Give your pentesters a head start. Show them the cross-package paths first. Pre-engagement reachability scan, taint-path map, structured-trace findings as starter chains, post-engagement closure tracking — so your team spends the engagement on judgement, not enumeration.
Most two-week pentests start with five days of enumeration: build the dependency map, find the entry points, identify the sinks, hunt for the chains. That's where Safeguard's deterministic engine + Eagle ranking is already done.
A senior pentester spends days walking the call graph by hand — Burp, jadx, dependency-track, custom scripts. That work is reproducible by a deterministic engine, but it's still being done with caffeine and patience.
The really interesting bug is the one where the entry point is in your app and the sink is six packages deep in a third-party vendored fork. Without a pre-built taint graph, the tester won't walk that path in two weeks.
Asking an LLM to find vulnerabilities produces a list of suspicious patterns with no reachability evidence. The pentester ends up validating false positives instead of exploiting real ones.
The report ships. Two weeks later, half the findings have an open ticket somewhere, none of them are verified closed, and nobody remembers which fix shipped in which release. The remediation loop dies in committee.
Before the engagement starts, Safeguard runs a deterministic reachability scan + Eagle ranking against the in-scope codebase. The pentest team gets a taint-path map and ranked candidate chains before they open Burp.
During the engagement, every Griffin-confirmed candidate ships to the tester as a structured trace — hypothesis, cited path, disproof attempt, proposed exploit input. Testers spend their time validating chains, not constructing them from scratch.
Post-engagement, every finding gets a unique signed ID. When the engineering team merges a fix, the platform re-runs the reachability scan against the affected path and flips the finding to verified-closed. The remediation loop ends with evidence, not promises.
Read-only access granted. Pre-engagement reachability scan runs. Taint-path map and 47 starter chains produced.
Lead pentester reviews the candidate chain list, picks 12 to start with, flags 4 paths the engine missed for manual exploration.
Tester confirms 9 of 12 starter chains as exploitable, disproves 3. Engagement starts at confirmation, not at enumeration.
Tester explores the 4 manual paths and finds 2 zero-days that the engine's reachability model missed. Both fed back into platform training.
Findings exported as structured traces. Each carries a signed ID. Report ships to engineering on D10.
Engineering merges fixes; platform re-runs reachability per finding ID and flips status. By D28, 10 of 11 are verified-closed with evidence.
Every starter chain ships with the same structured contract. Testers stop reconstructing context and start exploiting.
Source → sink, every node version-pinned.
What the engine thinks this is, with prior-art links.
A payload that should reach the sink under current sanitisers.
Every refutation the platform tried and failed.
Burp request templates, sample auth, environment notes.
For closure-tracking after engineering ships the fix.
Pre-filled finding write-up; tester edits, doesn't author from scratch.
A three-person offensive-security practice integrated Safeguard's pre-engagement scan into their delivery pipeline. Pre-engagement reachability scans ran the weekend before kickoff; testers walked into Monday with ranked starter chains and a working taint map. Across six engagements over a quarter, the team logged 3x findings per day compared to their baseline, with client reports tighter and easier to defend in the read-out call. The platform's structured trace became the standard finding format the firm now ships in every report.
Book a working session and we'll run a pre-engagement scan against a sample codebase, hand you the structured starter chains, and walk through closure tracking.