WITONE: Innovate Securely

We attack it first.
Then we publish the misses.

Red teaming for AI systems that behaves like engineering, not theater: a versioned attack corpus, driven against your live stack, scored on detection and on the false blocks that break real users, then wired into CI so the score cannot quietly regress.

  • 135-case corpus: 92 attacks across 7 families, 43 benign controls
  • Runs against the scan layer and end to end through the gateway
  • False blocks scored separately: the number that breaks users
  • Priced as an assessment. Never metered, never per scan

/ How it works

A score you can re-run
is a score you can trust.

Drive the corpus

Injection, jailbreaks, exfiltration, encodings, secrets, and six-language multilingual attacks against your live deployment.

Score honestly

Detection, flag versus block, and false-block rate on benign traffic, with latency percentiles alongside.

Gate regressions

The corpus runs in CI with exit gates. A fix that costs you coverage fails the build before it costs you an incident.

Fix and re-run

Findings map to the layer that owns them: patterns, policy, or the authorization gate. Then the same corpus proves the fix.

/ Capabilities

Everything this layer holds.

A corpus, not a vibe

Versioned and fingerprinted. Every claim traces to a case ID, so two runs a year apart are actually comparable.

Two attack surfaces

Direct against the scanning layer, and end to end through the gateway, because the wiring between them is where real gaps hide.

False blocks are findings

A benign prompt that gets blocked sends a user to shadow AI. We measure that rate with the same rigor as detection.

Multilingual pressure

Attacks in Spanish, Portuguese, French, German, Chinese, and Arabic, because English-only regex is not a security model.

Misses are published

The report names the families where content inspection is structurally insufficient and prescribes the layer that closes them.

Reports you can paste

Customer-ready markdown with methodology, per-family results, and deltas against your previous run.

/ Numbers we can defend

Our own baseline,
misses included.

90.2%
detection, all families
measured
100%
direct injection family
measured
58.3%
exfiltration family. Yes, we print it
measured
7.0%
false-block on benign controls
measured

Corpus v1.0.0 baseline, August 2026, against our own live stack. The exfiltration number is the honest one: an instruction like forwarding invoices to an outside address is indistinguishable from legitimate finance work at the content layer. That gap is architectural, and it is exactly what the Agent Security layer's argument-level authorization exists to close. Vendors who do not publish a number like this have one anyway.

/ The difference

Assurance you rent
versus assurance you keep.

Where the market stops
Where this layer keeps going

Red teaming priced per agent, per scan, per month. Testing more costs more.

An assessment with a report and a re-runnable corpus. Testing thoroughly is the point, not a billable event.

A glossy score with no way to reproduce it.

A versioned corpus and runner your team can execute again after every change, with CI gates included.

Weak families are quietly averaged into a headline number.

Per-family results, printed, including the ones we lose. The fix is prescribed, then proven by the next run.

Findings die in a PDF.

Findings map to owners: a pattern gap, a policy change, or an authorization rule, each verifiable by re-run.

Detect.Respond.Automate.Predict.Defend.Operate.Detect.Respond.Automate.Predict.Defend.Operate.Detect.Respond.Automate.Predict.Defend.Operate.Detect.Respond.Automate.Predict.Defend.Operate.
Detect.Respond.Automate.Predict.Defend.Operate.Detect.Respond.Automate.Predict.Defend.Operate.Detect.Respond.Automate.Predict.Defend.Operate.Detect.Respond.Automate.Predict.Defend.Operate.
WIT OS

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