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| author | Petr Svenda | 2020-10-18 11:35:03 +0200 |
|---|---|---|
| committer | GitHub | 2020-10-18 11:35:03 +0200 |
| commit | 7ed51240bd5e5e56a5847df28c8a1a9708307315 (patch) | |
| tree | 64b21004f61d219d0d4e88a9d59ae8d0d17a47fe | |
| parent | f15cbda18abeb174e565e996992a24c9507093f0 (diff) | |
| download | sec-certs-7ed51240bd5e5e56a5847df28c8a1a9708307315.tar.gz sec-certs-7ed51240bd5e5e56a5847df28c8a1a9708307315.tar.zst sec-certs-7ed51240bd5e5e56a5847df28c8a1a9708307315.zip | |
updated steps of usage
| -rw-r--r-- | README.md | 16 |
1 files changed, 10 insertions, 6 deletions
@@ -5,13 +5,17 @@ Analyzer of security certificates (Common Criteria, NIST FIPS140-2...) ## Usage Steps: - 1. Run `search_certificate.py` to generate download scripts (download_cc_web.bat, download_cc_web.sh) + 1. Run `process_certificates.py` to generate download scripts (download_cc_web.bat) 2. Run `download_cc_web.bat` to download important files from Common Criteria website (requires `curl` installed) - 3. Run `search_certificate.py` to generate download scripts for separate pdf files with certificates (`download_active_certs.bat`...) - 4. Place all dowload scripts into folder on disk with at least 5GB free space (yes, there are A LOT of certificates) and run them - 5. Run `search_certificate.py` to process CSV, HTML and PDF files. Extracted information is stored in *.json files. The consolidated info is in `certificate_data_complete.json` - 6. Run `search_certificate.py` to analyze information extracted to `certificate_data_complete.json`. Information like graph of certificates dependency is produced - + 3. Run `process_certificates.py` to generate download scripts for separate pdf files with certificates (`download_active_certs.bat`, `download_active_updates.bat`...) + 4. Place all download scripts into folder on disk with at least 5GB free space (yes, there are A LOT of certificates) and run them, wait until download and text extraction is completed + 5. Edit process_certificates.py, create new profile (paths_xxx) with correct paths pointing to the place where you dowloaded certificates, set paths_used = paths_xxx variable to your (see paths_20200904 dict for example). Intermediate files generated during the processing will be created inside `current_path/results_yyy` folder where yyy is value set by you at `paths_xxx['id']`. (DEBUG, remove later) + 6. Run `process_certificates.py` to process CSV, HTML and PDF files. Extracted information is stored in *.json files. `do_extraction` and `do_pairing` variables shall be True to execute this (time consuming) step. Set `do_extraction = False` and `do_pairing = False` to skip processing and read already computed information from `certificate_data_complete.json`. + 7. Optional: if info extracted from protection profiles is available, copy `pp_data_complete_processed.json` file into folder with results generated + 8. Run `process_certificates.py` with `do_processing = True` to run various heuristics which will create post-processed section `processed` for every certificate (results are stored in `certificate_data_complete_processed.json`). + 9. Run `process_certificates.py` with `do_analysis = True` to perform analysis of certificates (various graphs, statistics...). If `do_analysis_filtered = True` then same analysis for subsets of certificates is performed. + 10. Open, look and enjoy graphs like `num_certs_in_years.png` or `num_certs_eal_in_years.png`. For `certid_graph.dot.pdf` and other large graphs use Chrome to display as Adobe Acrobat Reader will fail to show whole graph. + ## Downloading again failes which failed to download properly Steps: |