Module: PWN::Reports::SAST
- Defined in:
- lib/pwn/reports/sast.rb
Overview
This plugin generates the Static Code Anti-Pattern Matching Analysis results within the root of a given source repo. Two files are created, a JSON file containing all of the SAST results and an HTML file which is essentially the UI for the JSON file.
Class Method Summary collapse
-
.authors ⇒ Object
- Author(s)
-
0day Inc.
-
.generate(opts = {}) ⇒ Object
- Supported Method Parameters
-
PWN::Reports::SAST.generate( dir_path: ‘optional - Directory path to save the report (defaults to .)’, results_hash: ‘optional - Hash containing the results of the SAST analysis (defaults to empty hash structure)’, report_name: ‘optional - Name of the report file (defaults to current directory name)’, ai_engine: ‘optional - AI engine to use for analysis (:grok, :ollama, or :openai)’, ai_model: ‘optionnal - AI Model to Use for Respective AI Engine (e.g., grok-4i-0709, chargpt-4o-latest, llama-3.1, etc.)’, ai_key: ‘optional - AI Key/Token for Respective AI Engine’, ai_fqdn: ‘optional - AI FQDN (Only Required for “ollama” AI Engine)’, ai_system_role_content: ‘optional - AI System Role Content (Defaults to “Confidence score of 0-10 this is vulnerable (0 being not vulnerable, moving upwards in confidence of exploitation). Provide additional context to assist penetration tester assessment.”)’, ai_temp: ‘optional - AI Temperature (Defaults to 0.1)’ ).
-
.help ⇒ Object
Display Usage for this Module.
Class Method Details
.authors ⇒ Object
- Author(s)
-
0day Inc. <[email protected]>
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# File 'lib/pwn/reports/sast.rb', line 513 public_class_method def self. "AUTHOR(S): 0day Inc. <[email protected]> " end |
.generate(opts = {}) ⇒ Object
- Supported Method Parameters
-
PWN::Reports::SAST.generate(
dir_path: 'optional - Directory path to save the report (defaults to .)', results_hash: 'optional - Hash containing the results of the SAST analysis (defaults to empty hash structure)', report_name: 'optional - Name of the report file (defaults to current directory name)', ai_engine: 'optional - AI engine to use for analysis (:grok, :ollama, or :openai)', ai_model: 'optionnal - AI Model to Use for Respective AI Engine (e.g., grok-4i-0709, chargpt-4o-latest, llama-3.1, etc.)', ai_key: 'optional - AI Key/Token for Respective AI Engine', ai_fqdn: 'optional - AI FQDN (Only Required for "ollama" AI Engine)', ai_system_role_content: 'optional - AI System Role Content (Defaults to "Confidence score of 0-10 this is vulnerable (0 being not vulnerable, moving upwards in confidence of exploitation). Provide additional context to assist penetration tester assessment.")', ai_temp: 'optional - AI Temperature (Defaults to 0.1)'
)
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# File 'lib/pwn/reports/sast.rb', line 26 public_class_method def self.generate(opts = {}) dir_path = opts[:dir_path] ||= '.' results_hash = opts[:results_hash] ||= { report_name: HTMLEntities.new.encode(report_name.to_s.scrub.strip.chomp), data: [] } report_name = opts[:report_name] ||= File.basename(Dir.pwd) ai_engine = opts[:ai_engine] if ai_engine ai_engine = ai_engine.to_s.to_sym valid_ai_engines = %i[grok ollama openai] raise "ERROR: Invalid AI Engine. Valid options are: #{valid_ai_engines.join(', ')}" unless valid_ai_engines.include?