One list. Deduplicated. Ranked by what's actually exploitable.
Every finding from every scanner, in one place — deduplicated, correlated, and ranked by reachability and proof of exploit. So your team fixes the ten findings that matter before the thousand that don't.
Ten thousand findings, no priority.
Severity alone doesn't tell you what to fix first — a “critical” in code that never runs matters less than a “high” an attacker can reach today. BreachLens ranks by reachability and proof, not the CVSS number in isolation.
Every tier, one queue
Findings from code, dependencies, containers, cloud, identities, running apps, and AI land in a single view.
Correlate and collapse
The same issue seen by three scanners becomes one finding; related findings correlate into attack paths.
Exploitable first
Reachability and proof of exploit float the findings an attacker could actually use to the top of the list.
Straight to a pull request
For the findings that matter, AI drafts the patch and opens a PR or MR against the right repo. A human reviews and merges — nothing changes without approval.
A backlog your team can actually work through.
Unified findings
All tiers, one view.
- · Code, dependencies, containers, cloud, identities, apps, and AI — together.
- · Filter by asset, application, severity, or confidence.
- · The same issue from multiple scanners collapses to one entry.
Reachability ranking
Is the vulnerable code reached?
- · Traces the call path from entry point to the vulnerable function.
- · Across major language ecosystems.
- · De-prioritises what can't be reached, so real risk rises.
Proof of exploit first
CONFIRMED floats to the top.
- · Findings BreachLens actually reproduced are marked CONFIRMED.
- · They outrank a wall of unproven highs.
- · Each ships with a reproducible command you can run.
Risk acceptance
Decide, and record it.
- · Accept a finding with a reason instead of leaving it to rot.
- · Every acceptance is attributed and time-stamped.
- · An audit trail your assessors can follow.
Fixes, reviewed
Ranked backlog → pull request.
- · AI drafts the patch and opens a PR/MR against the right repo.
- · Bring your own model — Anthropic, OpenAI, Gemini, or fully local.
- · Nothing auto-merges; a human is always in the approval seat.
One platform, not an integration project
We run the scanners — you don't wire up ten.
- · BreachLens runs the scanner set itself, in a single deployment.
- · No separate point-tool licences to keep, no aggregation to build.
- · One data model, one queue, one place your team works.