why cipher

Code ships at AI speed. So does the attack surface.

Coding agents ship more code in a week than most security teams can review in a quarter. What follows is our case: three claims, a conclusion, and the record they rest on.

Built by operators and AI researchers who ran security at scale.
claim 01· the pace

Code generation scaled super-linearly. Human reasoning about exploits did not.

code generated human-paced reasoning CIPHER · END-TO-END, AT THE SAME RATE
2023 →2026 →
claim 02· the terrain

Real exploits live between services, not inside them.

A refund endpoint that trusts a user ID. A session cache that keys across tenants. An auth service that issues tokens four services upstream. Separately, each is a design choice. Together, they form a business-logic exploit that chains from login to a refund on an account the attacker doesn't own.

Your best security reasoner would see it, given time to trace the chain across four repos, reason about the state machine, and validate exploitability. They don't have that time. Not for every PR. Not at AI-generated velocity. An LLM pointed at a diff reasons about the diff, not about the other three services the exploit lives in.

auth session ledger refund
one exploit · four servicesnothing "wrong" in any single file
claim 03· the method

Pattern matching finds code that looks wrong. Reasoning finds what an attacker can do.

A scanner matches the diff against known bad shapes and hands your team the maybes. Reasoning holds the whole system in view: what a change trusts, what trusts it, and whether a path runs from attacker input to real impact. Cipher does the second, then executes the chain to prove it.

pattern matching returns
hundreds of look-alikes · exploitability unknown
reasoning returns
auth session ledger refund ✓ PROVEN BY EXECUTION
one chain · demonstrated end to end
the conclusion

Security review has to reason. And it has to reason at the rate code ships.

That is Cipher: end-to-end reasoning on every change, across every service it touches. Everything it finds arrives proven, with the fix. The record below is how you check us.

in practice

Same Cipher. Different answer to the question you're actually asking.

security · ciso / security lead
what your team sees
critical · business-logic chain ✓ validated
auth session ledger refund

Expert-depth reasoning on the risk your engineers ship.

Scanner alerts drown the team in noise. The real exploits are chains nobody has expert-hours to trace.

Cipher reasons end-to-end across code, architecture, business logic, auth flows, and runtime. Every finding is a validated chain with demonstrated exploitability. Proof, not a pattern match. Your reviewers spend time on judgment instead of triage.

→ a business-logic chain, reasoned end-to-end
engineering · cto / vp eng
what your devs see

AI-assisted velocity. Exploits caught before merge, not after.

Devs generate a feature in hours. Reasoning about the chain it introduces takes a week. Either velocity or security.

Cipher reasons inline with the PR: same codebase, same commit, same window. Gate-latency stays constant while exploitability coverage scales to the code-gen rate. Engineers get a proposed fix, not a ticket in a different system.

→ an auth-logic flaw in a major identity platform
the record

Each claim, checked.

Public advisories in widely deployed software, and field reports from real engagements. If a claim above were wrong, this is where it would show.

checks claim 01
Continuous reasoning. Not point-in-time audits.
see the loop →
§checks claim 02
Whole attack chains. Not pattern alerts.
see a chain →
checks claim 03
Exploitability proven. Not flagged.
see the proof →
The ask

One repo. One target. One unattended review. Exploitable findings.

No slides, no sales pitch. You talk to a researcher who does this work. Point us at a system you own, even your hardest environment, and we hand back validated, exploitable findings, each one proven. If there's nothing worth your time, you'll know that too. Either way, you know where you stand.