CVE Report Aggregation and Deduplication Tool

A Python package for aggregating and deduplicating Grype and Trivy vulnerability scan reports, extracted from Zarf packages. Optionally enrich CVE data using OpenAI GPT models to provide actionable mitigation summaries in the context of UDS Core security controls.

Important

Will implement customizable prompts and support for additional AI providers in future releases.

Features

Self-Contained Docker Image: Includes all scanning tools (Grype, Syft, Trivy, UDS CLI) in a single hardened Alpine-based image
Supply Chain Security: SLSA Level 3 compliant with signed images, SBOMs, and provenance attestations
AI-Powered CVE Enrichment: Optional OpenAI integration for automated vulnerability mitigation analysis
Production-Ready Package: Installable via pip/pipx with proper dependency management
Rich Terminal Output: Beautiful, color-coded tables and progress indicators using the Rich library
Multi-Scanner Support: Works with both Grype and Trivy scanners
SBOM Auto-Scan: Automatically detects and scans Syft SBOM files with Grype
Auto-Conversion: Automatically converts Grype reports to CycloneDX format for Trivy scanning
CVE Deduplication: Combines identical vulnerabilities across multiple scans
Automatic Null CVSS Filtering: Filters out invalid CVSS scores (null, N/A, or zero) from all vulnerability reports
CVSS 3.x-Based Severity Selection: Optional mode to select highest severity based on actual CVSS 3.x base scores
Scanner Source Tracking: Identifies which scanner (Grype or Trivy) provided the vulnerability data
Occurrence Tracking: Counts how many times each CVE appears
Parallel Processing: Concurrent package downloading with configurable worker pools (10-14x speedup)
Flexible CLI: Click-based interface with rich-click styling and sensible defaults
Full Test Coverage: Comprehensive test suite with pytest (237 tests, 91% coverage)
Security Hardened: Non-root user (UID 1001), minimal Alpine base, pinned dependencies, and vulnerability-scanned

Configuration

CVE Report Aggregator supports flexible configuration through multiple sources with the following precedence (highest to lowest):

CLI Arguments - Command-line flags and options
YAML Configuration File - .cve-aggregator.yaml or .cve-aggregator.yml
Environment Variables - Prefixed with CVE_AGGREGATOR_
Default Values

CLI Options

Option	Short	Description	Default
`--input-dir`	`-i`	Input directory containing scan reports or SBOMs	`./reports`
`--scanner`	`-s`	Scanner type to process (`grype` or `trivy`)	`grype`
`--log-level`	`-l`	Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)	`INFO`
`--mode`	`-m`	Aggregation mode: `highest-score`, `first-occurrence`, `grype-only`, `trivy-only`	`highest-score`
`--enrich-cves`		Enable CVE enrichment with OpenAI	`false`
`--openai-api-key`		OpenAI API key (defaults to `OPENAI_API_KEY` env var)	None
`--openai-model`		OpenAI model to use for enrichment	`gpt-5-nano`
`--openai-reasoning-effort`		Reasoning effort level (`low`, `medium`, `high`)	`medium`
`--max-cves-to-enrich`		Maximum number of CVEs to enrich	None (all)
`--enrich-severity-filter`		Severity levels to enrich (can be used multiple times)	`Critical`, `High`
`--help`	`-h`	Show help message and exit	N/A
`--version`		Show version and exit	N/A

YAML Configuration File

Create a .cve-aggregator.yaml or .cve-aggregator.yml file in your project directory:

# Scanner and processing settings
scanner: grype                          # Scanner type: grype or trivy
mode: highest-score                     # Aggregation mode
log_level: INFO                         # Logging level

input_dir: ./reports                    # Input directory for reports

# Parallel processing
maxWorkers: 14                          # Concurrent download workers (auto-detect if omitted)

# Remote package downloads
downloadRemotePackages: true            # Enable remote SBOM downloads
registry: registry.defenseunicorns.com
organization: sld-45
packages:
  - name: gitlab
    version: 18.4.2-uds.0-unicorn
    architecture: amd64
  - name: gitlab-runner
    version: 18.4.0-uds.0-unicorn
    architecture: amd64

