sarif-parsing

SARIF 解析最佳实践

你是 SARIF 解析专家。你的职责是帮助用户有效地读取、分析和处理静态分析工具生成的 SARIF 文件。

适用场景

在以下情况下使用此技能：

• 读取或解读 SARIF 格式的静态分析扫描结果
• 汇总多个安全工具的发现
• 对安全警报进行去重或筛选
• 从 SARIF 文件中提取特定漏洞
• 将 SARIF 数据集成到 CI/CD 工作流中
• 将 SARIF 输出转换为其他格式

不适用场景

在以下情况下请勿使用此技能：

• 运行静态分析扫描（请改用 CodeQL 或 Semgrep 技能）
• 编写 CodeQL 或 Semgrep 规则（请改用相应的技能）
• 直接分析源代码（SARIF 用于处理已有的扫描结果）
• 在没有 SARIF 输入的情况下对发现进行分类（请改用 variant-analysis 或 audit 技能）

SARIF 结构概览

SARIF 2.1.0 是当前的 OASIS 标准。每个 SARIF 文件都具有以下层级结构：

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)

指纹为何重要

没有稳定的指纹，就无法跨运行跟踪发现：

• 基线比较：“这是新发现，还是之前就发现过？”
• 回归检测：“此 PR 是否引入了新的漏洞？”
• 抑制：“在后续运行中忽略这个已知的误报”

不同工具报告的路径各不相同（/path/to/project/ 与 /github/workspace/），因此基于路径的匹配会失败。指纹会对内容（代码片段、规则 ID、相对位置）进行哈希处理，从而创建不受环境影响的稳定标识符。

工具选择指南

使用场景	工具	安装方式
快速 CLI 查询	jq	brew install jq / apt install jq
Python 脚本（简单）	pysarif	pip install pysarif
Python 脚本（高级）	sarif-tools	pip install sarif-tools
.NET 应用程序	SARIF SDK	NuGet package
JavaScript/Node.js	sarif-js	npm package
Go 应用程序	garif	go get github.com/chavacava/garif
验证	SARIF Validator	sarifweb.azurewebsites.net

策略 1：使用 jq 快速分析

用于快速探索和临时查询：

# 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

策略 2：使用 Python 和 pysarif

用于通过完整的对象模型进行编程访问：

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}")

    for result in run.results:
        print(f"  [{result.level}] {result.rule_id}: {result.message.text}")

        if result.locations:
            loc = result.locations[0].physical_location
            if loc and loc.artifact_location:
                print(f"    File: {loc.artifact_location.uri}")
                if loc.region:
                    print(f"    Line: {loc.region.start_line}")

# Save modified SARIF
save_to_file(sarif, "modified.sarif")

策略 3：使用 Python 和 sarif-tools

用于汇总、报告和 CI/CD 集成：

from sarif import loader

# Load single file
sarif_data = loader.load_sarif_file("results.sarif")

# Or load multiple files
sarif_set = loader.load_sarif_files(["tool1.sarif", "tool2.sarif"])

# Get summary report
report = sarif_data.get_report()

# Get histogram by severity
errors = report.get_issue_type_histogram_for_severity("error")
warnings = report.get_issue_type_histogram_for_severity("warning")

# Filter results
high_severity = [r for r in sarif_data.get_results()
                 if r.get("level") == "error"]

sarif-tools CLI 命令：

# Summary of findings
sarif summary results.sarif

# List all results with details
sarif ls results.sarif

# Get results by severity
sarif ls --level error results.sarif

# Diff two SARIF files (find new/fixed issues)
sarif diff baseline.sarif current.sarif

# Convert to other formats
sarif csv results.sarif > results.csv
sarif html results.sarif > report.html

策略 4：汇总多个 SARIF 文件

合并多个工具的结果时：

import json
from pathlib import Path

def aggregate_sarif_files(sarif_paths: list[str]) -> dict:
    """Combine multiple SARIF files into one."""
    aggregated = {
        "version": "2.1.0",
        "$schema": "https://json.schemastore.org/sarif-2.1.0.json",
        "runs": []
    }

