AI INFRASTRUCTURE AS CODE SCANNING

Find what's
misconfigured
before it ships.

Most IaC scanners flag every deviation from a security benchmark regardless of whether the resource is deployed, internet-facing, or even attached to anything. 00felix scans your Terraform, CloudFormation, and Kubernetes configs, analyzes deployment context to understand what's actually exposed, then validates every finding with AI before it becomes a ticket. Real misconfigurations only.

iac scan: acme-corp/infra-terraform
resources scanned1,847
raw findings412
deployed and exposed38
AI-validated findings14
non-issues dismissed374
INFRASTRUCTURE AS CODE SCANNING

Every resource.
Every misconfiguration.

00felix parses your infrastructure definitions natively across Terraform, CloudFormation, Kubernetes manifests, Helm charts, and Ansible playbooks. It builds a complete resource graph from your IaC files, resolving module references, variable substitutions, and cross-stack dependencies, so it understands what your infrastructure actually looks like when deployed, not just what individual files say in isolation.

Every finding is anchored to the exact resource, block, and line in the file where the misconfiguration lives. An open S3 bucket in module/storage/main.tf at resource aws_s3_bucket.uploads is a different finding from one in module/logs/main.tf, and 00felix tracks them separately with their full context.

iac scan · infra-terraform
// resources parsed: 1,847
Terraform · 312 modules · 1,204 resources
Kubernetes · 38 manifests · 643 resources
 
// findings by category
Public storage buckets     · 11 resources
Overpermissive IAM        · 47 resources
Unencrypted storage       · 83 resources
Open ingress (0.0.0.0/0)  · 14 resources
Missing audit logging      · 91 resources
 
412 raw findings · 1,847 resources · full graph resolved
FINDING TYPES

Every class of misconfiguration
across your infrastructure.

Public Storage
S3 buckets, GCS buckets, and Azure Blob containers with public access enabled, including ACL and bucket policy conflicts that inadvertently open private buckets.
Overpermissive IAM
Roles, policies, and service accounts with wildcard actions, overly broad resource scopes, or missing condition keys that violate least-privilege principles.
Open Network Ingress
Security groups, firewall rules, and network policies with 0.0.0.0/0 ingress on sensitive ports including SSH (22), RDP (3389), and database ports.
Unencrypted Resources
Storage volumes, database instances, S3 buckets, SQS queues, and Kubernetes secrets without encryption at rest enabled or using weak key configurations.
Missing Audit Logging
CloudTrail, VPC flow logs, S3 access logging, and Kubernetes audit logs disabled on resources handling sensitive data or privileged operations.
Insecure Container Config
Kubernetes workloads running as root, with privileged containers, without read-only root filesystems, or missing seccomp and AppArmor profiles.
deployment context analysis
PROD
aws_s3_bucket.customer-data
acl = "public-read" · internet-facing · contains PII
ESCALATE
PROD
aws_security_group.db · port 5432
ingress 0.0.0.0/0 · RDS instance attached
ESCALATE
STG
aws_s3_bucket.test-uploads
acl = "public-read" · staging workspace · no PII
DEV
aws_security_group.dev-ssh · port 22
ingress 0.0.0.0/0 · dev env · no prod traffic
2 of 4 findings escalated · same misconfiguration, different risk based on deployment context
DEPLOYMENT CONTEXT ANALYSIS

The same misconfiguration means something different in prod than in dev.

An open S3 bucket in a dev workspace that's never touched by production traffic is not the same risk as an open S3 bucket holding production customer data. A security group open to 0.0.0.0/0 on port 22 in an isolated development VPC with no internet gateway is not the same as the same rule on a production database server.

00felix resolves your Terraform workspaces, CloudFormation stacks, and Kubernetes namespaces to understand which resources are deployed to which environments, what data they handle, and what network paths reach them. Misconfigurations on non-production resources with no sensitive data are deprioritized. The same misconfiguration in production is escalated. Traditional IaC scanners treat both identically.

AI-VALIDATED FINDINGS

Deployed and exposed doesn't
always mean exploitable.
AI validates the difference.

Deployment context tells you whether a misconfigured resource is in production and reachable. It doesn't tell you whether the specific configuration is intentional or whether there's a compensating control elsewhere that changes the risk. A public S3 bucket serving a static marketing website is functioning as designed. A public S3 bucket that happens to store CloudTrail logs is a critical finding. The IaC definition for both looks identical to a scanner without context.

00felix runs an AI validation pass on every deployed, exposed finding to assess real-world risk: is this configuration intentional based on the resource's tags, purpose, and data classification? Is there a WAF, a CloudFront distribution, or an IAM policy boundary that changes the exposure? Findings that clear AI validation are confirmed. Findings that don't are dismissed with a specific, readable reason. Every decision is visible and can be overridden by your team.

ai validation pass
Public S3 bucket AI reviewed
aws_s3_bucket.customer-data · prod · tagged: PII
● CONFIRMED
Open port 5432 ingress AI reviewed
aws_security_group.db · prod · RDS attached
● CONFIRMED
Public S3 bucket AI reviewed
aws_s3_bucket.marketing-site · prod · static assets
✕ DISMISSED · intentional, public static site
Wildcard IAM action AI reviewed
aws_iam_policy.deploy-role · s3:* on deploy bucket only
✕ DISMISSED · resource scope limits blast radius
Unencrypted EBS volume AI reviewed
aws_instance.payment-worker · prod · no KMS key
● CONFIRMED
THE IAC SCAN PIPELINE

From IaC file to confirmed
finding in one pass.

01
Parse IaC files and build the resource graph
00felix parses your Terraform modules, CloudFormation stacks, Kubernetes manifests, and Helm charts from your GitHub repositories. It resolves module references, variable substitutions, and cross-stack outputs to build a complete picture of what your infrastructure looks like when deployed.
02
Match resources against misconfiguration rules
Every parsed resource is evaluated against a library of misconfiguration rules covering CIS benchmarks, AWS/GCP/Azure security baselines, NSA Kubernetes hardening guidance, and custom policy rules. Every match is recorded with its severity, affected attribute, and the exact block in the file.
03
Resolve deployment context
00felix resolves which workspace, stack, or namespace each resource belongs to and classifies it by environment (production, staging, development) and data sensitivity. Findings on non-production resources or resources with no sensitive data or internet exposure are deprioritized, cutting the list by up to 90%.
04
AI validates every production finding
Each finding on a deployed, exposed resource goes through an AI validation pass that evaluates real-world risk: is this configuration intentional? Are there compensating controls? Does the resource's purpose change the severity? Findings are confirmed or dismissed with a visible, auditable reason.
05
Deliver a short, confirmed list
What comes out is a prioritized list of confirmed, production-deployed, AI-validated misconfigurations with exact resource and line locations. No benchmark-checkbox noise. No findings on dev resources. No alert fatigue.
WHAT HAPPENS NEXT
00felix confirmed it.
Now it fixes it.
Verified Upgrade takes every confirmed IaC finding and remediates it at the source: the misconfigured resource block is corrected, the fix is verified against a plan output, and a PR is opened for your team to review and approve before it ships.
SEE HOW VERIFIED UPGRADE WORKS →
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misconfigured in your infrastructure.

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