Bound what AI can do.
With your own cloud controls.
Harden your cloud with native guardrails that govern AI agents, constrain risky actions, and contain AI-driven attacks before they spread.
AI collapses the response window. Architect your cloud so it has no impact.
Cloud environments already contain exploitable gaps, from misconfigurations and excessive permissions to unknown vulnerabilities and seemingly legitimate actions.
AI lets attackers discover and exploit those gaps continuously, at machine speed. Once data is stolen or systems are disrupted, detection and response can contain the incident, but they can’t undo the damage.
- Existing gaps become easier to find. AI can continuously search configurations, permissions, identities, and access paths for opportunities to exploit.
- Exploitation happens faster than response. Attackers can move from discovery to action before traditional alert, triage, and remediation workflows can catch up.
- That changes how cloud security must be architected. When response comes too late, the cloud needs to be designed around prevention, limiting what attackers can reach and what they can do in the first place.
AI agents can cross the boundaries you thought you set.
Enterprises are giving AI agents access to cloud credentials, tools, and workflows so they can act on behalf of users. An agent may be given a legitimate goal, but it will pursue that goal by whatever path its access allows. If the authorized path is blocked, it will look for another one.
Access extends beyond the task
Agents inherit permissions from the identities, tools, and pipelines they use. Those permissions may let them reach systems and data far beyond what a specific task requires.
A goal can override the intended path
An agent focused on completing a task will look for a way around an obstacle instead of stopping. A prompt can tell it what it should do, but cannot reliably limit what its access allows it to do.
Damage before detection
A human attacker chains actions over hours. An agent executes in seconds. By the time the alert fires, the resource is gone, the data is out, or the governance is detached. There is no response window.
Set the ground rules for every actor, including AI.
Restraining an agent from the inside won’t hold, because it will find a way around. Keeping its environment free of every gap isn’t realistic either. The answer is ground rules for the cloud itself: what can and cannot happen, for every actor, including AI. Blast enforces those rules through native cloud controls, so they hold no matter what the agent inherits or tries.
1Let Blast automatically map every path an agent could take.
Blast analyzes the permissions and actual behavior of every identity in your environment, human and non-human, and shows not just who has done what but who can do what. Over-permissioned agents and service accounts surface as the blast radius they represent.
2Define what’s allowed and what’s denied.
Set your own boundary or start from the one Blast recommends: which data sources AI can reach, which services it can call, which regions it can operate in, and how long its access lives. Enforcement happens in the provider’s control plane, outside the agent, so it holds regardless of inherited permissions.
3Enforce boundaries your platform teams can trust.
See exactly what each guardrail would affect, then move it from testing to production in one click. Platform teams can enforce with confidence, agents keep working, and the business keeps moving.
Autonomous attacks never stop looking.
Attackers now have AI in their hands. They do not wait for a scanner to publish a finding or for a patch window to close. AI-driven tooling continuously searches your cloud for exposures, chains them together, and exploits them at machine speed, while your own sprints and your providers’ releases keep opening new surfaces to search.
Continuous reconnaissance
A misconfiguration used to stay theoretical unless someone worked to find it. AI probes at scale, around the clock. Every public resource, over-permissioned role, and exposed path is found, and what is found is used.
Exploit before you can patch
AI shrinks the distance between discovery and exploitation to near zero. Often there is no time to patch, and the weakness is exploited before a patch exists. Detection tells you it happened. It cannot make it not happen.
Kill chains at machine speed
Stolen credentials become secret access, a stolen key becomes lateral movement, an exploited workload becomes an expanding blast radius. Each link used to take a human hours. An autonomous attacker takes minutes, and the actions cannot be undone.
Harden the cloud continuously.
If the attacker never stops searching for gaps, the defense cannot be a point-in-time fix. Blast closes the exploitable surface up front and keeps it closed as your cloud changes, so there is nothing for the attacker to find and no next move once they are in.
- Close the exploitable surface before the attack arrives.Public access, risky service calls, and critical actions are denied by default for any actor.
- Break the kill chain at every link.Stolen credentials and keys can’t reach secrets or move laterally.
- Keep the surface closed as the cloud changes.New accounts inherit the guardrails, and drift is caught before it becomes a gap.
Eliminate attack paths first. Make response manageable.
Blast defines what can and cannot happen in your cloud, for every actor. Each boundary eliminates attack paths, neutralizing unwanted actions before they run and leaving only a small blast radius. What’s left for detection and response is focused, controllable, and at a scale your team can actually handle.
Attack paths eliminated
Guardrails enforced in the cloud’s own control plane (SCPs, RCPs, permission boundaries, Azure Policy, and GCP Organization Policy) deny unwanted actions before they run, for any actor: human, agent, or attacker.
Scaled down to what matters
With most attack paths closed, fewer alerts fire and each one matters more. Your CNAPP and response teams work on real risk at a manageable scale, instead of chasing every finding.
Secure by design
Unwanted actions neutralized up front, a small blast radius, and response teams focused on what matters. The business can adopt AI with the worst case already contained.
“Blast gave us the capabilities to do prevention at scale. In an AI-driven era having a preventive layer that enables rather than blocks development is no longer optional, it’s foundational.”
AI agents and autonomous attacks, answered.
How is bounding an agent different from prompts, policies, or model alignment?
Prompts, policies-as-guidance, and alignment shape what an agent intends to do. None of them constrain what it can do. Blast defines the boundary outside the agent and enforces it in the cloud’s own control plane, so even an agent that is compromised, poisoned, or simply wrong cannot execute actions outside its scope.
Will guardrails break our agents and pipelines?
No. Blast replays months of your real activity against each proposed guardrail and shows exactly which agent and pipeline actions it would touch. Known automation is excluded automatically, and nothing is enforced until you approve it. When an agent is blocked later, you see the exact statement that stopped it and can grant a scoped, time-boxed exception in seconds.
Do we need to deploy an agent or proxy in front of our AI agents?
No. Enforcement happens through native cloud controls such as SCPs, RCPs, permission boundaries, Azure Policy, and GCP Organization Policy. There is no middleware to route traffic through and no software to install on the agents themselves, so the boundary holds regardless of which framework or model the agent runs on.
What happens when an AI agent inherits broader permissions than intended?
It does not matter. The boundary is enforced above the identity’s own permissions, at the organization level. An agent that inherits an over-permissioned role can still only act inside the scope you defined, because the cloud denies out-of-scope actions before they run.
How does this help against attackers using AI, not just our own agents?
The same guardrails apply to any actor. Blast closes the exploitable surface up front: public and anonymous access denied, risky service calls blocked, and irreversible actions such as detaching an account from the organization made deny-by-default. An autonomous attacker that finds a foothold has no next move, because each link in the kill chain is already blocked.
What if we cannot patch a vulnerability before AI finds it?
An enforced boundary acts as the compensating control. Even when a weakness cannot be patched in time, or a scanner has not surfaced it yet, the guardrail limits what that weakness can reach. Protection holds while patching catches up.
Which clouds and controls does this cover?
AWS, Azure, Google Cloud, and Kubernetes, using each platform’s built-in enforcement controls. Blast keeps the boundary intact as your cloud changes: new accounts, projects, and workloads inherit the guardrails automatically, and drift is re-assessed before it becomes a gap.