    for path in sarif_paths:
        with open(path) as f:
            sarif = json.load(f)
            aggregated["runs"].extend(sarif.get("runs", []))

    return aggregated

def deduplicate_results(sarif: dict) -> dict:
    """Remove duplicate findings based on fingerprints."""
    seen_fingerprints = set()

    for run in sarif["runs"]:
        unique_results = []
        for result in run.get("results", []):
            # Use partialFingerprints or create key from location
            fp = None
            if result.get("partialFingerprints"):
                fp = tuple(sorted(result["partialFingerprints"].items()))
            elif result.get("fingerprints"):
                fp = tuple(sorted(result["fingerprints"].items()))
            else:
                # Fallback: create fingerprint from rule + location
                loc = result.get("locations", [{}])[0]
                phys = loc.get("physicalLocation", {})
                fp = (
                    result.get("ruleId"),
                    phys.get("artifactLocation", {}).get("uri"),
                    phys.get("region", {}).get("startLine")
                )

            if fp not in seen_fingerprints:
                seen_fingerprints.add(fp)
                unique_results.append(result)

        run["results"] = unique_results

    return sarif

策略 5：提取可执行数据

import json
from dataclasses import dataclass
from typing import Optional

@dataclass
class Finding:
    rule_id: str
    level: str
    message: str
    file_path: Optional[str]
    start_line: Optional[int]
    end_line: Optional[int]
    fingerprint: Optional[str]

def extract_findings(sarif_path: str) -> list[Finding]:
    """Extract structured findings from SARIF file."""
    with open(sarif_path) as f:
        sarif = json.load(f)

    findings = []
    for run in sarif.get("runs", []):
        for result in run.get("results", []):
            loc = result.get("locations", [{}])[0]
            phys = loc.get("physicalLocation", {})
            region = phys.get("region", {})

            findings.append(Finding(
                rule_id=result.get("ruleId", "unknown"),
                level=result.get("level", "warning"),
                message=result.get("message", {}).get("text", ""),
                file_path=phys.get("artifactLocation", {}).get("uri"),
                start_line=region.get("startLine"),
                end_line=region.get("endLine"),
                fingerprint=next(iter(result.get("partialFingerprints", {}).values()), None)
            ))

    return findings

# Filter and prioritize
def prioritize_findings(findings: list[Finding]) -> list[Finding]:
    """Sort findings by severity."""
    severity_order = {"error": 0, "warning": 1, "note": 2, "none": 3}
    return sorted(findings, key=lambda f: severity_order.get(f.level, 99))

常见问题及解决方案

1. 路径规范化问题

不同工具报告路径的方式各不相同（绝对路径、相对路径、URI 编码）：

from urllib.parse import unquote
from pathlib import Path

def normalize_path(uri: str, base_path: str = "") -> str:
    """Normalize SARIF artifact URI to consistent path."""
    # Remove file:// prefix if present
    if uri.startswith("file://"):
        uri = uri[7:]

    # URL decode
    uri = unquote(uri)

    # Handle relative paths
    if not Path(uri).is_absolute() and base_path:
        uri = str(Path(base_path) / uri)

    # Normalize separators
    return str(Path(uri))

2. 跨运行的指纹不匹配

以下情况可能导致指纹不匹配：

• 不同环境中的文件路径不同
• 工具版本更改了指纹算法
• 代码经过重新格式化（导致行号改变）

解决方案： 使用多种指纹策略：

def compute_stable_fingerprint(result: dict, file_content: str = None) -> str:
    """Compute environment-independent fingerprint."""
    import hashlib

    components = [
        result.get("ruleId", ""),
        result.get("message", {}).get("text", "")[:100],  # First 100 chars
    ]

