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Implement intelligent column type inference from Excel data
Add column analysis with distinct values and type statistics
Generate SQLite indexes for all table columns
Refactor cell formatting logic for improved maintainability
Diagram Walkthrough
flowchart LR
A["Excel Sheet"] -->|"Parse columns"| B["CollectColumnDistinctValues"]
B -->|"Analyze data types"| C["ColumnAnalysis"]
C -->|"Infer types"| D["InferColumnTypes"]
D -->|"Generate DDL"| E["CreateDBTableSqlString"]
E -->|"With indexes"| F["SQLite Table"]
C -->|"Generate summary"| G["Analysis Report"]
Below is a summary of compliance checks for this PR:
Security Compliance
⚪
SQL injection
Description: SQL statements are constructed via string interpolation using untrusted Excel-derived identifiers (e.g., sheet.SheetName as tableName and header-derived column names) in CreateDBTableSqlString without safely quoting/validating the table name and index name, enabling SQL injection or malformed SQL (e.g., a sheet name like x; DROP TABLE ... would be embedded into CREATE TABLE IF NOT EXISTS {tableName} and CREATE INDEX ... idx_{tableName}_{col} ...). SqliteService.cs [90-291]
Referred Code
_tableName=sheet.SheetName;_headerColumns=ParseSheetColumn(sheet);// Collect column distinct values for type inferencevarcolumnAnalyses=CollectColumnDistinctValues(sheet);varinferredTypes=InferColumnTypes(columnAnalyses);// generate column summaryvaranalysisSummary=GenerateColumnAnalysisSummary(columnAnalyses);_logger.LogInformation("Column Analysis:\n{Summary}",analysisSummary);stringcreateTableSql=CreateDBTableSqlString(_tableName,_headerColumns,inferredTypes);varrowCount=ExecuteSqlQueryForInsertion(createTableSql);// Get table schema using sqlite queryvarschema=GenerateTableSchema();return(true,$"Table `{_tableName}` has been successfully created in {Provider}. Table schema:\r\n{schema}\r\n\r\nColumn Analysis:\r\n{analysisSummary}");}catch(Exceptionex){return(false,ex.Message);
...(clipped 181lines)
Sensitive data exposure
Description: The PR logs and returns a "Column Analysis" summary that includes up to 10 distinct cell values per column (GenerateColumnAnalysisSummary), which can expose sensitive data from spreadsheets into application logs and API/UX responses when processing confidential Excel files. SqliteService.cs [98-107]
Referred Code
varanalysisSummary=GenerateColumnAnalysisSummary(columnAnalyses);_logger.LogInformation("Column Analysis:\n{Summary}",analysisSummary);stringcreateTableSql=CreateDBTableSqlString(_tableName,_headerColumns,inferredTypes);varrowCount=ExecuteSqlQueryForInsertion(createTableSql);// Get table schema using sqlite queryvarschema=GenerateTableSchema();return(true,$"Table `{_tableName}` has been successfully created in {Provider}. Table schema:\r\n{schema}\r\n\r\nColumn Analysis:\r\n{analysisSummary}");}
Ticket Compliance
⚪
🎫 No ticket provided
Create ticket/issue
Codebase Duplication Compliance
⚪
Codebase context is not defined
Follow the guide to enable codebase context checks.
Custom Compliance
🟢
Generic: Comprehensive Audit Trails
Objective: To create a detailed and reliable record of critical system actions for security analysis and compliance.
Objective: To prevent the leakage of sensitive system information through error messages while providing sufficient detail for internal debugging.
Status: Leaks internal errors: The catch block returns ex.Message directly, which can expose internal database/stack details to callers instead of a generic user-facing error with details only in secure logs.
Objective: To ensure logs are useful for debugging and auditing without exposing sensitive information like PII, PHI, or cardholder data.
Status: Logs raw data: The new column analysis logging includes sampled distinct cell values, which may contain sensitive data (PII/PHI/secrets) and is written to logs without redaction or opt-out controls.
Generic: Security-First Input Validation and Data Handling
Objective: Ensure all data inputs are validated, sanitized, and handled securely to prevent vulnerabilities
Status: SQL injection risk: SQL statements are constructed via string interpolation using Excel-controlled identifiers (sheet.SheetName as tableName and header names for index names) without strict allowlisting/escaping, enabling SQL injection or malformed SQL (especially in CREATE TABLE and CREATE INDEX).
