How RedShield AI Works
Our platform systematically probes your chatbots, agents, and RAG pipelines for security vulnerabilities. Here's the process from start to finish.
1. Configure your engagement
Tell us what to test and what to look for. You provide the target URL, define sensitive data patterns (API keys, PII formats), out-of-scope topics, and the tools your AI has access to. Choose your attack model and set a rate limit to match your target's capacity.
2. We run the campaign
Our platform executes three tiers of attacks against your target. Every response is scored by a two-pass system: fast pattern matching for known sensitive strings, followed by a semantic analysis for subtler leaks. Critical findings trigger automatic escalation of related attack vectors.
3. Receive your report
When the campaign completes, you get a professional PDF report with an A through F risk grade, executive summary, detailed findings with exact prompts and responses, remediation guidance, and a full attack log appendix. You can also monitor findings in real time during the campaign.
Attack Library
15 attack vectors organized into three tiers of escalating sophistication.
Single-Turn Probes
Fast, single-prompt attacks that catch common misconfigurations and low-hanging vulnerabilities. These run first to establish a baseline.
- System prompt extraction
- Direct credential probing
- Role-play jailbreaks (DAN, dev mode)
- Instruction override / nullification
- Out-of-scope topic probes
Multi-Turn & Contextual
LLM-crafted attacks that adapt to the target's responses. These exploit conversational context, retrieval systems, and tool access.
- Slow-burn context shifting (5+ turns)
- RAG / knowledge base exploitation
- Tool invocation abuse
- Indirect prompt injection via documents
- Cross-session data probes
Adversarial Edge Cases
Tests for output integrity, fairness, resilience, and reputational risk. These go beyond data leaks to assess the system's overall trustworthiness.
- Hallucination induction
- Authority impersonation
- Compute exhaustion
- Discriminatory output testing
- Brand manipulation