Identify exploitable cloud risks before attackers do

Cloud Security Testing for Modern Infrastructure

Autonomously discover and validate exploitable attack chains across identities, services, and infrastructure. Unlike static cloud security testing tools, OFFENSAI proves what is actually exploitable so your team can focus on what truly matters.

Trusted by cloud security teams worldwide

Cloud Security Challenges

Why Cloud Security Testing
Goes Beyond Detection

Cloud teams are overwhelmed by posture findings, toxic combinations, and fragmented alerts. What remains unclear is whether those exposures form real attack paths and which ones deserve immediate action.

Too many findings

Security teams inherit thousands of misconfigurations, permissions issues, and exposure alerts without a clear path to action.

No proof of exploitability

Most tools stop at detection. They do not validate whether an attacker could actually use those exposures to escalate access or reach sensitive assets.

Weak prioritization

Severity alone does not reflect real risk. Without validated paths and impact context, remediation priorities remain unclear.

The Shift: From Static Tools to Continuous Cloud Security Testing

From Cloud Security Alerts
to Validated Evidence

Cloud security testing tools that stop at detection leave teams guessing. A cloud security testing platform like OFFENSAI goes further by validating whether those exposures can be chained into meaningful attack paths across identities, services, and infrastructure.

Before

Detection Only

  • Thousands of unvalidated alerts
  • No proof of exploitability
  • Periodic, point-in-time testing
  • Manual triage with unclear priorities
  • Compliance evidence built from spreadsheets
After

Continuous Validated Path

  • Only exploitable attack paths surface
  • Every finding proven end-to-end
  • Continuous cloud security testing as your environment changes
  • Cloud security measured by true business impact
  • Audit-ready evidence mapped automatically

Platform Overview

Model. Generate.
Validate. Prioritize.

A continuous cloud security testing platform for identifying real cloud risk

Phase 1

Model

Build a structured view of cloud identities, resources, permissions, and trust relationships.

Phase 2

Generate

Explore attack path variations across APIs, IAM permissions, and service interactions.

Phase 3

Validate

Run controlled Adversarial Exposure Validation tests to prove whether cloud exposures can actually be exploited.

Phase 4

Prioritize

Surface validated results with evidence, impact context, and risk scoring.

Capabilities

Built for Continuous
Cloud Security Testing

OFFENSAI combines cloud environment intelligence, adversarial validation, and risk-based prioritization into a single cloud security testing platform that identifies exploitable exposures across AWS, Azure, and GCP.

UserIAMLambdaEC2ECSTarget
Initializing…searching...

Attack Path Discovery

Discover how attackers chain IAM permissions, service trusts, and identity relationships into full attack paths reaching your most sensitive resources.

Overpermissioned OIDC Role
Create Terraform Organization
terraform apply sts-get-caller-identity.tf
Proof of Success
arn:aws:sts::4821████9012:assumed-role/terraform-deploy/session
Stopped — no further actions taken
Validating…T1078.004

Exposure Validation

Run controlled attacks that mirror real-world techniques, and continuously validate what is truly exploitable, as your cloud environment evolves.

CSIR0.0/10
Exploitability0
Blast Radius0
Detection Gap0
Business Impact0
Calculating…SOC 2 · NIST CSF

Impact Prioritization

Prioritize risk with CSIR Risk Scoring and stop drowning in alerts. Know exactly which exposures can impact your business.

Benefits

Cloud Security Testing
You Can Trust

Every cloud security test is human-initiated, agentless, and read-only. Results are audit-ready and paired with actionable remediation guidance.

Human-Initiated by Design

Validations are only run upon user approval.

Agentless and Read-Only

Cloud environments are connected through native APIs without host agents.

Audit-Ready Output

Validated findings are structured for technical review, reporting, and follow-through.

Actionable Remediation

Results are paired with clear evidence and practical guidance, not just detection output.

Frequently Asked Questions

What is cloud security testing?

Cloud security testing is the practice of actively validating whether misconfigurations, excessive permissions, and exposed services in cloud environments can be chained into real attack paths. Rather than listing potential issues, it proves which ones an attacker could actually exploit to reach sensitive data or escalate access across AWS, Azure, and GCP.

What is autonomous cloud security testing?

Autonomous cloud security testing uses AI to continuously execute real attack chains against a live cloud environment without manual red team effort. Unlike scanners that report misconfigurations, it proves which vulnerabilities are actually exploitable by chaining them into full breach scenarios across AWS, Azure, and GCP.

What is Adversarial Exposure Validation (AEV)?

Adversarial Exposure Validation (AEV) is a Gartner-defined security category that moves beyond detection to prove which cloud exposures are actually exploitable. AEV platforms execute real attack chains, validate findings end-to-end, and score risk by business impact rather than theoretical severity.

How is cloud security testing different from CSPM?

CSPM tools passively surface potential misconfigurations but never prove whether those exposures are exploitable. Cloud security testing is active: it executes real attack chains to show exactly which misconfigurations chain into a breach. Most teams use both, with cloud security testing providing execution-level proof of what actually matters.

Why do cloud security teams need attack path analysis?

Attack path analysis maps how an attacker chains IAM permissions, service trusts, and identity relationships to move laterally through a cloud environment and reach sensitive resources. Without it, security teams are left prioritizing thousands of isolated findings with no understanding of which ones combine into real threats.

Does cloud security testing disrupt production environments?

No. Modern cloud security testing tools and platforms connect via least-privilege, read-only IAM roles and perform zero destructive actions. They simulate what an attacker could do by observing and chaining exploitable paths, without modifying, deleting, or disrupting any production workloads, data, or infrastructure.

How should security teams prioritize cloud vulnerabilities?

Severity scores alone do not reflect real risk. Effective prioritization requires understanding which vulnerabilities chain into exploitable attack paths and weighing them by data exposure, detection difficulty, attack complexity, and business impact rather than relying on theoretical CVSS ratings.

How does cloud security testing support compliance frameworks?

Cloud security testing maps executed attack chains to compliance frameworks like MITRE ATT&CK, SOC 2, ISO 27001, NIST CSF, and GDPR. Each report documents which controls were validated through real simulated attacks, replacing manual spreadsheet evidence with automated, audit-ready proof.

What is the difference between cloud penetration testing and autonomous cloud security testing?

Traditional cloud penetration testing is a periodic, point-in-time engagement that becomes outdated after your next deployment. A continuous cloud security testing platform runs attack simulations daily and adapts as your cloud changes so your security validation stays current.

Does cloud security testing work across AWS, Azure, and GCP?

Leading cloud security testing tools natively support AWS, Microsoft Azure, and Google Cloud Platform, executing attack chains across all three simultaneously with no agents, no infrastructure changes, and no disruption to production workloads.

Shift happens.
Be ready when it does.

See how OFFENSAI's cloud security testing platform helps teams move from exposure detection to controlled validation, technical evidence, and risk-based prioritization.