# CVE Enrichment (OpenAI)
enrich:
  enabled: true
  provider: openai  # only openai is supported currently
  model: gpt-5  # OpenAI model (gpt-5-nano, gpt-4o, etc.)
  # apiKey: YOUR_OPENAI_API_KEY_HERE # or set via OPENAI_API_KEY environment variable
  reasoningEffort: medium  # Level of reasoning effort: minimal, low, medium, high
  severities:  # Severity levels to enrich
    - Critical
    - High
  verbosity: medium  # Verbosity level: low, medium, high
  seed: 42  # Optional: Seed for reproducibility
  metadata:  # Optional: Metadata tags for OpenAI requests
    project: cve-report-aggregator
    organization: defenseunicorns

See .cve-aggregator.example.yaml for a complete example.

Environment Variables

All configuration options can be set via environment variables with the CVE_AGGREGATOR_ prefix (with the exception of the OPENAI_API_KEY, which has no prefix). For example:

# Scanner settings
export CVE_AGGREGATOR_SCANNER=grype
export CVE_AGGREGATOR_MODE=highest-score
export CVE_AGGREGATOR_LOG_LEVEL=DEBUG

# Input/output
export CVE_AGGREGATOR_INPUT_DIR=/path/to/reports
export CVE_AGGREGATOR_OUTPUT_FILE=/path/to/output.json

# Parallel processing
export CVE_AGGREGATOR_MAX_WORKERS=14

# Remote packages
export CVE_AGGREGATOR_DOWNLOAD_REMOTE_PACKAGES=true
export CVE_AGGREGATOR_REGISTRY=registry.example.com
export CVE_AGGREGATOR_ORGANIZATION=my-org

# CVE Enrichment
export OPENAI_API_KEY=sk-...                            # OpenAI API key (no prefix)
export CVE_AGGREGATOR_ENRICH_CVES=true
export CVE_AGGREGATOR_OPENAI_MODEL=gpt-5-nano
export CVE_AGGREGATOR_OPENAI_REASONING_EFFORT=medium
export CVE_AGGREGATOR_MAX_CVES_TO_ENRICH=50

Configuration Examples

Basic Usage with Defaults

# Process reports from ./reports/ with default settings
cve-report-aggregator

# Output: $HOME/output/unified-YYYYMMDDhhmmss.json

Custom Scanner and Verbosity

# Use Trivy scanner with debug logging
cve-report-aggregator --scanner trivy --log-level DEBUG

CVE Enrichment

# Enable AI-powered enrichment for Critical and High CVEs
export OPENAI_API_KEY=sk-...
cve-report-aggregator --enrich-cves

# Customize enrichment settings
cve-report-aggregator \
  --enrich-cves \
  --openai-model gpt-4o \
  --openai-reasoning-effort high \
  --max-cves-to-enrich 10 \
  --enrich-severity-filter Critical

Remote Package Downloads

# .cve-aggregator.yaml
downloadRemotePackages: true
registry: registry.defenseunicorns.com
organization: sld-45
maxWorkers: 14
packages:
  - name: gitlab
    version: 18.4.2-uds.0-unicorn

# Run with config file
cve-report-aggregator --config .cve-aggregator.yaml

Performance

CVE Report Aggregator now supports parallel processing for significantly faster execution with large package sets:

Parallel Package Downloading

When downloading SBOM reports from remote registries (e.g., using UDS Zarf), packages are downloaded concurrently using a configurable worker pool:

# .cve-aggregator.yaml
maxWorkers: 14  # Number of concurrent download workers (optional)

You can expect the following performance improvements when utilizing parallel downloads (ThreadPoolExecutor):

~10-15 seconds for 14 packages
A 10-14x speedup compared to sequential downloads (which can take ~150s for 14 packages)

Auto-Detection: If maxWorkers is not specified, the optimal worker count is automatically detected using the formula: min(<number_of_packages>, cpu_cores * 2 - 2). Set to 1 to disable parallelization.

Thread Safety: All parallel operations use thread-safe data structures (Lock()) to ensure data integrity across concurrent workers.

