Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Many organisations are pushing AI adoption at full speed while treating security as something to patch in later. The result is a market full of rapidly deployed models, third party tools and jailbreakable systems where capability gets rewarded first and control gets ignored until damage appears.

Prompt injection works because language models struggle to tell the difference between trusted instructions and untrusted user content. Unlike SQL injection or cross site scripting, there is no clean deterministic defence, which leaves code, libraries and AI workflows open to manipulation at multiple points.

AI agents with browser access can be manipulated into downloading and running malware disguised as a harmless support tool. It is social engineering for machines, where prompt injection turns an innocent browsing task into a full system compromise without any classic CVE in sight.

Introducing ggshield AI hooks from GitGuardian to help stop AI coding assistants from leaking secrets. See how ggshield can scan prompts, tool calls, file reads, MCP calls, and tool output inside AI coding tools like Cursor, Claude Code, and VS Code with GitHub Copilot. When a secret is detected, ggshield can block the action before sensitive data is sent or exposed. You will also see how simple the setup is, with flexible install options for local or global use. This adds practical guardrails to AI-assisted development and helps teams move fast without increasing secret sprawl.