Referred Code
_tableName=sheet.SheetName;_headerColumns=ParseSheetColumn(sheet);// Collect column distinct values for type inferencevarcolumnAnalyses=CollectColumnDistinctValues(sheet);varinferredTypes=InferColumnTypes(columnAnalyses);// generate column summaryvaranalysisSummary=GenerateColumnAnalysisSummary(columnAnalyses);_logger.LogInformation("Column Analysis:\n{Summary}",analysisSummary);stringcreateTableSql=CreateDBTableSqlString(_tableName,_headerColumns,inferredTypes);varrowCount=ExecuteSqlQueryForInsertion(createTableSql);// Get table schema using sqlite queryvarschema=GenerateTableSchema();return(true,$"Table `{_tableName}` has been successfully created in {Provider}. Table schema:\r\n{schema}\r\n\r\nColumn Analysis:\r\n{analysisSummary}");}catch(Exceptionex){return(false,ex.Message);
...(clipped 181lines)
Generic: Meaningful Naming and Self-Documenting Code
Objective: Ensure all identifiers clearly express their purpose and intent, making code self-documenting
Status: Non-descriptive variables: The new type inference lambda uses short variable names (a, n) that reduce readability and self-documentation for non-trivial logic.
Generic: Robust Error Handling and Edge Case Management
Objective: Ensure comprehensive error handling that provides meaningful context and graceful degradation
Status: Unvalidated identifiers: New DDL generation uses Excel-derived tableName/column names to build SQL without robust validation/quoting, which can fail on reserved characters and edge-case names and may surface confusing runtime errors.
Referred Code
privatestringCreateDBTableSqlString(stringtableName,List<string>headerColumns,List<string>?columnTypes=null){_columnTypes=columnTypes.IsNullOrEmpty()?headerColumns.Select(x =>"TEXT").ToList():columnTypes;varsanitizedColumns=headerColumns.Select(x =>x.Replace(" ","_").Replace("#","_")).ToList();varcolumnDefs=sanitizedColumns.Select((col,i)=>$"`{col}` {_columnTypes[i]}");varcreateTableSql=$"CREATE TABLE IF NOT EXISTS {tableName} ( Id INTEGER PRIMARY KEY AUTOINCREMENT, {string.Join(", ",columnDefs)} );";// Create index for each columnvarindexSql=sanitizedColumns.Select(col =>$"CREATE INDEX IF NOT EXISTS idx_{tableName}_{col} ON {tableName} (`{col}`);");returncreateTableSql+"\n"+string.Join("\n",indexSql);}
private string CreateDBTableSqlString(string tableName, List<string> headerColumns, List<string>? columnTypes = null)
{
...
var sanitizedColumns = headerColumns.Select(x => x.Replace(" ", "_").Replace("#", "_")).ToList();
var columnDefs = sanitizedColumns.Select((col, i) => $"`{col}` {_columnTypes[i]}");
- var createTableSql = $"CREATE TABLE IF NOT EXISTS {tableName} ( Id INTEGER PRIMARY KEY AUTOINCREMENT, {string.Join(", ", columnDefs)} );";+ var quotedTableName = $"`{tableName.Replace("`", "``")}`";+ var createTableSql = $"CREATE TABLE IF NOT EXISTS {quotedTableName} ( Id INTEGER PRIMARY KEY AUTOINCREMENT, {string.Join(", ", columnDefs)} );";
// Create index for each column
- var indexSql = sanitizedColumns.Select(col => $"CREATE INDEX IF NOT EXISTS idx_{tableName}_{col} ON {tableName} (`{col}`);");+ var indexSql = sanitizedColumns.Select(col => $"CREATE INDEX IF NOT EXISTS `idx_{tableName}_{col}` ON {quotedTableName} (`{col}`);");
return createTableSql + "\n" + string.Join("\n", indexSql);
}
[To ensure code accuracy, apply this suggestion manually]
Suggestion importance[1-10]: 10
__
Why: This suggestion correctly identifies a critical SQL injection vulnerability in the CREATE TABLE and CREATE INDEX statements and provides a comprehensive fix that sanitizes the tableName input, significantly improving security.
