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threatmap

CI Python License: MIT Offline

Static IaC threat modeler that parses Terraform, CloudFormation, and Kubernetes manifests and produces a structured STRIDE threat model report with a data flow diagram. No network calls, no cloud credentials, fully offline.


Quick Start

pip install threatmap
# Run as a command
threatmap scan ./examples --output report.md --fail-on HIGH
# Or as a module
python -m threatmap scan ./examples --ascii

Supported Formats and Providers

Format Provider Extension
Terraform HCL AWS, Azure, GCP .tf
CloudFormation AWS .yaml, .yml, .json
Kubernetes manifests Kubernetes .yaml, .yml

Install

Install from PyPI:

pip install threatmap

Or for local development:

git clone https://github.com/bogdanticu88/threatmap.git
cd threatmap
pip install -e .

Usage

Scan a directory and print a Markdown report to stdout:

threatmap scan ./terraform/

Scan multiple paths and write a JSON report to a file:

threatmap scan ./terraform/ ./k8s/ ./cloudformation/ --format json --output report.json

Generate an interactive HTML report or a SARIF report for GitHub Security:

threatmap scan ./infra/ --format html --output report.html
threatmap scan ./infra/ --format sarif --output report.sarif

CI gate β€” exit code 1 if any CRITICAL or HIGH threat is found:

threatmap scan ./infra/ --fail-on HIGH --output threat-report.md

Print a terminal summary table only, without writing a full report:

threatmap scan ./infra/ --summary

Use ASCII-only severity indicators (no emojis) for environments that don't support Unicode:

threatmap scan ./infra/ --ascii --output report.md

Sample Report Output

Running threatmap scan ./examples --output report.md against the bundled examples produces a full Markdown report. Below is a representative excerpt.

STRIDE Threat Table

ID Severity STRIDE Category Resource Description
T-001 πŸ”΄ CRITICAL Information Disclosure AuditBucket S3 bucket 'AuditBucket' has no public access block configured β€” bucket may be publicly accessible.
T-002 πŸ”΄ CRITICAL Spoofing WebSecurityGroup Security group 'WebSecurityGroup' exposes SSH/RDP (port 22/3389) to 0.0.0.0/0.
T-003 πŸ”΄ CRITICAL Elevation of Privilege app_contributor Role assignment 'app_contributor' grants the privileged role 'Contributor'.
T-006 🟠 HIGH Information Disclosure AuditBucket S3 bucket 'AuditBucket' does not have server-side encryption configured.
T-008 🟠 HIGH Elevation of Privilege api Container 'api' in Deployment 'api' may run as root (no runAsNonRoot=true or runAsUser=0).
T-011 🟠 HIGH Elevation of Privilege web EC2 instance 'web' allows IMDSv1 β€” metadata service accessible without session tokens, enabling SSRF-based credential theft.

Mitigation Detail (excerpt)

### T-002 β€” Spoofing (CRITICAL)

Resource:   AWS::EC2::SecurityGroup.WebSecurityGroup
Property:   ingress.ssh_rdp_open
Finding:    Security group 'WebSecurityGroup' exposes SSH/RDP (port 22/3389) to 0.0.0.0/0.
Mitigation: Remove public SSH/RDP access. Use AWS Systems Manager Session Manager
            or a bastion host with IP restrictions.

Data Flow Diagram (Mermaid)

The report appends a Mermaid flowchart LR diagram. Nodes are coloured by worst-case severity (πŸ”΄ red = CRITICAL, 🟠 orange = HIGH). Paste the block into any Mermaid renderer or view it directly on GitHub.

flowchart LR
    Internet((Internet))
    subgraph Networking
        aws_security_group_web_sg{web_sg}
        NetworkPolicy_default_deny{default-deny}
        azurerm_network_security_group_app_nsg{app_nsg}
    end
    subgraph Compute
        aws_instance_web[web]
    end
    subgraph Kubernetes
        Namespace_myapp[myapp]
        Deployment_api[api]
        Service_api_svc[api-svc]
        Ingress_api_ingress[api-ingress]
    end
    subgraph Data
        aws_s3_bucket_app_data[(app_data)]
        aws_db_instance_app_db[(app_db)]
        azurerm_storage_account_app_storage[(app_storage)]
    end
    subgraph Security
        azurerm_key_vault_app_kv[app_kv]
    end
    subgraph Identity
        azurerm_role_assignment_app_contributor[/app_contributor/]
    end
    AWS__S3__Bucket_AppBucket -->|ref| AWS__S3__Bucket_AuditBucket
    AWS__CloudTrail__Trail_AppTrail -->|ref| AWS__S3__Bucket_AuditBucket
    Internet -->|HTTPS| Ingress_api_ingress
    style aws_security_group_web_sg fill:#ff4444,color:#fff
    style aws_s3_bucket_app_data fill:#ff4444,color:#fff
    style aws_instance_web fill:#ff8800,color:#fff
    style Deployment_api fill:#ff8800,color:#fff
    style azurerm_key_vault_app_kv fill:#ffcc00,color:#000
    style azurerm_network_security_group_app_nsg fill:#ff8800,color:#fff
    style azurerm_role_assignment_app_contributor fill:#ff4444,color:#fff
Loading

Advanced Features (v1.1.0+)

Graph-based Attack Path Analysis

threatmap now includes Graph Intelligence that traces relationships between resources. It automatically identifies "chained" threats where a compromise of one resource (e.g., an internet-exposed EC2) leads directly to another (e.g., a private S3 bucket), flagging these as Elevation of Privilege attack paths.

