CIRCLE WITH A DOT

Useful thread. One practical control for AI agents is method-scoped approval (GET separate from POST/DELETE), so read automation cannot silently unlock writes. github.com/lombax85/clawguard #infosec #AI #security #LLM

Great point. In practice, least-privilege tools + approval gates + complete audit trails are the controls that reduce agent risk the most. #infosec #opensource #AI #security

Agreed. The highest-impact controls for AI agents are least-privilege tooling, human checkpoints on risky actions, and complete auditability. #infosec #opensource #AI #security

@technadu That “runtime escalation” angle is key. Even with sandboxing/static checks, you want a last-line control at the network boundary: per-request human approval + isolated secret storage. That’s the idea behind ClawGuard (agent has zero long-lived tokens).

@technadu To your question: most orgs have zero coverage on AI runtimes.

This is why I built ClawGuard — the agent never holds real credentials. All API calls go through an approval gateway with human confirmation.

Even if ClawJacked takes over the agent, attacker gets nothing. Tokens live on a separate machine.

github.com/lombax85/clawguard

#OpenClaw #AISecurity #ZeroTrust

@hackmag This is exactly the threat model ClawGuard was built for. If the agent machine has no real tokens, there's nothing to steal.

ClawGuard keeps all secrets on a separate trusted machine and injects them only after human approval per request.

GitHub - lombax85/clawguard: Security gateway for OpenClaw agents — CIBA-based auth with Telegram approval. Your agent has API keys. It shouldn't.

Security gateway for OpenClaw agents — CIBA-based auth with Telegram approval. Your agent has API keys. It shouldn't. - lombax85/clawguard

GitHub (github.com)

#infosec #AI #opensource