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Enclave
A fleet of autonomous security agents that finishes scoped security jobs end to end for AI-native companies.
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-25T23:52:31.636Z. Cached copy · Source on enclave.ai
# Enclave
> A fleet of autonomous security agents that finishes scoped security jobs end to end for AI-native companies.
Both sides have agents now. Attackers run theirs without guardrails or approval chains. Most security agents just generate more work: scan, flag, hand you a list. Enclave's agents carry the work through instead: they verify reachability and exploitability against your live environment, write each fix as a PR or infrastructure-as-code change, route it to the owner, and leave every merge to your engineers for approval. After deploy, they re-run the original attack path and confirm it no longer works.
Enclave connects repositories and cloud inventory into a living security graph. Agents run against it, reasoning about reachability, identity, exposure, and attacker preconditions, then drive each confirmed finding to a fix your team approves. The longer it runs, the more it knows about your architecture, and the faster it gets.
## Platform Capabilities
Not a pipeline of steps: a fleet of agents working one live model of your environment, in parallel and continuously, from first scan to verified closure.
- **Live security graph**: Services, repos, cloud accounts, and existing scanners connected into a single graph of components, entry points, trust boundaries, and ownership. Every pull request and infrastructure change updates it. Covers AWS, GCP, and Azure.
- **Agentic investigations**: Agents run code review, SAST, DAST, cloud misconfiguration, secrets, and supply chain analysis, alongside CVEs, pre-CVE advisories, and threat intel, reasoning about reachability, identity, exposure, and attacker preconditions the way a security researcher would.
- **Verification and triage**: Every finding is tested against the graph for reachability and exploitability in the live environment, then ranked by KEV status and business impact. What reaches the team is confirmed, prioritized exposure, not a CVSS-sorted list.
- **Batched remediation**: Agents write each fix as a PR or infrastructure-as-code change, dispatched to the coding agents you already license (BYOK), and route it to the owner in a plan optimized to close the most exposure with the least effort. Nothing merges without a human.
- **Closure verification**: After deploy, agents re-run the original attack path. If it still works, the process restarts; if not, the evidence is logged: exploit path, exact change, post-deploy re-test. An audit trail for every closed finding.
- **Security chat**: Query findings, attack paths, affected assets, ownership, and prioritization reasoning: the same live context the agents work from.
Bring your own model API keys (Anthropic, OpenAI, or Google) or run models through Enclave; the harness is purpose-built for security research. Approval gates are set per repository. Deploys as SaaS, in your private VPC (AWS, GCP, or Azure), or fully air-gapped for regulated and classified environments.
Built for CISOs, VP Security, and CloudSec and AppSec secur
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