(ai_engine) ai_fqdn = opts[:ai_fqdn] raise 'ERROR: FQDN for Ollama AI engine is required.' if ai_engine == :ollama && ai_fqdn.nil? ai_model = opts[:ai_model] raise 'ERROR: AI Model is required for AI engine ollama.' if ai_engine == :ollama && ai_model.nil? ai_key = opts[:ai_key] ||= PWN::Plugins::AuthenticationHelper.mask_password(prompt: "#{ai_engine} Token") ai_system_role_content = opts[:ai_system_role_content] ||= 'Confidence score of 0-10 this is vulnerable (0 being not vulnerable, moving upwards in confidence of exploitation). Provide additional context to assist penetration tester assessment.' ai_temp = opts[:ai_temp] ||= 0.1 puts "Analyzing source code using AI engine: #{ai_engine}\nModel: #{ai_model}\nSystem Role Content: #{ai_system_role_content}\nTemperature: #{ai_temp}" end # Calculate percentage of AI analysis based on the number of entries total_entries = results_hash[:data].sum { |entry| entry[:line_no_and_contents].size } puts "Total entries to analyze: #{total_entries}" if ai_engine percent_complete = 0.0 entry_count = 0 spin = TTY::Spinner.new( '[:spinner] Report Generation Progress: :percent_complete :entry_count of :total_entries', format: :dots, hide_cursor: true ) spin.auto_spin results_hash[:data].each do |hash_line| hash_line[:line_no_and_contents].each do |src_detail| entry_count += 1 percent_complete = (entry_count.to_f / total_entries * 100).round(2) request = src_detail[:contents] response = nil line_no = src_detail[:line_no] = src_detail[:author].to_s.scrub.chomp.strip case ai_engine when :grok response = PWN::AI::Grok.chat( token: ai_key, model: ai_model, system_role_content: ai_system_role_content, temp: ai_temp, request: request.chomp, spinner: false ) when :ollama response = PWN::AI::Ollama.chat( fqdn: ai_fqdn, token: ai_key, model: ai_model, system_role_content: ai_system_role_content, temp: ai_temp, request: request.chomp, spinner: false ) when :openai response = PWN::AI::OpenAI.chat( token: ai_key, model: ai_model, system_role_content: ai_system_role_content, temp: ai_temp, request: request.chomp, spinner: false ) end ai_analysis = nil if response.is_a?(Hash) ai_analysis = response[:choices].last[:text] if response[:choices].last.keys.include?(:text) ai_analysis = response[:choices].last[:content] if response[:choices].last.keys.include?(:content) # puts "AI Analysis Progress: #{percent_complete}% Line: #{line_no} | Author: #{author} | AI Analysis: #{ai_analysis}\n\n\n" if ai_analysis end src_detail[:ai_analysis] = ai_analysis.to_s.scrub.chomp.strip spin.update( percent_complete: "#{percent_complete}%", entry_count: entry_count, total_entries: total_entries ) end end # JSON object Completion # File.open("#{dir_path}/pwn_scan_git_source.json", 'w') do |f| # f.print(results_hash.to_json) # end File.write( "#{dir_path}/#{report_name}.json", JSON.pretty_generate(results_hash) ) column_names = [ 'Timestamp', 'Test Case / Security References', 'Path', 'Line# | Source | AI Analysis | Author', 'Raw Content', 'Test Case' ] driver_src_uri = 'https://github.com/0dayinc/pwn/blob/master/bin/pwn_sast' html_report = %(#{PWN::Reports::HTMLHeader.generate(column_names: column_names, driver_src_uri: driver_src_uri)} $(document).ready(function() { var table = $('#pwn_results').DataTable( { "order": [[2, 'asc']], "scrollY": scrollYHeight + "px", "scrollCollapse": true, "searchHighlight": true, "paging": true, "lengthMenu": [25, 50, 100, 250, 500, 1000, 2500, 5000], "drawCallback": function () { var api = this.api(); // Redo the row counters api.column(0, {page: 'current'} ).nodes().each(function(cell, i) { cell.innerHTML = i + 1; }); // Jump to top of scroll body when utilizing pagination var info = api.page.info(); if (info.start !