High
High-level
Avoid indexing every single column
Avoid creating a database index for every column from the Excel sheet, as this harms write performance and increases storage. Instead, do not create indexes by default or use a more selective strategy.
varindexSql=sanitizedColumns.Select(col =>$"CREATE INDEX IF NOT EXISTS idx_{tableName}_{col} ON {tableName} (`{col}`);");returncreateTableSql+"\n"+string.Join("\n",indexSql);
Solution Walkthrough:
Before:
functionCreateDBTableSqlString(tableName,headerColumns, ...){// ... logic to create table ...varcreateTableSql=$"CREATE TABLE ...";// Create an index for EVERY columnvarindexSql=headerColumns.Select(col =>$"CREATE INDEX ON {tableName} (`{col}`);");returncreateTableSql+"\n"+string.Join("\n",indexSql);}
After:
functionCreateDBTableSqlString(tableName,headerColumns, ...){// ... logic to create table ...varcreateTableSql=$"CREATE TABLE ...";// Do not create indexes by default.// Indexing should be an optional, more targeted feature.// For example, only index columns specified by the user// or those with high cardinality.returncreateTableSql;}
Suggestion importance[1-10]: 9
__
Why: This suggestion correctly identifies a significant performance and design flaw, as indexing every column negatively impacts write performance and storage, which is a poor default behavior.
High
Process the Excel sheet only once
Combine the two separate passes over the Excel data—one for analysis (CollectColumnDistinctValues) and one for data insertion (ParseSheetData)—into a single pass to improve performance.
functionSqlCreateTableFn(sheet){// First pass: Analyze columnsvarcolumnAnalyses=CollectColumnDistinctValues(sheet);varinferredTypes=InferColumnTypes(columnAnalyses);CreateDBTableSqlString(...,inferredTypes);// ... create table ...}functionSqlInsertDataFn(sheet){// Second pass: Generate INSERT statementsvardataSql=ParseSheetData(sheet);// ... insert data ...}
After:
functionProcessSheet(sheet){// Single pass over the sheetvarcolumnAnalyses=new ...;varinsertValues=newStringBuilder();for each rowin sheet {// 1. Analyze cell types and update columnAnalyses// 2. Format cell values and append to insertValues}varinferredTypes=InferColumnTypes(columnAnalyses);CreateDBTableSqlString(...,inferredTypes);// ... create table ...// ... use insertValues to insert data ...}
Suggestion importance[1-10]: 8
__
Why: This is a valid and important performance optimization, as reading the Excel file twice is inefficient for large datasets; combining the analysis and data preparation into a single pass would significantly improve performance.
Medium
Possible issue
Avoid potential null reference exception
In GetCellValueAndType, store the result of cell.StringCellValue?.Trim() in a variable to avoid a potential NullReferenceException and redundant calls.
Why: This suggestion correctly identifies a potential NullReferenceException if cell.StringCellValue is null and provides a robust fix, preventing a runtime crash.
Medium
General
Format numbers with invariant culture
In GetCellValueAndType, use CultureInfo.InvariantCulture when converting numeric cell values to strings to avoid issues with locale-specific decimal separators.
Why: This is a valuable suggestion that prevents potential SQL syntax errors by ensuring numeric values are formatted consistently, regardless of the system's locale, which improves the robustness of the data import logic.
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PR Type
Enhancement
Description
Implement intelligent column type inference from Excel data
Add column analysis with distinct values and type statistics
Generate SQLite indexes for all table columns
Refactor cell formatting logic for improved maintainability
Diagram Walkthrough
File Walkthrough
ColumnAnalysis.cs
New ColumnAnalysis model for type inferencesrc/Plugins/BotSharp.Plugin.ExcelHandler/Models/ColumnAnalysis.cs
SqliteService.cs
Implement type inference and indexing for SQLitesrc/Plugins/BotSharp.Plugin.ExcelHandler/Services/SqliteService.cs
CollectColumnDistinctValuesmethod to analyze column data typesand collect statistics
InferColumnTypesmethod to determine optimal SQLite columntypes based on data analysis
GetCellValueAndTypehelper to detect cell types (NULL, NUMERIC,DATE, BOOLEAN, TEXT)
FormatCellForSqlmethod to format cell values for SQL insertionwith proper type handling
IsBooleanStringandIsIntegerhelper methods for type detectionGenerateColumnAnalysisSummarymethod to create human-readableanalysis reports
ParseSheetDatato use newFormatCellForSqlmethod, removinginline switch statement
CreateDBTableSqlStringto generate CREATE INDEX statements forall columns
SqlCreateTableFnto collect and log column analysis beforetable creation