CloudThinker's Oliver and Cyber are an AI security operations agent that detects, analyzes, remediates, and verifies exposures across your cloud, Kubernetes, and source — autonomously, under your team's policy. Continuous AI Cyber that validates every finding with a safe read-only check, opens the fix as a merge request, and never touches production. Brokered credentials, sandboxed execution, deterministic tokenization, and a tamper-evident audit trail on every action.
Your scanners raise thousands of alerts a week — and your security team still can't tell which ones are actually exploitable.
Annual pentests are stale the day they ship. Scanner reports drown teams in false positives. Findings pile up faster than anyone can triage them, and the fix lands weeks after the exposure. Security has become a bottleneck on every release — not because the work is hard, but because a human has to prove and route every finding by hand.
Oliver and Cyber run a closed loop on every release. Each pass is recorded, so the next exposure of the same shape is handled faster than the last.
Maps your application and infrastructure and surfaces real, exploitable exposures — not a wall of raw scanner alerts.
Proves each finding with a safe, read-only exploit and assesses blast radius across tenant isolation, privilege boundaries, and business logic.
Opens the fix as a merge request or executes the runbook inside a sandbox with brokered credentials — under your approval gate.
Retests to confirm the finding is closed and writes a tamper-evident receipt of everything it did.
The agent starts read-only and earns scope per skill — from L1 (observe and propose) to L4 (act autonomously within a guardrail). Engineers set the gate; the platform enforces it on every task.
Promote each security skill from notify, to act-with-approval, to autonomous — one at a time, as it earns trust.
Scoped credentials are issued per task and live in the sandbox — never in the prompt, never in the model.
Every action runs in an isolated environment, scoped to environments you approve — production is off-limits by default.
Sensitive data is tokenized deterministically at egress — production PII and secrets never leave in the clear.
Every request an agent sends, every decision, and every action is recorded in an append-only, exportable audit log.
Your team reviews verified findings and tunes guardrails instead of triaging false positives by hand.
Every finding is proven with a safe read-only exploit before it reaches your team — no false-positive triage tax.
Remediation lands as a merge request with automatic retest, so exposures close in hours instead of weeks.
AI Cyber tests every release instead of once a year, and a CI/CD gate blocks verified criticals before they ship.
Want the full mechanics? See CloudThinker Cyber, learn what AgenticOps is, and check what your environment exposes with an Assessment.
An AI security operations agent is an autonomous software agent that runs security operations work — detecting exposures, analyzing exploitability, remediating findings, and verifying the fix — without a human driving every step. CloudThinker delivers this through Oliver and its Cyber module, which run the DARV loop (Detect, Analyze, Remediate, Verify) under team policy, with engineers on the loop rather than in the middle of every action.
AI Cyber is continuous application security testing driven by AI agents that reason about your app the way a real pentester would — chaining techniques, testing tenant isolation and privilege boundaries, and abusing business logic. Unlike a scanner that probes from the outside and guesses, CloudThinker Cyber is connected to your cloud, Kubernetes, and source, so it tests real exploitability and only reports findings it has verified with a safe, read-only check. Zero false positives reach your team.
CloudThinker is built so autonomous action stays safe. Every task runs under graduated autonomy (L1–L4) — the agent starts read-only and earns broader scope per skill. Credentials are brokered per task, never handed to the model; execution is sandboxed; sensitive data is tokenized deterministically at egress; and every action lands in a tamper-evident audit log. Testing is gray-box and scoped to environments you approve — production is off-limits by default, and engineers set the approval gate for each environment.
DARV is the four-stage loop the security agent runs on every exposure: Detect (surface a real, exploitable finding, not a raw scanner alert), Analyze (prove exploitability with a safe read-only check and assess blast radius), Remediate (open the fix as a merge request or execute the runbook inside a sandbox under policy), and Verify (retest to confirm the finding is closed). Because every loop is recorded, the next finding of the same shape is handled faster.
The artifacts a full security engagement produces: verified findings triaged with severity, owner, and SLA; the fix drafted as a merge request with automatic retest; a CI/CD release gate that blocks verified criticals; and an OWASP-aligned report with per-run evidence for SOC 2, ISO 27001, and PCI DSS — every action backed by a tamper-evident audit trail.
No — it changes what security work looks like. Your team moves from triaging false-positive-heavy scan reports to reviewing verified findings and tuning guardrails. The agent handles the repetitive detect-analyze-remediate-verify work on every release; engineers stay on the loop to approve higher-risk actions, promote skills to more autonomy, and turn recurring exposures into permanent fixes.
Point CloudThinker at one staging target and get verified findings today — read-only, scoped to environments you approve, and fixed by merge request. Start a trial or book a demo.