== oldStart) { $('.dt-scroll-body').animate({scrollTop: 0}, 500); oldStart = info.start; } }, "ajax": "#{report_name}.json", "deferRender": false, "layout": { }, "autoWidth": false, "columns": [ { "data": null }, { "data": "timestamp", "render": function (data, type, row, meta) { if (type === 'display') { timestamp = htmlEntityEncode(data); return '<table class="squish"><tr><td style="width:70px;" align="left">' + timestamp + '</td></tr></table>'; } else { return data; } } }, { "data": "security_references", "render": function (data, type, row, meta) { if (type === 'display') { var sast_dirname = data['sast_module'].split('::')[0].toLowerCase() + '/' + data['sast_module'].split('::')[1].toLowerCase(); var sast_module = data['sast_module'].split('::')[2]; var sast_test_case = sast_module.replace(/\\.?([A-Z])/g, function (x,y){ if (sast_module.match(/\\.?([A-Z][a-z])/g) ) { return "_" + y.toLowerCase(); } else { return y.toLowerCase(); } }).replace(/^_/g, ""); return '<table class="squish"><tr><td style="width:125px;" align="left"><a href="https://github.com/0dayinc/pwn/tree/master/lib/' + htmlEntityEncode(sast_dirname) + '/' + htmlEntityEncode(sast_test_case) + '.rb" target="_blank">' + htmlEntityEncode(data['sast_module'].split("::")[2]) + '</a><br /><br /><a href="' + htmlEntityEncode(data['nist_800_53_uri']) + '" target="_blank">NIST 800-53: ' + htmlEntityEncode(data['section']) + '</a><br /><br /><a href="' + htmlEntityEncode(data['cwe_uri']) + '" target="_blank">CWE:' + htmlEntityEncode(data['cwe_id']) + '</a></td></tr></table>'; } else { return data['sast_module'].split("::")[2] + ' | NIST 800-53: ' + data['section'] + ' | CWE:' + data['cwe_id']; } } }, { "data": "filename", "render": function (data, type, row, meta) { if (type === 'display') { line_entry_uri = htmlEntityEncode( data['git_repo_root_uri'] + '/' + data['entry'] ); file = htmlEntityEncode(data['entry']); return '<table class="squish"><tr><td style="width:200px;" align="left"><a href="' + line_entry_uri + '" target="_blank">' + file + '</a></td></tr></table>'; } else { return data['entry']; } } }, { "data": "line_no_and_contents", "render": function (data, type, row, meta) { if (type === 'display') { var pwn_rows = '<table class="multi_line_select squish" style="width: 725px"><tbody>'; for (var i = 0; i < data.length; i++) { var tr_class; if (i % 2 == 0) { tr_class = "odd"; } else { tr_class = "even"; } var filename_link = row.filename; var author_and_email_arr = data[i]['author'].split(" "); var email = author_and_email_arr[author_and_email_arr.length - 1]; var email_user_arr = email.split("@"); var assigned_to = email_user_arr[0].replace("<", ""); var uri = '#uri'; var canned_email_results = 'Timestamp: ' + row.timestamp + '\\n' + 'Source Code File Impacted: ' + $("<div/>").html(filename_link).text() + '\\n\\n' + 'Source Code in Question:\\n\\n' + data[i]['line_no'] + ': ' + $("<div/>").html(data[i]['contents'].replace(/\\s{2,}/g, " ")).text() + '\\n\\n'; var canned_email = email.replace("<", "").replace(">", "") + '?subject=Potential%20Bug%20within%20Source%20File:%20'+ encodeURIComponent(row.filename) +'&body=Greetings,%0A%0AThe%20following%20information%20likely%20represents%20a%20bug%20discovered%20through%20automated%20security%20testing%20initiatives:%0A%0A' + encodeURIComponent(canned_email_results) + 'Is%20this%20something%20that%20can%20be%20addressed%20immediately%20or%20would%20filing%20a%20bug%20be%20more%20appropriate?%20%20Please%20let%20us%20know%20at%20your%20earliest%20convenience%20to%20ensure%20we%20can%20meet%20security%20expectations%20for%20this%20release.%20%20Thanks%20and%20have%20a%20great%20day!'; domain = line_entry_uri.replace('http://','').replace('https://','').split(/[/?