You already have security tools. Here's why they don't solve the AI agent credential problem.
Store secrets securely and retrieve them at runtime via SDK calls.
The AI agent still fetches and holds the real secret in memory - it can be leaked via prompt injection, logged in conversations, or exposed in debug output. Also requires code changes: SDK integration, URL changes, IAM policy configuration.
No SDK. No code changes. Transparent proxy at the network layer. Agent uses a placeholder like $STRIPE_KEY - Heimdall injects the real credential into the outgoing HTTP request. The agent never sees the actual secret.
| Cloud Vaults | Heimdall | |
|---|---|---|
| Agent sees the real secret | ✗ Yes | ✓ Never |
| Requires code changes | ✗ Yes (SDK, URLs, IAM) | ✓ No - drop-in proxy |
| Prevents prompt injection leaks | ✗ No | ✓ Yes |
| Works with any AI framework | ✗ Per-framework integration | ✓ Framework-agnostic |
| Setup time | ⚠ Hours to days | ✓ Minutes |
Scan code, repos, logs, and commits to find credentials that have already been exposed. Alert so you can rotate and remediate.
They're reactive - firefighters arriving after the fire started. They answer "did a secret leak?" not "how do I prevent it?" When an agent gets a secret in its context window, there's no commit to scan. The secret leaks through conversation logs, prompt injection, or LLM provider APIs.
Prevention, not detection. The secret never reaches the AI agent. There's nothing to scan for because the exposure never happens.
| Scanners | Heimdall | |
|---|---|---|
| When it acts | ✗ After the leak | ✓ Before the leak |
| Protects AI agent runtime | ✗ No - designed for repos | ✓ Yes |
| Covers prompt injection | ✗ No | ✓ Yes |
| Covers conversation log exposure | ✗ No | ✓ Yes |
| Requires remediation after detection | ✗ Yes | ✓ No - nothing leaked |
You should still use secret scanners as a safety net. Heimdall makes sure there's nothing for them to find.
Monitor LLM inputs and outputs in real time. Detect and redact sensitive data (PII, credentials) before it reaches the model.
They rely on pattern matching to catch secrets after they've been typed or injected into the prompt. If the pattern isn't recognized or the secret is obfuscated, it slips through. They also don't help with outbound API authentication - when the agent needs to call Stripe or AWS, guardrails can't authenticate for it.
Doesn't try to recognize secrets in text - removes them from the equation entirely. The secret is never in the prompt, never in the conversation. It's architecturally impossible for the agent to leak what it never had.
| Guardrails | Heimdall | |
|---|---|---|
| How it protects | ⚠ Filters text (pattern matching) | ✓ Removes secrets entirely |
| Can be bypassed | ✗ Yes - encoding, obfuscation | ✓ No - secret isn't there |
| Handles outbound API auth | ✗ No | ✓ Yes |
| False positives/negatives | ✗ Common | ✓ N/A - architectural prevention |
| Adds latency to LLM calls | ✗ Yes | ✓ No - network layer only |
Replace static API keys with workload identity and dynamic credential injection. Intercept HTTPS requests and inject short-lived tokens based on verified identity.
Aembit is the closest to what we do - solid approach. But they're built for enterprise workload IAM across all non-human identities (CI/CD, microservices, cloud workloads). AI agents are one use case among many. This means complex setup, enterprise sales cycles, and architecture designed for platform teams managing hundreds of identities.
Purpose-built for AI agent security. Lightweight, developer-first, designed to get running in minutes - not months.
| Aembit | Heimdall | |
|---|---|---|
| Primary focus | Enterprise workload IAM | ✓ AI agent credential security |
| Setup complexity | ⚠ Enterprise deployment | ✓ Minutes to integrate |
| Target buyer | IAM teams, platform eng | ✓ DevOps, AI engineers |
| Pricing | ⚠ Enterprise contracts | ✓ Developer-friendly tiers |
How every major approach stacks up against the AI agent credential problem.
| Capability | Cloud Vaults | Scanners | Guardrails | Aembit | Heimdall |
|---|---|---|---|---|---|
| Agent never sees the secret | ✗ | ✗ | ✗ | ✓ | ✓ |
| No code changes needed | ✗ | ✓ | ✓ | ⚠ | ✓ |
| Prevents prompt injection leaks | ✗ | ✗ | ⚠ | ✓ | ✓ |
| Built for AI agent workflows | ✗ | ✗ | ⚠ | ⚠ | ✓ |
| Works in minutes | ✗ | ✓ | ✓ | ✗ | ✓ |
| Covers outbound API auth | ✓ | ✗ | ✗ | ✓ | ✓ |
"Secret scanners find the fire. Vaults lock the matches. Guardrails try to catch sparks.
Heimdall makes sure the fire never starts."
The only solution built from the ground up to keep secrets out of the AI agent's hands - architecturally, not reactively.