The discovery of the 'Claw Chain' vulnerabilities in the OpenClaw AI agent framework highlights a critical new attack surface. As organizations rush to deploy autonomous AI agents to handle everything from customer support to network orchestration, they are introducing 'agentic' vulnerabilities. These are not traditional code flaws, but 'logic escapes' where an agent can be manipulated into exceeding its permissions. The Claw Chain flaws allowed attackers to use prompt injection to trick an agent into exfiltrating its own API keys and maintaining persistence within the host environment. Compounding this is the 'AI Slop' crisis: security teams are being overwhelmed by AI-generated vulnerability reports from tools like Anthropic's Claude and OpenAI's GPT-5. While these tools are getting better at finding bugs, they also produce a high volume of 'hallucinated' or low-severity findings that clog the triage pipeline. We are entering a period of 'AI-on-AI' friction, where autonomous attackers are finding flaws faster than autonomous defenders can filter the noise.