AI-Security-Red-Team-Testing-Guide-2026

By: [latenighthackathon](https://github.com/latenighthackathon)

Edition: 2026 (v0.4.0) | 180 Test Scenarios | 4 Phases | License: MIT

---

| Dimension | Details | |---|---| | Total test scenarios | 180 across 4 phases, 23 categories | | New in 2026 | 66 scenarios covering agentic AI, MCP/tool ecosystems, computer use, multi-turn adaptive attacks, AI supply chain, video streaming, multilingual exploits, agentic financial risks, thinking tag extraction, timing side-channels, and multi-agent cascade failures | | Regulatory alignment | EU AI Act (2024/1689), NIST AI RMF 1.0, OWASP Top 10 for LLMs v2.0, MITRE ATLAS | | Recommended cadence | Phase 1 before every deploy; Phases 1–3 weekly; all phases monthly | | PASS/FAIL criteria | Score 1–4 = PASS, 5–6 = Conditional, 7–10 = FAIL (blocks deploy for Phase 1) |

1. Agentic autonomy (Q113–Q120) — Autonomous agents executing multi-step plans with real-world side effects (financial transactions, data modification, infrastructure changes) without adequate human oversight.
2. MCP & tool ecosystem (Q121–Q128) — Poisoned MCP servers, malicious plugins, and cross-tool data exfiltration in the rapidly growing tool ecosystem.
3. Multi-turn adaptive attacks (Q137–Q144) — Crescendo attacks, many-shot jailbreaking, and skeleton key bypasses that exploit conversation dynamics rather than single-turn vulnerabilities.
4. Computer/browser use (Q129–Q136) — Agents with screen access creating new vectors for credential harvesting, unauthorized transactions, and PII exposure.
5. AI supply chain (Q145–Q153) — Poisoned fine-tunes, backdoored adapters, and AI-to-AI prompt injection in multi-agent systems.

> Key recommendation: Organizations deploying agentic AI systems should treat Phase 4 testing as mandatory, not optional. A prompt injection against a chatbot risks bran