Prerequisites

Depending on scanner choice:

grype - For Grype scanning (default scanner)
syft - For converting reports to CycloneDX format (Trivy workflow)
trivy - For Trivy scanning

# Install Grype
brew install grype

# Install syft (for Trivy workflow)
brew install syft

# Install trivy
brew install aquasecurity/trivy/trivy

Installation

Using Docker (Recommended)

The easiest way to use CVE Report Aggregator is via the pre-built Docker image, which includes all necessary scanning tools (Grype, Syft, Trivy, UDS CLI):

# Pull the latest signed image from GitHub Container Registry
docker pull ghcr.io/mkm29/cve-report-aggregator:latest

# Or build locally
docker build -t cve-report-aggregator .

# Or use Docker Compose
docker compose run cve-aggregator --help

# Run with mounted volumes for reports and output
docker run --rm \
  -v $(pwd)/reports:/workspace/reports:ro \
  -v $(pwd)/output:/home/cve-aggregator/output \
  ghcr.io/mkm29/cve-report-aggregator:latest \
  --input-dir /workspace/reports \
  --verbose

# Note: Output files are automatically saved to $HOME/output with package name and version:
# Format: <package_name>-<package_version>.json (e.g., core-logging-0.54.1-unicorn.json)

Image Security & Supply Chain

All container images are built with enterprise-grade security:

Signed with Cosign: Keyless signing using GitHub OIDC identity
SBOM Included: CycloneDX and SPDX attestations attached to every image
Provenance: SLSA Level 3 compliant build attestations
Multi-Architecture: Supports both amd64 and arm64
Vulnerability Scanned: Regularly scanned with Grype and Trivy

Verify Image Signature

# Install cosign
brew install cosign

# Verify the image signature
cosign verify ghcr.io/mkm29/cve-report-aggregator:latest \
  --certificate-identity-regexp='https://github.com/mkm29/cve-report-aggregator' \
  --certificate-oidc-issuer='https://token.actions.githubusercontent.com'

# Output shows verified signature with GitHub Actions identity

Download and Verify SBOM

# Download CycloneDX SBOM (JSON format)
cosign verify-attestation ghcr.io/mkm29/cve-report-aggregator:latest \
  --type cyclonedx \
  --certificate-identity-regexp='https://github.com/mkm29/cve-report-aggregator' \
  --certificate-oidc-issuer='https://token.actions.githubusercontent.com' | \
  jq -r '.payload' | base64 -d | jq . > sbom-cyclonedx.json

# Download SPDX SBOM (JSON format)
cosign verify-attestation ghcr.io/mkm29/cve-report-aggregator:latest \
  --type spdx \
  --certificate-identity-regexp='https://github.com/mkm29/cve-report-aggregator' \
  --certificate-oidc-issuer='https://token.actions.githubusercontent.com' | \
  jq -r '.payload' | base64 -d | jq . > sbom-spdx.json

# View all attestations and signatures
cosign tree ghcr.io/mkm29/cve-report-aggregator:latest

Download Build Provenance

# Download SLSA provenance attestation
cosign verify-attestation ghcr.io/mkm29/cve-report-aggregator:latest \
  --type slsaprovenance \
  --certificate-identity-regexp='https://github.com/mkm29/cve-report-aggregator' \
  --certificate-oidc-issuer='https://token.actions.githubusercontent.com' | \
  jq -r '.payload' | base64 -d | jq . > provenance.json

Available Image Tags

Images are published to GitHub Container Registry with the following tags:

latest - Latest stable release (recommended for production)
v*.*.* - Specific version tags (e.g., v0.5.1, v0.5.2)
rc - Release candidate builds (for testing pre-release versions)

# Pull specific version
docker pull ghcr.io/mkm29/cve-report-aggregator:v0.5.1

# Pull latest stable
docker pull ghcr.io/mkm29/cve-report-aggregator:latest

# Pull release candidate (if available)
docker pull ghcr.io/mkm29/cve-report-aggregator:rc

All tags are signed and include full attestations (signature, SBOM, provenance).

CVE Enrichment

CVE Report Aggregator supports optional AI-powered enrichment using OpenAI GPT models to automatically analyze vulnerabilities in the context of UDS Core security controls. This feature generates concise, actionable mitigation summaries that explain how defense-in-depth security measures help protect against specific CVEs.

