SolonGate DLP: Stop AI Agents from Leaking Your Secrets
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It's been a week since we launched @SolonGate . You guys are pushing the absolute limits of agentic workflows—which means you're also realizing how terrifying it is when autonomous agents actually have access to your infra.
To kill that anxiety, we just pushed DLP & Secret Scanning for SolonGate.
It scans tool arguments in milliseconds. If your agent hallucinates and tries to pass an AWS key, Anthropic token, JWT, or a custom PII regex to an external tool, SolonGate kills the call before the payload ever executes.
System prompts are a good start, but execution control is what actually saves your infrastructure. It's live on the dashboard right now. Check it out and let us know what custom patterns you're setting up. 👇
SolonGate
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@emirhandemir This actually caught my attention. As agents become more autonomous, the concern stops being "can they do it ? "and becomes "what happens when they do the wrong thing ? "Blocking risky actions before execution feels like the right layer to build around.
SolonGate
@edward_baker3Â Exactly... The "can they do it" phase is over. Now we are in the "how do we survive their mistakes" phase. If you aren't blocking risky payloads at the execution layer, you're just crossing your fingers and hoping the LLM behaves. Glad you see the vision :)
This is the right layer to focus on. Prompts and policies are useful, but once an agent can touch real infrastructure, execution-time controls matter much more.
Secret scanning inside tool arguments feels especially important because leaks can happen in places humans may never read: intermediate calls, retries, logs, or malformed tool inputs. For business teams deploying AI agents, this kind of guardrail is what makes the difference between “interesting demo” and something a company can actually allow near production systems.
SolonGate
@rahulbhavsar Spot on Sir. Everyone loves a cool agent demo until it hallucinates an AWS key into a random retry loop. That’s exactly why SolonGate sits as a transparent proxy. You can't catch those intermediate leaks with system prompts. Production requires deterministic execution control, not probabilistic prayers.
@emirhandemir That framing makes a lot of sense. The transparent proxy approach feels much closer to how teams actually need to govern agents in production: observe every intermediate step, enforce deterministic controls, and avoid relying on the model to police itself. Curious how you think about balancing strict blocking with keeping agent workflows usable.
SolonGate
@rahulbhavsar yeah you don't just blindly block everything out of the gate. start in "detect" mode, let the agent run, watch the audit logs. tweak your rules, then switch to "block" for the hard stuff. we don't force the rules, just the engine. human in the loop always
Hello @emirhandemir This is exactly the layer agents need once they move from demos to real infra. Prompts can reduce risk, but execution-time controls are what actually matter when a tool call is about to leak a token, key, or sensitive payload. Blocking the call before it runs feels like the right place to enforce trust.
SolonGate
@alpertayfurr Yep. Trusting prompts in real infra is just a disaster waiting to happen. Appreciate the support
@emirhandemir I agree and you're welcome :)