Custom YAML Rules

You can define internal security requirements by creating a threatmap_rules.yaml in your project root.

rules:
  - resource_type: "aws_s3_bucket"
    property: "force_destroy"
    expected: false
    stride: "Tampering"
    severity: "MEDIUM"
    description: "Production buckets should not have force_destroy enabled."
    mitigation: "Set force_destroy = false."

Remediation Hints

Most findings now include a remediation field (visible in JSON, HTML, and SARIF reports) that provides the exact code snippet needed to fix the security issue.


Where rules live

Each cloud provider has its own analyzer module:

threatmap/analyzers/
β”œβ”€β”€ aws.py         # 22 rules β€” S3, IAM, EC2, RDS, EKS, CloudTrail, KMS, Lambda
β”œβ”€β”€ azure.py       # 19 rules β€” Storage, Key Vault, NSG, RBAC, AKS, ACR, SQL
β”œβ”€β”€ gcp.py         # 15 rules β€” GCS, Firewall, Compute, Cloud SQL, GKE, IAM, KMS
└── kubernetes.py  # 17 rules β€” workloads, RBAC, network, secrets

Each rule is a function that receives a Resource object (normalised from whatever source format was parsed) and returns a Threat if the condition is met. Rules are plain Python conditionals β€” no DSL, no regex engine, no external ruleset files.

How severities are assigned

Severity reflects both exploitability and blast radius:

Severity Meaning
CRITICAL Directly exploitable with no additional preconditions (e.g. SSH open to 0.0.0.0/0, wildcard IAM policy, cluster-admin binding to anonymous)
HIGH Significant risk requiring one additional step (e.g. unencrypted RDS with public access, IMDSv1 on an EC2 instance)
MEDIUM Defence-in-depth controls missing β€” lower immediate risk but violates security baselines (e.g. no versioning, no logging, no resource limits)
LOW Best-practice gaps with limited standalone exploitability (e.g. Lambda not in VPC)

How false positives are avoided

  • No heuristics or ML β€” every rule fires on a concrete, unambiguous property value (e.g. publicly_accessible = true, Principal: "*").
  • Conservative defaults β€” if a property is absent, the rule assumes the insecure default (e.g. no metadata_options block on an EC2 instance means IMDSv1 is active, because that is AWS's default).
  • No cross-account or runtime state β€” the tool only looks at what is declared in the template. It does not attempt to infer what SCPs, permission boundaries, or runtime configs might mitigate a finding.
  • Deduplication in the engine β€” findings are keyed on (stride_category, resource_name, trigger_property) so the same logical issue is never reported twice even if it appears across multiple file formats.

CI Integration

# .github/workflows/threat-model.yml
name: Threat Model

on: [pull_request]

jobs:
  threatmap:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: "3.11"

      - name: Install threatmap
        run: pip install threatmap

      - name: Run threat model scan
        run: |
          threatmap scan ./infra/ \
            --format markdown \
            --output threat-report.md \
            --fail-on HIGH

      - name: Upload threat report
        if: always()
        uses: actions/upload-artifact@v4
        with:
          name: threat-report
          path: threat-report.md

The --fail-on HIGH flag makes the job exit with code 1 if any HIGH or CRITICAL threat is found, blocking the PR merge. The uploaded artifact gives reviewers the full report without leaving the pull request.


STRIDE Rule Coverage

Provider Rules
AWS (Terraform + CloudFormation) 22
Azure (Terraform) 19
GCP (Terraform) 15
Kubernetes 17
Total 73

Categories covered per provider:

Provider S T R I D E
AWS βœ“ βœ“ βœ“ βœ“ βœ“ βœ“
Azure βœ“ βœ“ βœ“ βœ“ β€” βœ“
GCP βœ“ βœ“ βœ“ βœ“ β€” βœ“
Kubernetes βœ“ βœ“ β€” βœ“ βœ“ βœ“

(S=Spoofing, T=Tampering, R=Repudiation, I=Information Disclosure, D=Denial of Service, E=Elevation of Privilege)


Development

Run tests:

pytest tests/ -v

Run with coverage:

pytest tests/ --cov=threatmap --cov-report=term-missing

Contributing

  1. Fork the repository
  2. Add rules in threatmap/analyzers/<provider>.py following the existing pattern
  3. Add a fixture in tests/fixtures/ that triggers the new rule
  4. Add assertions in tests/test_analyzers.py
  5. Open a pull request

About

Static IaC threat modeler , parses Terraform, CloudFormation, and Kubernetes manifests and applies STRIDE rules to produce a structured threat model report with a Mermaid DFD.

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