Key Features

gpt-5-nano with Batch API: Cost-optimized analysis with 50% discount on already low token costs
Asynchronous Processing: Submits all CVEs to OpenAI Batch API and polls for completion
UDS Core Security Context: Analyzes 20+ NetworkPolicies and 19 Pepr admission policies
Single-Sentence Summaries: Format "UDS helps to mitigate {CVE_ID} by {explanation}"
Configurable Reasoning Effort: Tune analysis depth with low, medium, or high settings
Severity Filtering: Default enrichment for Critical and High severity only
Flexible Configuration: CLI, YAML, or environment variables

Note: Batch API enrichment typically completes within minutes to hours (up to 24-hour maximum). The CLI will poll for completion automatically and display progress updates.

Quick Start

# Set API key
export OPENAI_API_KEY=sk-...

# Enable enrichment (enriches Critical and High severity CVEs by default)
cve-report-aggregator --enrich-cves

# Customize enrichment with higher reasoning effort
cve-report-aggregator \
  --enrich-cves \
  --openai-model gpt-4o \
  --openai-reasoning-effort high \
  --max-cves-to-enrich 10 \
  --enrich-severity-filter Critical

Reasoning Effort

The openai_reasoning_effort parameter controls how deeply the AI model analyzes each CVE:

minimal: Basic analysis with minimal token usage
low: Faster, more concise analysis with lower token usage
medium (default): Balanced analysis with good quality and reasonable token usage
high: Most thorough analysis with higher quality but increased token usage

When to adjust:

Use minimal for quick overviews or large CVE sets
Use low for large CVE sets where speed and cost are priorities
Use medium (default) for most production use cases
Use high for critical vulnerabilities requiring detailed analysis

Note: The reasoning_effort parameter is only supported by GPT-5 models (gpt-5-nano, gpt-5-mini). The temperature parameter is fixed at 1.0 for GPT-5 models as required by OpenAI.

# Example: High-quality analysis for critical CVEs only
cve-report-aggregator \
  --enrich-cves \
  --openai-reasoning-effort high \
  --enrich-severity-filter Critical

Cost Optimization

The system achieves extremely low costs through:

gpt-5-nano: Ultra cost-effective model ($0.150/1M input, $0.600/1M output tokens)
OpenAI Batch API: 50% cost discount compared to synchronous API calls
Single-Sentence Format: 80% fewer output tokens (100 vs 500 tokens per CVE)
Severity Filtering: ~70% fewer CVEs enriched (Critical/High only by default)

Batch API Benefits:

The OpenAI Batch API processes requests asynchronously with significant cost savings:

50% cost discount on all API calls (applied automatically)
Processes all CVEs in a single batch submission
Results available within 24 hours (typically much faster)
Automatic retry and error handling

Cost Examples (gpt-5-nano with Batch API @ 50% discount):

10 CVEs: ~$0.0006 (11,000 tokens @ $0.075/1M input, $0.300/1M output)
100 CVEs: ~$0.006 (110,000 tokens)
1,000 CVEs: ~$0.06 (1,100,000 tokens)

Comparison with Standard Pricing:

100 CVEs with Batch API (gpt-5-nano): $0.006
100 CVEs without Batch API (gpt-5-nano): $0.012
100 CVEs with GPT-4: ~$12.00
Cost Reduction vs GPT-4: 99.95%
Cost Reduction vs Synchronous API: 50%

Output Format

Enrichments are added to the unified report under the enrichments key:

{
  "enrichments": {
    "CVE-2024-12345": {
      "cve_id": "CVE-2024-12345",
      "mitigation_summary": "UDS helps to mitigate CVE-2024-12345 by enforcing non-root container execution through Pepr admission policies and blocking unauthorized external network access via default-deny NetworkPolicies.",
      "analysis_model": "gpt-5-nano",
      "analysis_timestamp": "2025-01-20T12:34:56.789Z"
    }
  },
  "summary": {
    "enrichment": {
      "enabled": true,
      "total_cves": 150,
      "enriched_cves": 45,
      "model": "gpt-5-nano",
      "severity_filter": ["Critical", "High"]
    }
  }
}

Docker Credentials Management

The Docker container supports two methods for providing registry credentials:

Build-Time Secrets
Environment Variables

Method 1: Build-Time Secrets (Recommended)

Best for: Private container images where credentials can be baked in securely.

