Aggregate and deduplicate vulnerability scan reports from Grype and Trivy
Project description
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.yamlor.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)
Prerequisites
This depends on how you plan to use CVE Report Aggregator. The recommended method is via the Docker image, which includes all necessary tooling. In which case, the only prerequisite is having Docker installed.
For running from source, you will need uv. Additionally, you will need at least one
of the following scanners installed, depending on your workflow:
You can expect the following performance improvements when utilizing parallel downloads (ThreadPoolExecutor):
~10-15seconds for 14 packages- A 10-14x speedup compared to sequential downloads (which can take
~150sfor 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)
- trivy - For Trivy scanning
- syft - For converting reports to CycloneDX format (Trivy workflow)
# 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 \
-v $(pwd)/packages:/home/cve-aggregator/packages \
ghcr.io/mkm29/cve-report-aggregator:latest \
--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.
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 usagemedium(default): Balanced analysis with good quality and reasonable token usagehigh: Most thorough analysis with higher quality but increased token usage
When to adjust:
- Use
minimalfor quick overviews or large CVE sets - Use
lowfor large CVE sets where speed and cost are priorities - Use
medium(default) for most production use cases - Use
highfor 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
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
[!IMPORTANT] Since this package (image) currently has public access, this method is not used. Changing the visibility to private would be required to safely use this method, however, since the credentials are baked in, shared credentials would need to be used for all users. This method makes it difficult to granularly control access per user. Consider using environment variables for more flexible credential management.
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 local/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.jsonexists- 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 usernameUDS_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 identifierSeverity: Severity level (Critical, High, Medium, Low, etc.)Count: Number of occurrences across all scanned imagesCVSS: 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
uv run pytest
# Run with coverage
uv run pytest --cov=cve_report_aggregator --cov-report=html
# Run specific test file
uv run pytest tests/test_severity.py
Code Quality
# Lint code
uv run ruff check src/ tests/
# Type checking
uv run mypy src/
# Or run both
uv run lint
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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file cve_report_aggregator-0.12.0.tar.gz.
File metadata
- Download URL: cve_report_aggregator-0.12.0.tar.gz
- Upload date:
- Size: 333.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: uv/0.9.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
632a3212bae60ec37cdcd95956ffb033398caa3ade94ca9c0e33c9d5eff841f0
|
|
| MD5 |
8f75ec47a4eb7d44d6a78d41c4d062eb
|
|
| BLAKE2b-256 |
b9189e25de6478759c74ee2dbe34c8c9e8d1e160851076b6b52a6b64b8125194
|
File details
Details for the file cve_report_aggregator-0.12.0-py3-none-any.whl.
File metadata
- Download URL: cve_report_aggregator-0.12.0-py3-none-any.whl
- Upload date:
- Size: 116.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: uv/0.9.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
472a5ceeab7661427ff60e5cf55a920106fe7a613e00bd1bea06a971474ee6ac
|
|
| MD5 |
a3ff770d8ff1eff9f9fca2eefd954fba
|
|
| BLAKE2b-256 |
e9977b05522371f0e982195395d36693178fcfade20cfededc7fab9f7120dbd8
|