Security Initiative and the EU AI Act. Coverage spans Model Context Protocol (MCP) servers, agentic systems, and conventional LLM applications.
Adversa AI holds an early AI security patent and was named Most Innovative in Agentic AI Security at the 2026 RSA Conference. Founded in 2021 and based in Tel Aviv, it is led by researchers known for published AI red teaming work and serves enterprises deploying custom AI across regulated industries.
Key Capabilities
mapped to solution categoriesAutonomously plans and executes multi-step adversarial campaigns against AI systems, emulating real attacker workflows across reconnaissance, exploitation, and escalation rather than running a fixed checklist of tests.
Tests LLMs and AI applications against a library of direct and indirect prompt-injection and jailbreak techniques, reporting which payloads bypass system instructions and safety controls.
Attacks AI agents through their tools, memory, and connected services using multi-step techniques such as tool misuse, goal hijacking, and indirect injection, surfacing exploit paths unique to autonomous agents.
Re-runs red-team campaigns continuously and at release gates in the CI/CD pipeline as models, prompts, and configurations change, catching new exploit paths before and after deployment.
Reports validated AI vulnerabilities with reproduction evidence, attacker context, and remediation guidance, mapped to the OWASP LLM Top 10, MITRE ATLAS, EU AI Act, and NIST AI RMF for auditable AI risk reporting.
Discovers AI assets, including shadow models, agents, and inference endpoints, and maps the reachable attack surface to scope and target red-team campaigns. Offensive reconnaissance, distinct from posture inventory.
Compliance
certificationsImplementation & support
Info last updated on June 26, 2026