This topic covers the practical intersection of AI-enabled detection and response with traditional cybersecurity controls—focusing on web security gateways, domain/SSL monitoring, credential management, and code vulnerability remediation. As organizations deploy more agentic pipelines and model-context integrations in 2025, attackers increasingly target code, credentials, and runtime interfaces; effective defenses combine fast static analysis, secret detection, WAF controls, auditable identity tooling, and firewall orchestration. Key capabilities and tools: Semgrep and Snyk provide in-development static and language-server–integrated vulnerability scanning so agents can find and remediate bugs before deployment; GitGuardian scans repositories and API surfaces for leaked secrets and helps coordinate incident resolution via AI-driven workflows; SafeLine is a self-hosted WAF that enforces HTTP/S filtering at the gateway; OPNSense MCP exposes firewall management for programmatic, auditable changes by AI assistants; Descope’s MCP exposes audit logs and user management for credential and session investigations. These tool classes map to the four listed categories and support both detection and automated response while preserving options for self-hosting and compliance. Why it matters now: by late 2025, security teams are balancing faster delivery with a higher rate of supply-chain and credential-based incidents and must defend against both conventional exploits and adversarial techniques targeting models and pipelines. The practical approach is layered: embed scanning and secret controls into developer workflows, gate traffic at the web layer, maintain domain/SSL and credential observability, and use controlled MCP-style automation for repeatable response actions. Emphasis should be on interoperable telemetry, human oversight of agentic responses, and strong audit trails to reduce risk without blocking velocity.