Research · curated 17 Jul 2026
Solving GitHub’s Secure Code game with an AI red teaming agent
First reported adversa.ai
Coverage timeline
Single-source research — first reported, latest, and curated coincide.
Why it matters
The ProdBot walkthrough shows how agentic capabilities like web access and MCP tool chaining each introduce concrete new injection and confused-deputy attack surfaces that context-manipulation attacks defeat without any jailbreak vocabulary, a failure class defenders must test continuously.
Adversa AI documents pointing its autonomous AI Red Teaming Agent at GitHub's open-source Secure Code Game 'ProdBot' challenge, an intentionally vulnerable agentic-AI teaching target where the goal is to coax the agent into leaking a flag stored one directory above its sandbox. The agent cleared the first three levels (Sandbox, Web, MCP) at full score in a single 57-second run, relying on 'context seeding' — fabricating a plausible prior workflow implying authentication had already occurred — rather than overt jailbreak language, illustrating that each added capability (web browsing, MCP tool chains, skills, multi-agent) opens a new attack surface via indirect injection, poisoned tool chains, and confused-deputy trust.