#]/)[0]; if (domain.includes('stash') || domain.includes('bitbucket') || domain.includes('gerrit')) { to_line_number = line_entry_uri + '#' + data[i]['line_no']; } else { // e.g. GitHub, GitLab, etc. to_line_number = line_entry_uri + '#L' + data[i]['line_no']; } pwn_rows = pwn_rows.concat('<tr class="' + tr_class + '"><td style="width:50px" align="left"><a href="' + htmlEntityEncode(to_line_number) + '" target="_blank">' + htmlEntityEncode(data[i]['line_no']) + '</a>: </td><td style="width:300px" align="left">' + htmlEntityEncode(data[i]['contents']) + '</td><td style="width:200px" align=:left">' + htmlEntityEncode(data[i]['ai_analysis']) + '</td><td style="width:175px" align="right"><a href="mailto:' + canned_email + '">' + htmlEntityEncode(data[i]['author']) + '</a></td></tr>'); } pwn_rows = pwn_rows.concat('</tbody></table>'); return pwn_rows; } else { var lines = []; for (var i = 0; i < data.length; i++) { lines.push(data[i]['line_no'] + ': ' + data[i]['contents'] + ' | AI: ' + data[i]['ai_analysis'] + ' | By: ' + data[i]['author']); } return lines.join('\\n'); } } }, { "data": "raw_content", "render": function (data, type, row, meta) { if (type === 'display') { raw_content = htmlEntityEncode(data); return '<table class="squish"><tr><td style="width:300px;" align="left">' + raw_content + '</td></tr></table>'; } else { return data; } } }, { "data": "test_case_filter", "render": function (data, type, row, meta) { if (type === 'display') { test_case_filter = htmlEntityEncode(data); return '<table class="squish"><tr><td style="width:300px;" align="left">' + test_case_filter + '</td></tr></table>'; } else { return data; } } } ], "initComplete": function(settings, json) { $('#report_name').text(json.report_name); var raw_content_column = 5; var test_case_filter_column = 6; table.column(raw_content_column).visible(false); table.column(test_case_filter_column).visible(false); // Add export buttons after initialization new $.fn.dataTable.Buttons(table, { buttons: [ { text: 'Select / Deselect All Lines', action: function () { select_deselect_all(); } }, { text: 'Export to JSON', action: function () { export_json(table); } }, { text: 'Export to XLSX', action: function () { export_xlsx_or_pdf('xlsx'); } }, { text: 'Export to PDF', action: function () { export_xlsx_or_pdf('pdf'); } } ] }); table.buttons().container().appendTo('#toggle_col_and_button_group'); // Update Smart Search Label with Example $('.dt-search label').text('Smart Search (e.g., "password !secure"):').css({'font-weight': 'bold', color: '#B40404'}); } }); function export_xlsx_or_pdf(type) { if ($('.multi_line_select tr.highlighted').length === 0 && !confirm('No lines selected. Export all records?')) { return; } getExportData(table).then(({data, report_name}) => { // Flatten data for export var flatData = []; data.forEach(function(row) { row.line_no_and_contents.forEach(function(line) { flatData.push({ timestamp: row.timestamp, test_case: row.security_references.sast_module.split('::')[2], nist_800_53_security_control: row.security_references.nist_800_53_uri, cwe: row.security_references.cwe_uri, nist_section: row.security_references.section, cwe_id: row.security_references.cwe_id, path: row.filename.entry, line_no: line.line_no, contents: line.contents, ai_analysis: line.ai_analysis, author: line.author }); }); }); var exportDate = new Date().toLocaleString(); var title = '~ pwn sast >>> ' + report_name + ' (Exported on ' + exportDate + ')'; if (type === 'xlsx') { const workbook = new ExcelJS.Workbook(); const worksheet = workbook.addWorksheet('PWN SAST Results'); // Add title row and merge worksheet.mergeCells('A1:I1'); const titleCell = worksheet.getCell('A1'); titleCell.value = title; titleCell.font = { size: 14, bold: true }; titleCell.alignment = { horizontal: 'center' }; // Add header row worksheet.addRow(['Timestamp', 'Test Case', 'NIST 800-53', 'CWE', 'Path', 'Line#', 'Content', 'AI Analysis', 'Author']); const headerRow = worksheet.getRow(2); headerRow.eachCell((cell) => { cell.font = { bold: true, color: { argb: 'FF000000' } }; cell.fill = { type: 