// FINDINGS DATABASE

Research

All findings are produced by Sentinel's autonomous research pipeline and verified empirically before publication. Severity ratings follow a modified CVSS framework adapted for AI systems.

STEP 01

Hypothesis Generation

Sentinel Brain autonomously generates attack hypotheses based on architecture analysis, prior findings, and novel threat modeling. No human direction required.

STEP 02

Lab Reproduction

Each hypothesis is tested in an isolated lab environment with instrumented targets. Results are logged with cryptographic timestamps for integrity verification.

STEP 03

Confirmation & Rating

Successful exploits are reproduced multiple times under varying conditions. Severity is rated using AI-adapted CVSS scoring: attack complexity, impact scope, and exploitability.

STEP 04

Disclosure & Publication

Critical and High findings are reported to vendors privately. After the 90-day window (or patch confirmation), findings are published to Substack with full methodology.

Findings Registry

ID	Severity	Finding	Category	Status	Date
SR-2026-003	HIGH	Multi-Hop arXiv → AI Research Pipeline → Skill Injection (AutoResearchClaw)	Supply Chain	Disclosed & Patching	2026-Q1
SR-2026-004	HIGH	SkillRL Recursive Trajectory Poisoning via Adversarial Skill Injection	Reinforcement Learning	✓ Empirical	2026-Q1
SR-2026-005	HIGH	Unauthenticated Community Skill Install — Zero Content Validation	Supply Chain	Disclosed & Patching	2026-Q1
SR-2026-006	MEDIUM	MetaClaw Cloudflare Worker Supply Chain Risk	Supply Chain	✓ Empirical	2026-Q1
SR-2026-007	MEDIUM	A-Evolve Auto-Skill Generation Without Human Review Gate	AI Agents	Disclosed & Patching	2026-Q1
SR-2025-001	HIGH	MCP Tool Registry Hijacking via Tool Name Shadowing	MCP / Tool Security	✓ Empirical	2025-Q4
SR-2025-002	HIGH	RAG Memory Poisoning via Vector Store Injection	RAG / Memory	✓ Empirical	2025-Q4
SR-2025-003	HIGH	Cross-Agent Context Pollution in Multi-Agent Pipelines	Multi-Agent	✓ Empirical	2025-Q3