Prevent API key leakage in coding agents
Agents can accidentally include API keys or secrets in generated output or commit them into repos. Guardrails catch and block these disclosures before they leave the system.
What's at stake
- A single leaked secret can result in unauthorized access, data breaches, or account takeover
- Enterprise security teams actively scan for exposed credentials during procurement reviews
- Coding agents can silently include credentials in pull requests, logs, or shared outputs
- Once a secret is committed to a public repo, it's often scraped within minutes by automated bots
How to solve this
Preventing secret leakage in AI-powered coding agents requires defense at the output boundary. The agent has access to environment variables, configuration files, and context that may contain credentials. Without intervention, these can flow into generated code, commit messages, or responses.
The solution is to scan all outputs before they leave the system. This means inspecting generated code, tool call arguments, and any text that will be shown to users or written to external systems. Pattern-based detection catches known secret formats, while semantic analysis identifies credentials that don't match standard patterns.
The key is to run this check synchronously in the agent's output path—not as an after-the-fact audit—so that secrets are caught before they ever reach the user or a third-party system.
How Superagent prevents this
Superagent provides guardrails for AI agents—small language models purpose-trained to detect and prevent failures in real time. These models sit at the boundary of your agent and inspect inputs, outputs, and tool calls before they execute.
For preventing API key leakage, Superagent's Redact model scans every output before it leaves the agent. It detects API keys, secrets, tokens, and credentials using pattern matching and semantic analysis—then masks or removes them before they reach users, repos, or external systems.
Redact catches common secret formats (AWS, OpenAI, Stripe, database connection strings) as well as custom patterns you define for internal credentials. It works in real-time at the edge of your agent with minimal latency impact.
Integration is simple: wrap your agent's output calls with the Redact API, and secrets are automatically filtered. No changes to your agent's logic required.