sarif-parsing
Parses and processes SARIF files from static analysis tools like CodeQL, Semgrep, or other scanners.
Skill by idchain-world
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: devops, data, security
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What's inside
- Skill name
sarif-parsing- Description
- Parses and processes SARIF files from static analysis tools like CodeQL, Semgrep, or other scanners. Triggers on "parse sarif", "read scan results", "aggregate findings", "deduplicate alerts", or "process sarif output". Handles filtering, deduplication, format conversion, and CI/CD integration of SARIF data. Does NOT run scans — use the Semgrep or CodeQL skills for that.
- License
- MIT
- Instructions
- 471 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
- Instructions call the network
Agent Skills spec issues
- allowed-tools: must be a space-separated string
Files (3)
- SKILL.md
- jq-queries.md · resources/
- sarif_helpers.py · resources/
SKILL.md (first lines)
# SARIF Parsing Best Practices
You are a SARIF parsing expert. Your role is to help users effectively read, analyze, and process SARIF files from static analysis tools.
## When to Use
Use this skill when:
- Reading or interpreting static analysis scan results in SARIF format
- Aggregating findings from multiple security tools
- Deduplicating or filtering security alerts
- Extracting specific vulnerabilities from SARIF files
- Integrating SARIF data into CI/CD pipelines
- Converting SARIF output to other formats
## When NOT to Use
Do NOT use this skill for:
- Running static analysis scans (use CodeQL or Semgrep skills instead)
- Writing CodeQL or Semgrep rules (use their respective skills)
- Analyzing source code directly (SARIF is for processing existing scan results)
- Triaging findings without SARIF input (use variant-analysis or audit skills)
## SARIF Structure Overview
SARIF 2.1.0 is the current OASIS standard. Every SARIF file has this hierarchical structure:
```
sarifLog
├── version: "2.1.0"
├── $schema: (optional, enables IDE validation)
└── runs[] (array of analysis runs)
├── tool
│ ├── driver
│ │ ├── name (required)
│ │ ├── version
│ │ └── rules[] (rule definitions)
│ └── extensions[] (plugins)
├── results[] (findings)
│ ├── ruleId
│ ├── level (error/warning/note)
│ ├── message.text
│ ├── locations[]
│ │ └── physicalLocation
│ │ ├── artifactLocation.uri
│ │ └── region (startLine, startColumn, etc.)
│ ├── fingerprints{}
│ └── partialFingerprints{}
└── artifacts[] (scanned files metadata)
```
### Why Fingerprinting Matters
Without stable fingerprints, you can't track findings across runs:
- **Baseline comparison**: "Is this a new finding or did we see it before?"
- **Regression detection**: "Did this PR introduce new vulnerabilities?"
- **Suppression**: "Ignore this known false positive in future runs"
Tools report different paths (`/path/to/project/` vs `/github/workspace/`), so path-based matching fails. Fingerprints hash the *content* (code snippet, rule ID, relative location) to create stable identifiers regardless of environment.
## Tool Selection Guide
| Use Case | Tool | Installation |
|----------|------|--------------|
| Quick CLI queries | jq | `brew install jq` / `apt install jq` |
| Python scripting (simple) | pysarif | `pip install pysarif` |
| Python scripting (advanced) | sarif-tools | `pip install sarif-tools` |
| .NET applications | SARIF SDK | NuGet package |
| JavaScript/Node.js | sarif-js | npm package |
| Go applications | garif | `go get github.com/chavacava/garif` |
| Validation | SARIF Validator | sarifweb.azurewebsites.net |
## Strategy 1: Quick Analysis with jq
For rapid exploration and one-off queries:
```bash
# Pretty print the file
jq '.' results.sarif
# Count total findings
jq '[.runs[].results[]] | length' results.sarif
# List all rule IDs triggered
jq '[.runs[].results[].ruleId] | unique' results.sarif
# Extract errors only
jq '.runs[].results[] | select(.level == "error")' results.sarif
# Get findings with file locations
jq '.runs[].results[] | {
rule: .ruleId,
message: .message.text,
file: .locations[0].physicalLocation.artifactLocation.uri,
line: .locations[0].physicalLocation.region.startLine
}' results.sarif
# Filter by severity and get count per rule
jq '[.runs[].results[] | select(.level == "error")] | group_by(.ruleId) | map({rule: .[0].ruleId, count: length})' results.sarif
# Extract findings for a specific file
jq --arg file "src/auth.py" '.runs[].results[] | select(.locations[].physicalLocation.artifactLocation.uri | contains($file))' results.sarif
```
## Strategy 2: Python with pysarif
For programmatic access with full object model:
```python
from pysarif import load_from_file, save_to_file
# Load SARIF file
sarif = load_from_file("results.sarif")
# Iterate through runs and results
for run in sarif.runs:
tool_name = run.tool.driver.name
print(f"Tool: {tool_name}")From idchain-world/id-agents, MIT.
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Signals
- Stars
- 18
- Forks
- 4
- Open issues
- 0
- Last commit (this folder)
- Apr 25, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/idchain-world/id-agents
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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sarif-parsing skill. Agent Mart. https://agentmart.dev/skills/idchain-world-sarif-parsing (last updated 2026-10-24)