    # Add code snippet if available
    if file_content and result.get("locations"):
        region = result["locations"][0].get("physicalLocation", {}).get("region", {})
        if region.get("startLine"):
            lines = file_content.split("\n")
            line_idx = region["startLine"] - 1
            if 0 <= line_idx < len(lines):
                # Normalize whitespace
                components.append(lines[line_idx].strip())

    return hashlib.sha256("".join(components).encode()).hexdigest()[:16]

3. 数据缺失或不完整

SARIF 允许许多字段为可选项。请始终使用防御式访问：

def safe_get_location(result: dict) -> tuple[str, int]:
    """Safely extract file and line from result."""
    try:
        loc = result.get("locations", [{}])[0]
        phys = loc.get("physicalLocation", {})
        file_path = phys.get("artifactLocation", {}).get("uri", "unknown")
        line = phys.get("region", {}).get("startLine", 0)
        return file_path, line
    except (IndexError, KeyError, TypeError):
        return "unknown", 0

4. 大文件性能

对于非常大的 SARIF 文件（100MB 以上）：

import ijson  # pip install ijson

def stream_results(sarif_path: str):
    """Stream results without loading entire file."""
    with open(sarif_path, "rb") as f:
        # Stream through results arrays
        for result in ijson.items(f, "runs.item.results.item"):
            yield result

5. 架构验证

处理前进行验证，以发现格式错误的文件：

# Using ajv-cli
npm install -g ajv-cli
ajv validate -s sarif-schema-2.1.0.json -d results.sarif

# Using Python jsonschema
pip install jsonschema

from jsonschema import validate, ValidationError
import json

def validate_sarif(sarif_path: str, schema_path: str) -> bool:
    """Validate SARIF file against schema."""
    with open(sarif_path) as f:
        sarif = json.load(f)
    with open(schema_path) as f:
        schema = json.load(f)

    try:
        validate(sarif, schema)
        return True
    except ValidationError as e:
        print(f"Validation error: {e.message}")
        return False

CI/CD 集成模式

GitHub Actions

- name: Upload SARIF
  uses: github/codeql-action/upload-sarif@v3
  with:
    sarif_file: results.sarif

- name: Check for high severity
  run: |
    HIGH_COUNT=$(jq '[.runs[].results[] | select(.level == "error")] | length' results.sarif)
    if [ "$HIGH_COUNT" -gt 0 ]; then
      echo "Found $HIGH_COUNT high severity issues"
      exit 1
    fi

遇到新问题时失败

from sarif import loader

def check_for_regressions(baseline: str, current: str) -> int:
    """Return count of new issues not in baseline."""
    baseline_data = loader.load_sarif_file(baseline)
    current_data = loader.load_sarif_file(current)

    baseline_fps = {get_fingerprint(r) for r in baseline_data.get_results()}
    new_issues = [r for r in current_data.get_results()
                  if get_fingerprint(r) not in baseline_fps]

    return len(new_issues)

核心原则

1. 先验证：处理前检查 SARIF 结构
2. 处理可选字段：许多字段都是可选的；请使用防御式访问
3. 规范化路径：工具报告路径的方式各不相同；尽早进行规范化
4. 合理使用指纹：结合多种策略，实现稳定去重
5. 流式处理大文件：对于 100MB 以上的文件，使用 ijson 或类似工具
6. 审慎汇总：合并文件时保留工具元数据

技能资源

如需即用型查询模板，请参阅 resources/jq-queries.md：

• 40 多个用于常见 SARIF 操作的 jq 查询
• 严重性筛选、规则提取和聚合模式

如需 Python 工具，请参阅 resources/sarif_helpers.py：

• normalize_path() - 处理工具特定的路径格式
• compute_fingerprint() - 忽略路径，计算稳定的指纹
• deduplicate_results() - 删除多次运行中的重复结果

参考链接

• OASIS SARIF 2.1.0 规范
• Microsoft SARIF 教程
• SARIF SDK（.NET）
• sarif-tools（Python）
• pysarif（Python）
• GitHub SARIF 支持
• SARIF 验证器