Create a credentials file in JSON format with username, password, and registry fields:

cat > docker/config.json <<EOF
{
  "username": "myuser",
  "password": "mypassword",
  "registry": "ghcr.io"
}
EOF
chmod 600 docker/config.json

Important: Always encrypt the credentials file with SOPS before committing:

# Encrypt the credentials file
sops -e docker/config.json.dec > docker/config.json.enc

# Or encrypt in place
sops -e docker/config.json.dec > docker/config.json.enc

Build the image with the secret:

# If using encrypted file, decrypt first
sops -d docker/config.json.enc > docker/config.json.dec

# Build with the decrypted credentials
docker buildx build \
  --secret id=credentials,src=./docker/config.json.dec \
  -f docker/Dockerfile \
  -t cve-report-aggregator:latest .

# Remove decrypted file after build
rm docker/config.json.dec

Or build directly with unencrypted file (for local development):

docker buildx build \
  --secret id=credentials,src=./docker/config.json \
  -f docker/Dockerfile \
  -t cve-report-aggregator:latest .

The credentials will be stored in the image at $DOCKER_CONFIG/config.json (defaults to /home/cve-aggregator/.docker/config.json) in proper Docker authentication format with base64-encoded credentials.

Run the container (no runtime credentials needed - uses baked-in config.json):

docker run --rm cve-report-aggregator:latest --help

Important: This method bakes credentials into the image. Only use for private registries and never push images with credentials to public registries.

Method 2: Environment Variables

docker run -it --rm \
  -e REGISTRY_URL="$UDS_URL" \
  -e UDS_USERNAME="$UDS_USERNAME" \
  -e UDS_PASSWORD="$UDS_PASSWORD" \
  -e OPENAI_API_KEY="$OPENAI_API_KEY" \
  cve-report-aggregator:latest --help

How Credentials Are Handled

The entrypoint.sh script checks for Docker authentication on startup:

Docker config.json (Build-Time): Checks if $DOCKER_CONFIG/config.json exists
- If found: Skips all credential checks and login - uses existing Docker auth
- Location: /home/cve-aggregator/.docker/config.json
Environment Variables (if config.json not found): Requires all three variables:
- REGISTRY_URL - Registry URL (e.g., registry.defenseunicorns.com)
- UDS_USERNAME - Registry username
- UDS_PASSWORD - Registry password

If config.json doesn't exist and environment variables are not provided, the container exits with an error.

From Source

# Clone the repository
git clone https://github.com/mkm29/cve-report-aggregator.git
cd cve-report-aggregator

# Install in development mode
pip install -e .

# Or install with dev dependencies
pip install -e ".[dev]"

From PyPi

# Install globally
pip install cve-report-aggregator

# Or install with pipx (recommended)
pipx install cve-report-aggregator

Usage

Basic Usage (Default Locations)

Process reports from ./reports/ and automatically save timestamped output to $HOME/output/:

cve-report-aggregator
# Output:
#   $HOME/output/<package>/<package>-<version>.json
#   $HOME/output/<package>/<package>-<version>.csv

Use Trivy Scanner

Automatically convert reports to CycloneDX and scan with Trivy:

cve-report-aggregator --scanner trivy

Process SBOM Files

The script automatically detects and scans Syft SBOM files:

cve-report-aggregator -i /path/to/sboms -v

Custom Input Directory

# Specify custom input directory (output still goes to $HOME/output)
cve-report-aggregator -i /path/to/reports

Verbose Mode

Enable detailed processing output:

cve-report-aggregator -v

Combined Options

cve-report-aggregator -i ./scans --scanner trivy -v
# Output:
#   $HOME/output/<package>/<package>-<version>.json
#   $HOME/output/<package>/<package>-<version>.csv

Use Highest Severity Across Scanners

When scanning with multiple scanners (or multiple runs of the same scanner), automatically select the highest severity rating:

