Autonomous offensive security

Bad AI that breaks in first.

We train AI to be the worst thing that could happen to your company — then point it at you, with permission. Autonomous penetration testing and AI red teaming that proves every exploit, and a 24/7 defense agent that never takes the night off.

Proof or it didn't happen24/7 attack & defense< 5 days to first findings
3h 12mmedian time from kickoff to first proven critical
11,400+exploitable findings proven for customers this year
94%of alerts closed by Nightwatch with written evidence, no human needed
4m 38smedian time to contain a confirmed incident

Trusted by security teams at

  • A top-10 U.S. bank
  • A Fortune 100 retailer
  • A global payments network
  • A top-3 cloud provider
  • Two national grid operators
  • A leading GPU manufacturer
§01 — Two products, one adversary

Attack all day.
Defend all night.

Most security programs test once a year and watch with half a team at 3 a.m. We built both halves with the same offensive models: one that hunts for the way in, one that already knows what the hunt looks like from the inside.

Offense · Rogue

Rogue

A swarm of autonomous attack agents that recon, exploit and chain weaknesses across your perimeter, web apps, APIs, cloud identity and AI agents — continuously, not once a year.

  • 01Proof of exploit and a replay script for every finding
  • 02Multi-step attack chains, not isolated CVEs
  • 03Automatic retest the moment a fix ships
  • 04Covers LLM apps and agents: injection, tool abuse, exfiltration
Explore Rogue →
Defense · Nightwatch

Nightwatch

An always-on AI incident agent that investigates every alert like a senior analyst, contains confirmed threats with pre-approved actions and runs the incident until a human takes the wheel.

  • 01Every alert investigated — not sampled, not suppressed
  • 02Contain in minutes: isolate host, revoke token, disable user
  • 03Live incident timeline, bridge notes and exec brief
  • 04Drafts SEC, NIS2 and DORA notifications on the clock
Explore Nightwatch →
The BadAI loop Rogue attacks your environment, proves an exploit, Nightwatch checks whether it was detected, the gap becomes a new detection and a fix, and Rogue retests. 01 · ATTACK 02 · PROVE 03 · DETECT 04 · HARDEN ROGUE EXPLOIT NIGHTWATCH NEW RULE 24/7 every proven attack becomes a detection and a verified fix
§02 — The loop

Every attack we land makes you harder to hit.

  1. Rogue attacks

    Agents work your real attack surface inside a signed scope, around the clock.

  2. It proves impact

    No theoretical risk scores. A chain either reaches the crown jewels or it doesn't.

  3. Nightwatch checks itself

    Did anything fire? Every undetected step becomes a drafted detection rule for your SIEM.

  4. You harden, Rogue retests

    Fix ships, Rogue replays the chain within the hour and closes the ticket only if it fails.

§03 — Proof, not noise

What lands in your queue.

Every Rogue finding is a working attack, written up the way your engineers want to read it: what was chained, what it reached, whether you saw it, and the smallest change that closes it.

Findings sync to Jira, Linear, ServiceNow and GitHub Issues with the owning team already assigned. Retests run automatically on merge.

SEC-8812 · rogue/web · retest: scheduledCritical · 9.4

OAuth authorization code theft via legacy SSO open redirect

Asset
sso-legacy.example-corp.com → billing.example-corp.com
Impact
Account takeover of any billing user who clicks a link; read access to 41,207 invoices proven via planted canary record.
Detected?
No. No alert in SIEM or EDR. Nightwatch rule BW-3192 drafted.
Fix
Exact-match redirect_uri allowlist on IdP client 0x41; rotate client secret.
  1. 1Open redirect on /sso/continue accepts any https hostT+07m
  2. 2IdP allows wildcard redirect for legacy clientT+12m
  3. 3Code exchanged for session as svc-billingT+18m
  4. 4Canary invoice INV-CANARY-77 retrieved, chain haltedT+22m
$ rogue replay SEC-8812 --dry-run ✓ step 1 302 → https://callback.rogue-lab.net/c ✓ step 2 code=7f3c…a1 captured (redacted) ✓ step 3 session issued: role=billing_reader ✓ step 4 canary match · sha256 9e1b…04 replay deterministic · safe to run in CI
§04 — Why change

The annual pentest is a photograph. Attackers watch video.

Your environment changes every day. A point-in-time report is out of date before the PDF is signed. Here is how the options actually compare.

Annual pentestVulnerability scannerBreach & attack simulationBadAI Rogue + Nightwatch
FrequencyOnce or twice a yearContinuousScheduledContinuous, 24/7
Exploits and chains vulnerabilitiesYes, limited by hoursNoReplays known scenariosYes, novel chains
Proof of impactScreenshotsNoPass / failReplay script + canary proof
False positives on criticalsLowHighLowEffectively zero
Tests LLM apps and AI agentsRarelyNoNoYes
Checks whether you detected itSometimesNoYesYes, and drafts the rule
Retest after fixNext engagementNext scanNext runWithin the hour

What CISOs say

§06 — From the field
Our last annual pentest found nine mediums. Rogue found the chain from our support chatbot to the billing database in its first afternoon — and Nightwatch hadn't seen it either. Both are fixed. That's the whole pitch.
CISO, Fortune 100 retailer
§07 — Questions

Asked in every briefing.

Anything else, ask an operator directly — we answer in plain language.

What is BadAI?

BadAI is an offensive security company. We build AI agents trained to think like attackers — Rogue — and point them at your systems with your written authorization, so every exploitable path is found and proven before a real adversary finds it. Our second product, Nightwatch, is a 24/7 AI defense agent that triages every alert, investigates incidents and contains threats in minutes.

How is autonomous penetration testing different from a vulnerability scanner?

A scanner reports what might be vulnerable. Rogue actually exploits it — safely, inside agreed scope — chains weaknesses together the way an attacker would, and hands you proof: the exact request sequence, the data it could reach and a replay script. If Rogue cannot prove impact, it does not file a ticket. That is why our false-positive rate on critical findings is effectively zero.

Is it safe to let an AI attack production?

Yes, when it is engineered for it. Rogue runs under a signed rules-of-engagement file that is enforced at the network layer, not just in a prompt. Destructive actions are blocked by default, impact is proven with canary records rather than real data, every action is logged and a kill switch halts all agents in under two seconds. See our rules of engagement.

Does Nightwatch replace my SOC or MDR?

Nightwatch replaces the tier-1 and much of the tier-2 workload: it investigates every alert, not a sample, and closes the noise with written evidence. Your analysts — or your MDR — get a short list of real incidents with a full timeline already assembled. Many customers run Nightwatch alongside an existing MDR and cut their escalations by over 80%.

Can you test AI and LLM applications?

Yes. Rogue/AI attacks chatbots, copilots and autonomous agents for prompt injection, tool abuse, data exfiltration, privilege escalation through function calls and jailbreaks, mapped to the OWASP Top 10 for LLM Applications and MITRE ATLAS. Our human Red Cell runs deeper model-level red teaming engagements.

How fast can we start?

Most customers have a first Rogue engagement running within five business days of the briefing: one day to sign the rules of engagement, one day to connect scope, and the agents do the rest. Nightwatch connects to common SIEM, EDR and cloud log sources in an afternoon.

Find out what bad AI finds.

A 30-minute briefing with an operator. We'll scope a first engagement against one real system of yours and show you the findings format before you sign anything.