AI Red Teaming
Simulate attacks against AI systems to identify weaknesses before attackers do.
Red teaming is the discipline of attacking your own AI system before someone else does. SkyMind runs structured red team engagements: threat modeling, attack tree construction, automated and manual probing of prompts, retrieval, agents, and integrations, and clear documentation of every finding with reproduction steps and severity. We test for prompt injection, jailbreaks, sensitive disclosure, RAG poisoning, unauthorized retrieval, excessive permissions, tool abuse, and insecure integrations.
Structured adversarial simulation against AI systems to find exploitable weaknesses before real attackers do.
What this engagement covers
Each capability is a scoped workstream with defined deliverables and acceptance criteria.
Threat modeling
Map adversaries, motivations, and attack paths specific to your AI system and its data.
Adversarial prompt testing
Manual and automated prompt injection, jailbreak, and bypass attempts.
Retrieval & poisoning tests
Test whether attackers can poison retrieval or extract unauthorized information.
Agent & integration probing
Probe agents for permission escalation, tool abuse, and integration weaknesses.
What you walk away with
Tangible artifacts your team owns and operates — not a deck and a handshake.
Red team report
Every finding with reproduction steps, evidence, severity, and remediation guidance.
Attack tree documentation
Documented attack paths and adversarial models for your system.
Prioritized remediation plan
Concrete, ranked fixes for engineering and product teams.
What changes after this engagement
Find exploitable weaknesses before attackers do
Evidence-based prioritization for security investment
A repeatable methodology your team can run again
Frequently combined with
Common questions about Red Teaming
Start AI Red Teaming
Tell us about your problem. We'll scope a path that fits your stack, timeline, and risk posture.