Name CPE-derived technologies by product and retain the CPE

[liquidsec]

shodan_idb, shodan_enterprise and censys_ip emit raw CPE strings as the technology name, e.g. cpe:/a:cloudflare:cloudflare or cpe:2.3:a:apache:tomcat:9.0.50:*:*:*:*:*:*:*. These don't match how any other module names technologies, so they can't be correlated or filtered. They also never trigger technology-driven modules: trajan matches jenkins/artifactory, and gitlab_onprem matches names starting with gitlab.

Changes

• New cpe_product() helper that returns the product name from a CPE 2.2 URI or 2.3 formatted string (lowercased; None for */- or non-CPE input; handles 2.3's escaped colons).
• TECHNOLOGY events get an optional cpe field.
• shodan_idb: cpe:/a:jquery:jquery:3.5.1 becomes technology: jquery, cpe: cpe:/a:jquery:jquery:3.5.1.
• shodan_enterprise: previously emitted each technology up to three times (from cpe, cpe23 and product). It now uses the CPE product names (preferring cpe23), and falls back to Shodan's product field only when a service has no CPE.
• censys_ip: uses the CPE product name, falling back to product as before.
• shodan_enterprise no longer passes a port field on TECHNOLOGY events. It wasn't in the event schema, so it was already being dropped.

Behavior change
Technology names from these modules change format, e.g. cpe:/a:microsoft:internet_information_services becomes internet_information_services. Anything filtering on the old CPE strings should use the new cpe field instead.

Tests

• New test_cpe_product.
• shodan_idb, shodan_enterprise and censys_ip tests updated to expect product names and the retained CPE, and shodan_enterprise checks that no technology name starts with cpe:.

[codecov]

Codecov Report

❌ Patch coverage is 95.55556% with 2 lines in your changes missing coverage. Please review.
✅ Project coverage is 91%. Comparing base (484cfb6) to head (f527d67).

Files with missing lines	Patch %	Lines
bbot/modules/shodan_idb.py	50%	2 Missing ⚠️

Additional details and impacted files

@@          Coverage Diff          @@
##             dev   #3535   +/-   ##
=====================================
+ Coverage     91%     91%   +1%     
=====================================
  Files        463     463           
  Lines      49758   49791   +33     
=====================================
+ Hits       44890   44929   +39     
+ Misses      4868    4862    -6     

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[github-actions]

📊 Performance Benchmark Report

Comparing dev (baseline) vs technology-cpe-names (current)

📈 Detailed Results (All Benchmarks)

📋 Complete results for all benchmarks - includes both significant and insignificant changes

🧪 Test Name	📏 Base	📏 Current	📈 Change	🎯 Status
Bloom Filter Dns Mutation Tracking Performance	3.81ms	3.83ms	+0.3% ⚪	✅
Bloom Filter Large Scale Dns Brute Force	15.35ms	15.87ms	+3.4% ⚪	✅
Large Closest Match Lookup	357.84ms	363.37ms	+1.5% ⚪	✅
Realistic Closest Match Workload	201.70ms	195.26ms	-3.2% ⚪	✅
Event Memory Medium Scan	1402 B/event	1408 B/event	+0.4% ⚪	✅
Event Memory Large Scan	1527 B/event	1527 B/event	+0.0% ⚪	✅
Event Validation Full Scan Startup Small Batch	436.44ms	436.35ms	-0.0% ⚪	✅
Event Validation Full Scan Startup Large Batch	581.33ms	581.44ms	+0.0% ⚪	✅
Make Event Autodetection Small	27.72ms	27.57ms	-0.6% ⚪	✅
Make Event Autodetection Large	278.08ms	278.27ms	+0.1% ⚪	✅
Make Event Explicit Types	12.08ms	12.19ms	+0.9% ⚪	✅
Excavate Single Thread Small	4.419s	4.381s	-0.9% ⚪	✅
Excavate Single Thread Large	10.910s	10.700s	-1.9% ⚪	✅
Excavate Parallel Tasks Small	4.641s	4.629s	-0.3% ⚪	✅
Excavate Parallel Tasks Large	7.426s	6.980s	-6.0% ⚪	✅
Intercept Throughput Small	921.06ms	933.85ms	+1.4% ⚪	✅
Intercept Throughput Medium	913.04ms	923.76ms	+1.2% ⚪	✅
Dns Throughput Quiet	2.850s	2.875s	+0.8% ⚪	✅
Dns Throughput Loaded	1.918s	1.906s	-0.6% ⚪	✅
Dns Throughput Inherited	2.464s	2.658s	+7.9% ⚪	✅
Is Ip Performance	2.34ms	2.34ms	-0.2% ⚪	✅
Make Ip Type Performance	268.77µs	245.74µs	-8.6% ⚪	✅
Mixed Ip Operations	2.43ms	2.46ms	+1.4% ⚪	✅
Memory Use Web Crawl	1.2 MB	1.2 MB	+0.0% ⚪	✅
Memory Use Subdomain Enum	28.3 MB	28.3 MB	+0.0% ⚪	✅
Memory Use Deep Chain	5.0 MB	5.0 MB	+0.0% ⚪	✅
Memory Use Parallel Chains	12.9 MB	14.4 MB	+11.7% 🟡🟡	⚠️
Scan Throughput 100	3.216s	3.051s	-5.1% ⚪	✅
Scan Throughput 1000	23.305s	22.214s	-4.7% ⚪	✅
Typical Queue Shuffle	5.52µs	5.58µs	+1.1% ⚪	✅
Priority Queue Shuffle	25.80µs	26.02µs	+0.8% ⚪	✅

🎯 Performance Summary

! 1 regression ⚠️
  30 unchanged ✅

🔍 Significant Changes (>10%)

• Memory Use Parallel Chains: 11.7% 🐌 more memory

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🐍 Python Version 3.11.17