A gov.np HTTP probe ran 66 minutes over 25,916 host and port pairs, then lost every
row: a captured response body carried a NUL byte, postgres refuses NUL in text and in
json alike, and the failing flush rolled back the whole stage transaction. Recording
that failure then failed too — psycopg puts the offending parameters in its error
message, so the NUL travelled into `scan_activities.error` and took the failure path
down with it, leaving the activity RUNNING and the scan unable to finalize.
`shared/utils/text.py` is now the one place that names what postgres will not store.
`strip_nul` runs through every string, list and dict a tool record yields, applied in
`tools/runner/fieldmap.py` so every tool that maps a record is covered rather than
httpx alone. `strip_control` replaces the two identical local regexes in the nuclei
parser and the template indexer, and now also guards the activity log, the activity
timeline and the command recorder — the three places that write a tool's own words.
The HTTP probe's batch flush runs in a savepoint: a row postgres refuses costs that
row, retried one at a time, and the count comes back as a PARTIAL stage naming how
many responses could not be stored. Recording a stage failure is wrapped too, so a
second error while writing the first can never leave a scan running forever.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01DPueZXQMbjLXMokXeA8LFP
- Implemented TargetEnrichmentStage for enriching targets with DNS, WHOIS, and BGP context.
- Added VhostStage for virtual host discovery using host-header fuzzing.
- Introduced WafDetectStage for fingerprinting web application firewalls.
- Created configuration files for each new stage with relevant parameters.
- Updated Dockerfile to copy stages instead of engines.
- Enhanced existing tools and services for better integration with new stages.
- Refactored task management in Celery to accommodate new stages and improve error handling.
Every scan now runs a discovery phase, gated per seed type:
- seed_resolution: expand ip / cidr / asn seeds into IpAddress assets
(stdlib ipaddress, even-stride sampling + rfc1918 skip on big ranges)
- reverse_dns: dnsx -ptr over discovered IPs
- ip_enrichment: asn / org / country from cached bgp + whois
- target_enrichment: consolidate cached whois/dns/bgp, refresh on miss/stale
The engine framework grows a phase axis (discovery/expansion/depth) and
per-stage applies_to gating so a stage skips cleanly when it doesn't apply
to the seed; subdomain discovery is retagged as expansion. Adds the
IpAddress model + migration.
- Added new types and interfaces for scan scheduling in the frontend.
- Created a new Svelte page for managing scheduled scans, including listing, creating, editing, and deleting schedules.
- Implemented backend models and services for scan schedules, including handling different schedule types (one-off, interval, daily, cron).
- Introduced a Celery task to manage the execution of scheduled scans based on their defined timing.
- Enhanced notification system to include alerts for newly discovered subdomains during scans.
- Added utility functions for handling time zones and scheduling logic.
- Updated the default route for automation to redirect to engines instead of scans.
- Removed the scans page and replaced it with a new scans overview page that lists scan history for projects.
- Introduced a detailed scan view page to display individual scan results and subdomain discoveries.
- Added new enums for scan statuses and subdomain sources to improve code clarity and maintainability.
- Implemented a new scan task in Celery to handle scan execution and logging.
- Enhanced the database models for scans and subdomains to support new features and improve data integrity.
- Updated the worker Dockerfile to include necessary scanning tools and dependencies.
- Added utility functions for domain matching and pattern compilation to streamline scan operations.
- Added `clean_name` function to `validation.py` for name validation with max length.
- Simplified docstrings in `dnsx` client, parser, and service files for clarity.
- Enhanced error handling in `ViewDNSService` to prevent disabling keys on rate limits.
- Improved WHOIS service to handle concurrent inserts gracefully with integrity checks.
- Updated `Settings` class in worker config to inherit from `BaseAppSettings`.
- Added new dependencies in `pyproject.toml` for `apprise` and `cryptography`.
WHOIS/DNS correlation was grouping unrelated targets on low-signal keys.
Add centralized privacy-redaction and shared-infrastructure detection,
drop country from auto-correlation, and bound every correlation query.
Backend:
- shared/utils/privacy.py: detect privacy-proxy/redacted registrant names
and emails (Withheld for Privacy, Domains By Proxy, WhoisGuard, GDPR
masked, etc.) so they never become correlation keys
- shared/utils/infra.py: detect shared/managed DNS (Cloudflare, Route 53,
GoDaddy, ...) so targets are not linked merely by DNS provider
- wire redaction into WHOIS entity extraction; guard correlation queries
defensively so legacy redacted rows do not correlate
- drop country from get_correlations_for_target (links whole regions)
- filter shared nameservers out of WHOIS nameserver correlation
- bound all WHOIS/DNS correlation queries (limit + distinct)
- exclude CDN-fronted IPs and shared nameservers from DNS correlation
- normalize country code casing at storage to fix missed matches
- return accurate cache-hit provenance from WhoisService.lookup
- reuse service finders from correlation API endpoints (DRY)
Frontend:
- remove country as a correlation type across types, API client, and the
related/lookup/overview WHOIS components (still shown as a record field)
- Added models for WHOIS responses including WhoisDomainResponse, WhoisIPResponse, and WhoisASNResponse.
- Created a parser for WHOIS data to convert raw responses into structured models.
- Developed an RDAPProvider class to handle RDAP lookups using the whoisit library.
- Implemented a WhoisService class for performing WHOIS lookups with optional database caching.
- Added methods for finding correlations between WHOIS records based on registrant, registrar, network, country, and nameservers.
- Updated Dockerfile to include tools directory and added rengine-tools dependency in pyproject.toml.
