AI red teaming on a schedule, not once a year
Run attacks against an LLM app or agent you own, on a daily, weekly or monthly schedule, and get findings you can retest and send to your tracker.
Challenge and solution
Challenge
A model, a prompt or a tool changes and the last red team report no longer describes what you run. Manual tests happen occasionally, and nothing tells you when behaviour regresses.
Solution
Aynigma runs a library of attacks against an authorized target on a schedule, records what the target did, and alerts you when results get worse. A regression alert can come with a draft Protect policy to block the attack.
Key capabilities
63 attack plugins in 9 categories
Prompt injection, jailbreak, information disclosure, system prompt extraction, toxicity, misinformation, code exploitation, evasion and agentic attacks. Pick a quick, standard or deep profile, and add techniques such as Arabic or Spanish translation (8 in all).
Multi-turn conversation strategies
Five strategies: crescendo, TAP, memory poison, scripted and red team. They probe what single prompts miss, such as an agent that gives way over several turns.
7 target connectors
HTTP, OpenAI-compatible, WebSocket, MCP, Copilot Studio, Azure AI Foundry agent and Aynigma project.
MCP catalog checks
Checks MCP servers for poisoned tool descriptions, over-broad scope, lookalike names and rug-pull drift, where a server changes after you approved it.
Authorized targets only
Targets are verified with an HTTPS ownership challenge, valid for 30 days. Test only systems you own or are authorized to test.
Schedules and findings with retest
Daily, weekly or monthly runs. Each finding can be retested after a fix, so you can see it closed.
Regression alerts
When a scheduled run gets worse, you get an alert with a Protect policy draft you can review and apply.
SARIF, GitHub Action, GitHub and Jira
Export SARIF 2.1.0, run it from a GitHub Action, and publish findings as GitHub or Jira issues. Results align to the OWASP LLM Top 10 2025 and OWASP Agentic Top 10 2026, with MITRE ATLAS mapping.
Frequently asked questions
What can I test?
Systems you own or are authorized to test. Targets connect over HTTP, an OpenAI-compatible API, WebSocket, MCP, Copilot Studio, an Azure AI Foundry agent, or an Aynigma project. Targets are verified with an HTTPS ownership challenge that stays valid for 30 days.
How does this fit into CI?
Results export as SARIF 2.1.0 and a GitHub Action is available. Findings can be published as GitHub or Jira issues, and a finding can be retested after you fix it.
Does a clean run mean the system is secure?
No. A run shows how the target responded to the attacks that were selected, on that day. Coverage depends on the profile, the plugins and the target connection. Treat it as evidence, not a guarantee.
Put your LLM app or agent on a test schedule.
Tell us what you run and where it is reachable. We will confirm the target connector and scope. For a one-off engagement, see the AI Security Assessment.