Product Security
SecNode AI reasons like a product security engineer
Shift real security judgment left, not more alerts. SecNode AI reasons like a product security engineer: it reviews designs, thinks about code in context, and the web and API pentest agents confirm whether a finding is actually exploitable.
Product Security
From design review to exploit verification
The model understands the service, its data, and its reachability, so product teams get conclusions, not a wall of scanner output.
Design-time review
Threat modeling on architecture changes before they ship.
Context-aware analysis
Findings judged against how the service is actually reached.
Exploitability gating
The pentest agents confirm reachability, so only real issues become developer work.
New webhook endpoint lacks signature verification
API pentest agent forges a payload · state mutation confirmed
HMAC verification patch drafted with a test
Developer approves · finding closed in-flow
Illustrative · delivered inside the pull request
In the flow
Security that developers don't route around
Where they work
Findings and fixes arrive in the PR, not a separate portal.
Low false positives
Reachability filtering means fewer, truer findings.
Fix-first
Remediation drafted with the finding, ready to review.
Put senior-level security engineering on every system you own
See SecNode's agents run a live investigation against a real environment.