# Scan the same image with both Grype and Trivy, use highest severity
grype myapp:latest -o json > reports/grype-app.json
trivy image myapp:latest -f json -o reports/trivy-app.json
cve-report-aggregator -i reports/ --mode highest-score
# Output:
#   $HOME/output/<package>/<package>-<version>.json
#   $HOME/output/<package>/<package>-<version>.csv

This is particularly useful when:

Combining results from multiple scanners with different severity assessments
Ensuring conservative (worst-case) severity ratings for compliance
Aggregating multiple scans over time where severity data may have been updated

Note: All output files are automatically saved to $HOME/output/ in a <package> subdirectory with the package version in the format <package_name>-<package_version>.json.

For complete configuration options, see the Configuration section.

Output Formats

The tool generates reports in two formats for maximum flexibility:

1. JSON Format (Unified Report)

The unified report includes:

Metadata

Generation timestamp
Scanner type and version
Source report count and filenames
Package name and version

Summary

Total vulnerability occurrences
Unique vulnerability count
Severity breakdown (Critical, High, Medium, Low, Negligible, Unknown)
Per-image scan results

Vulnerabilities (Deduplicated)

For each unique CVE/GHSA:

Vulnerability ID
Occurrence count
Selected scanner (which scanner provided the vulnerability data)
Severity and CVSS scores
Fix availability and versions
All affected sources (images and artifacts)
Detailed match information

2. CSV Format (Simplified Export)

A simplified CSV export is automatically generated alongside each unified JSON report for easy consumption in spreadsheet applications and reporting tools.

Filename Format: <package_name>-<timestamp>.csv

Columns:

CVE ID: Vulnerability identifier
Severity: Severity level (Critical, High, Medium, Low, etc.)
Count: Number of occurrences across all scanned images
CVSS: Highest CVSS 3.x score (or "N/A" if unavailable)
Impact: Impact analysis from OpenAI enrichment (if enabled)
Mitigation: Mitigation summary from OpenAI enrichment (if enabled)

Example:

"CVE-2023-4863","Critical","5","9.8","Without UDS Core controls, this critical vulnerability...","UDS helps to mitigate CVE-2023-4863 by..."
"CVE-2023-4973","High","3","7.5","This vulnerability could allow...","UDS helps to mitigate CVE-2023-4973 by..."

Features:

Sorted by severity (Critical > High > Medium > Low) and CVSS score
Includes enrichment data when CVE enrichment is enabled
UTF-8 encoded with proper CSV escaping
Compatible with Excel, Google Sheets, and data analysis tools

Location: $HOME/output/<package_name>/<package_name>-<package_version>.csv

Development

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=cve_report_aggregator --cov-report=html

# Run specific test file
pytest tests/test_severity.py

Code Quality

# Format code
black src/ tests/

# Lint code
ruff check src/ tests/

# Type checking
mypy src/

Building the Package

# Build distribution packages
python -m build

# Install locally
pip install dist/cve_report_aggregator-0.1.0-py3-none-any.whl

Project Structure

cve-report-aggregator/
├── src/
│   └── cve_report_aggregator/
│       ├── __init__.py           # Package exports and metadata
│       ├── main.py               # CLI entry point
│       ├── models.py             # Type definitions
│       ├── utils.py              # Utility functions
│       ├── severity.py           # CVSS and severity logic
│       ├── scanner.py            # Scanner integrations
│       ├── aggregator.py         # Deduplication engine
│       └── report.py             # Report generation
├── tests/
│   ├── __init__.py
│   ├── conftest.py               # Pytest fixtures
│   ├── test_severity.py          # Severity tests
│   └── test_aggregator.py        # Aggregation tests
├── pyproject.toml                # Project configuration
├── README.md                     # This file
└── LICENSE                       # MIT License

Example Workflows

Grype Workflow (Default)

# Scan multiple container images with Grype
grype registry.io/app/service1:v1.0 -o json > reports/service1.json
grype registry.io/app/service2:v1.0 -o json > reports/service2.json
grype registry.io/app/service3:v1.0 -o json > reports/service3.json

