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CSV exports produce a flat file with one row per finding, suitable for Excel, Google Sheets, database import, and reporting workflows.

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Generating CSV

CLI: 
qai audit scan --transport stdio --command "npx @modelcontextprotocol/server-memory" \
  --format csv --output results.csv
Or convert an existing scan: 
qai audit report --input results/scan.json --format csv --output results.csv

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Columns

ColumnDescription
run_idRun identifier
target_nameTarget name
categoryFinding category (e.g., command_injection, auth)
severitySeverity level (critical, high, medium, low, info)
titleFinding title
descriptionDetailed description
| tool_name | MCP tool name associated with the finding | | owasp_mcp_id | OWASP MCP Top 10 identifier (e.g., MCP05) | | remediation | Recommended fix | | mitigation_summary | Condensed mitigation guidance (first action item or “See full report”) | | framework_ids | All framework mappings as semicolon-separated key=value pairs | | timestamp | ISO timestamp of when the finding was created |

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Example Output

run_id,target_name,category,severity,title,description,tool_name,owasp_mcp_id,remediation,mitigation_summary,framework_ids,timestamp
a1b2c3d4,memory-server,command_injection,high,Tool parameter allows shell injection,...,memory_store,MCP05,...,...,owasp_mcp_top10=MCP05; mitre_atlas=AML.T0054,2026-03-22T10:30:15

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Usage

Open directly in Excel or Google Sheets. All text fields containing commas, quotes, or newlines are properly escaped per RFC 4180. For database import: 
-- PostgreSQL
COPY findings FROM '/path/results.csv' WITH (FORMAT csv, HEADER);
For command-line analysis, use a CSV-aware tool to handle quoted fields and newlines correctly (plain cut/grep can break on RFC 4180 CSV): 
# Using csvkit (pip install csvkit)
csvcut -c severity results.csv | sort | uniq -c | sort -rn   # Count by severity
csvgrep -c severity -m high results.csv > high.csv           # Filter high-severity

# Using Python's csv module
python -c "
import csv, sys
with open('results.csv') as f:
    reader = csv.DictReader(f)
    for row in reader:
        if row['severity'] == 'high':
            print(row['title'])
"
CSV flattens the framework_ids dict into a single string column. For structured framework data, use the JSON bundle or NDJSON exports.