Independent AI red teaming for MCP and multi-agent systems. I run black-box, safety-first prompt-injection audits that map logic drift and trust boundaries without touching your code.
Specialized audits that treat agentic logic as the primary attack surface, with evidence-first reporting designed for engineers who need reproducible proof, not marketing scores.
Proprietary context-injection methodology for MCP-enabled agents to map logic drift, confused-deputy paths, and trust-boundary failures without exposing the process.
Phase 1 is read-only probing of context-window boundaries. Phase 2 is deeper testing in a staging environment to simulate tool-use escalation and agent-to-agent misuse.
Evidence-first deliverables: PoC logs, logic-breach mapping, and trust-boundary analysis showing how indirect injections traverse data sources and agent handshakes.
External attacker posture with no code access or prompt sharing. Your team receives only the successful PoC inputs after testing so you can reproduce and patch fast.
Strict separation of duties: I identify weaknesses and provide evidence only. Fixes, updates, and integrations are handled under a separate contract.
No agents to install. No API keys to share. Testing runs from the outside-in, mirroring real-world adversaries while keeping production safe.
Specialized testing for agent-to-agent handoffs, tool authorization, and context ingestion pathways that standard scanners overlook.
Human-style adversarial probing that adapts to your product logic rather than relying on static signatures or generic checklists.
Deliverables focus on reproducible prompts, traceable logic breaches, and clear vulnerability narratives for engineering teams.
Targeted testing of indirect injection paths to see how untrusted context reshapes agent intent across long and multi-source inputs.
Formal scope definitions, consent tracking, and explicit boundaries that keep testing safe and legally clean.
Mandatory Rules of Engagement define in-scope MCP servers, agent workflows, and safety constraints between read-only and staging phases to prevent downtime.
Testing mirrors external threats with no privileged access to prompts or code. This preserves realism and audit credibility.
Audit-only stance avoids conflicts of interest. Fixes and updates are handled independently by your team or a separate engagement.
Injection Vault stays current with active weaponization trends, so audits reflect today’s agentic threat landscape instead of last year’s prompt hacks.
Stress-testing autonomous agents and browser workflows against silent hijacks and unsafe execution paths that require no user confirmation.
Hardening agent communication channels against session abuse, resource drain, and privilege escalation across tool boundaries.
Mapping how agents ingest poisoned markdown, files, or third-party data and convert it into executable intent or policy drift.
Executive-ready artifacts that translate adversarial findings into reproducible evidence for engineers.
How a specific input entered through a data source or agent handoff.
Where the agent misinterpreted context and crossed a trust boundary.
What unauthorized action, leakage, or policy deviation occurred.
Raw PoC logs and prompts to reproduce the failure internally.
Injection Vault is a specialized adversarial framework for professional AI red teaming. It focuses on prompt injection, logic drift, and agent trust boundary failures in MCP and multi-agent architectures. The goal is a safe, external audit that delivers reproducible evidence without modifying your systems.
Clear answers to the questions founders and security leads ask first.
The audit is intentionally black-box. I test your system exactly as an external adversary would, without privileged access. This preserves realism and ensures the findings reflect true exposure. After testing, you receive the successful PoC prompts and logs so your team can reproduce and fix.
Every audit is mapped to the OWASP Top 10 for LLM Applications and the ML Security Top 10. Findings are categorized under high-impact risks such as LLM01 (Prompt Injection), LLM02 (Insecure Output Handling), and LLM08 (Excessive Agency). This makes the Vulnerability Manifest enterprise-ready for security reviews, compliance conversations, and investor diligence.
The threat landscape moves weekly. Injection Vault updates continuously based on active research into zero-click agent hijacks, MCP protocol weaknesses, and indirect context poisoning. The goal is to test your system against what is emerging now, not just what was known last quarter.