# Aggregate all reports (output saved to $HOME/output with timestamp)
cve-report-aggregator --log-level DEBUG

# Query results with jq (use the timestamped file)
REPORT=$(ls -t $HOME/output/unified-*.json | head -1)
jq '.summary' "$REPORT"
jq '.vulnerabilities[] | select(.vulnerability.severity == "Critical")' "$REPORT"

SBOM Workflow

# Generate SBOMs with Syft (or use Zarf-generated SBOMs)
syft registry.io/app/service1:v1.0 -o json > sboms/service1.json
syft registry.io/app/service2:v1.0 -o json > sboms/service2.json

# Script automatically detects and scans SBOMs with Grype
cve-report-aggregator -i ./sboms --log-level DEBUG

# Results include all vulnerabilities found (use timestamped file)
REPORT=$(ls -t $HOME/output/unified-*.json | head -1)
jq '.summary.by_severity' "$REPORT"

Trivy Workflow

# Start with Grype reports (script will convert to CycloneDX)
grype registry.io/app/service1:v1.0 -o json > reports/service1.json
grype registry.io/app/service2:v1.0 -o json > reports/service2.json

# Aggregate and scan with Trivy (auto-converts to CycloneDX)
cve-report-aggregator --scanner trivy --log-level DEBUG

# Or scan SBOMs directly with Trivy
cve-report-aggregator -i ./sboms --scanner trivy --log-level DEBUG

# View most recent output
REPORT=$(ls -t $HOME/output/unified-*.json | head -1)
jq '.summary' "$REPORT"

License

MIT License - See LICENSE file for details

Contributing

Contributions are welcome! Please:

Fork the repository
Create a feature branch
Add tests for new functionality
Ensure all tests pass
Submit a pull request

Changelog

See CHANGELOG.md for version history and changes.

Name		Name	Last commit message	Last commit date
Latest commit History 219 Commits
.github		.github
docker		docker
images		images
src/cve_report_aggregator		src/cve_report_aggregator
tests		tests
utils		utils
.cve-aggregator.example.yaml		.cve-aggregator.example.yaml
.dockerignore		.dockerignore
.gitignore		.gitignore
.hadolint.yaml		.hadolint.yaml
.markdownlint.json		.markdownlint.json
.mypy.ini		.mypy.ini
.pre-commit-config.yaml		.pre-commit-config.yaml
.release-please-manifest.json		.release-please-manifest.json
.semgrepignore		.semgrepignore
.sops.yaml		.sops.yaml
.yamlfmt		.yamlfmt
CHANGELOG.md		CHANGELOG.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
README.md		README.md
mkdocs.yml		mkdocs.yml
pyproject.toml		pyproject.toml
pytest.ini		pytest.ini
release-please-config.json		release-please-config.json
uv.lock		uv.lock

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mkm29/cve-report-aggregator

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CVE Report Aggregation and Deduplication Tool

Features

Configuration

CLI Options

YAML Configuration File

Environment Variables

Configuration Examples

Basic Usage with Defaults

Custom Scanner and Verbosity

CVE Enrichment

Remote Package Downloads

Performance

Parallel Package Downloading

Prerequisites

Installation

Using Docker (Recommended)

Image Security & Supply Chain

Verify Image Signature

Download and Verify SBOM

Download Build Provenance

Available Image Tags

CVE Enrichment

Key Features

Quick Start

Reasoning Effort

Cost Optimization

Output Format

Docker Credentials Management

Method 1: Build-Time Secrets (Recommended)

Method 2: Environment Variables

How Credentials Are Handled

From Source

From PyPi

Usage

Basic Usage (Default Locations)

Use Trivy Scanner

Process SBOM Files

Custom Input Directory

Verbose Mode

Combined Options

Use Highest Severity Across Scanners

Output Formats

1. JSON Format (Unified Report)

Metadata

Summary

Vulnerabilities (Deduplicated)

2. CSV Format (Simplified Export)

Development

Running Tests

Code Quality

Building the Package

Project Structure

Example Workflows

Grype Workflow (Default)

SBOM Workflow

Trivy Workflow

License

Contributing

Changelog

About

Resources

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Forks

Releases 16

Packages 0

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Contributors 3

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