'pattern', pattern: 'solid', fgColor: { argb: 'FF999999' } }; cell.alignment = { horizontal: 'center', wrapText: true }; }); // Add data rows with alternating fills and hyperlinks flatData.forEach((item, index) => { const row = worksheet.addRow([ item.timestamp, item.test_case, { text: item.nist_section, hyperlink: item.nist_800_53_security_control }, { text: item.cwe_id, hyperlink: item.cwe }, item.path, item.line_no, item.contents, item.ai_analysis, item.author ]); const fill = (index % 2 === 0) ? { type: 'pattern', pattern: 'solid', fgColor: { argb: 'FFDEDEDE' } } : { type: 'pattern', pattern: 'solid', fgColor: { argb: 'FFFFFFFF' } }; row.eachCell((cell) => { cell.fill = fill; cell.alignment = { wrapText: true, vertical: 'top', horizontal: 'left' }; }); }); // Set column widths (converted from pixels to character units approx.) const pixelWidthsInches = [1.0, 2.0, 4.5, 0.5, 2.5, 0.75, 3.5, 3.5, 2]; worksheet.columns = pixelWidthsInches.map(inches => { let width; width = inches / 0.077 return { width: width }; }); // Freeze header worksheet.views = [{ state: 'frozen', ySplit: 2 }]; // Generate and download the file workbook.xlsx.writeBuffer().then(buffer => { const blob = new Blob([buffer], { type: 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet' }); const url = URL.createObjectURL(blob); const a = document.createElement('a'); a.href = url; a.download = report_name + '.xlsx'; a.click(); URL.revokeObjectURL(url); }); } else if (type === 'pdf') { var docDefinition = { pageOrientation: 'landscape', pageSize: 'LETTER', pageMargins: [10, 10, 10, 10], header: { text: title, margin: [20, 10, 20, 0], fontSize: 12, bold: true, alignment: 'center' }, footer: function(currentPage, pageCount) { return { text: 'Page ' + currentPage.toString() + ' of ' + pageCount + ' | Exported on ' + exportDate, alignment: 'center', fontSize: 8, margin: [0, 0, 0, 10] }; }, content: [ { text: title, style: 'header' }, { table: { headerRows: 1, widths: [45, 40, 70, 30, 80, 30, 165, 165, 70], body: [ ['Timestamp', 'Test Case', 'NIST 800-53', 'CWE', 'Path', 'Line#', 'Content', 'AI Analysis', 'Author'], ...flatData.map(r => [ r.timestamp, r.test_case, { text: r.nist_section, link: r.nist_800_53_security_control, style: {decoration: 'underline'} }, { text: r.cwe_id, link: r.cwe, style: {decoration: 'underline'} }, r.path, r.line_no, r.contents, r.ai_analysis, r.author ]) ] }, layout: { hLineWidth: function(i, node) { return (i === 0 || i === node.table.body.length) ? 1 : 0.5; }, vLineWidth: function(i, node) { return 0.5; }, hLineColor: function(i, node) { return '#aaaaaa'; }, vLineColor: function(i, node) { return '#aaaaaa'; }, fillColor: function (rowIndex, node, columnIndex) { if (rowIndex === 0) { return '#999999'; // Dark header } return (rowIndex % 2 === 0) ? '#ffffff' : '#dedede'; // White even, gray odd }, paddingLeft: function(i, node) { return 4; }, paddingRight: function(i, node) { return 4; }, paddingTop: function(i, node) { return 2; }, paddingBottom: function(i, node) { return 2; } } } ], styles: { header: { fontSize: 12, bold: true, margin: [0, 0, 0, 10] } }, defaultStyle: { fontSize: 8, color: '#000000', columnGap: 20 } }; pdfMake.createPdf(docDefinition).download(report_name + '.pdf'); } }); } }); #{PWN::Reports::HTMLFooter.generate} ) File.open("#{dir_path}/#{report_name}.html", 'w') do |f| f.print(html_report) end rescue StandardError => e raise e ensure spin.stop unless spin.nil? end |
.help ⇒ Object
Display Usage for this Module
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# File 'lib/pwn/reports/sast.rb', line 521 public_class_method def self.help puts "USAGE: #{self}.generate( dir_path: dir_path, results_hash: results_hash ) #{self}.authors " end |