3 critical advisoriesLiteLLM 1.107.0·PHP2Shell·GitLab CVE-2026-110264All advisories→
Products

Continuous pen testing and an AI-native SOC. One loop, one findings stream.

An Attack agent that re-tests every confirmed path daily and tests new surface as it appears, scanners on every deploy, and expert pentesters for what no scanner models. Beside it, a SIEM that reads logs in your own cloud, response without playbooks, and an AI analyst on shift around the clock. Run the whole platform, or start with the one product your next audit needs.

Book a demo→Scope a pentest
● 2 free retests per engagement● Experts start within 5 business days● Read-only scanner access
Continuous pen testing

Automation for coverage. Experts for depth. One place to see what's exploitable.

Scanners catch known vulnerability classes the day they ship. The Attack agent proves which ones chain. People find the logic flaws and novel paths nothing automated can. What gets tested, and when you hear about it, is led by live threat intelligence. How we decide what to test→

Agentdaily + on change
Attack agentTests new surface as it appears, led by live threat intel
Daily regressionEvery confirmed case re-tested, so regressions surface by morning
Scannersevery deploy
DAST ScannerAuthenticated web app scanningAPI Security PlatformDiscovery and OWASP API Top 10Cloud Vulnerability ScannerAWS, Azure and Google Cloud
Expertson demand
PTaaS PlatformBlack, grey and white-box pentestsGenAI Penetration TestingModel and harness-level testingNetwork Penetration TestingExternal, internal and Active Directory
One findings stream. Deduplicated across sources, ranked by exploitability, mapped to SOC 2, ISO 27001, PCI DSS and HIPAA, and picked up by Analyse, Act and Adapt the moment a finding is confirmed.
PTaaS Platform

Expert-led pentests, delivered like software.

Scope and launch engagements from the platform. Security experts test business logic, chain vulnerabilities and probe what no scanner models. You see each finding the moment it's logged, not in a PDF weeks later.

Explore PTaaS→
  • Black box

    No credentials or internal knowledge. Testers attack like an outsider would, starting from what's publicly reachable.

  • Grey box

    User-level accounts and architecture notes. Simulates a compromised user or insider and gets deeper coverage in the same time.

  • White box

    Source code, configs and admin access. Testers pair code review with live exploitation to find flaws that are hard to reach from outside.

GenAI Penetration Testing

Test the model, and everything you've built around it.

LLM features fail in two places: in the model's behavior, and in the harness of prompts, retrieval, tools and agent permissions wrapped around it. We test both, mapped to the OWASP Top 10 for LLM Applications.

Explore GenAI testing→
Model levelHow the model itself responds under attack.
  • Jailbreaks and guardrail bypass
  • Direct prompt injection
  • Training and system prompt leakage
  • Harmful, biased or unsafe output
Harness levelThe application, data and tools around the model.
  • Indirect injection via RAG sources
  • Tool and agent abuse, excessive agency
  • Insecure output handling
  • Cross-tenant data exposure
How it works

From scope to signed-off report. Then it keeps proving itself.

Your apps, APIs, runtime, cloud, code and subdomains change with every deploy, so a point-in-time test goes stale the day the next one ships. Here, the report is where verification starts, not where it ends.

  1. 01

    Scope

    Connect your assets or upload a scope. Rules of engagement are agreed in a single call.

  2. 02

    Test

    The Attack agent and scanners start the day assets connect. Expert testing begins in your scheduled window, typically within 5 business days.

  3. 03

    Fix

    Findings arrive with reproduction steps and fix guidance, pushed to Jira, GitHub or Slack. For cloud and IAM issues, the Act agent can open the PR once you grant its opt-in remediation role.

  4. 04

    Prove

    Retest the fix, export reports mapped to SOC 2, ISO 27001, PCI DSS and HIPAA, then daily regression keeps re-checking the path, and reopens it if it regresses.

Powers every product

Threat intelligence by Scout. Know about new threats first.

Over 30 sources checked every 10 minutes, plus our own scanning of package registries. One deduplicated record per threat, feeding the Attack agent and the SOC alike.

Every finding

Proof for engineers. Clarity for leadership.

For engineering teams

Every finding comes with the exact request, the response that proves it, and a fix written for your stack, tied to the change that introduced it. Only exploitable issues interrupt your team; everything else waits for the daily digest.

For security leaders

Continuous evidence instead of an annual snapshot. Risk ranked against live threat intelligence across every domain, cloud account and device, in reports the board and your auditors can read without a translator.

For the SOC

A confirmed exploit path becomes something the agents watch for. Adapt drafts a detection for it, and Analyse links any live attempt back to the finding.

CriticalCVSS 9.1API SecurityConfirmed by tester
Broken object-level authorization on GET /api/v2/invoices/{id}
api.example.com · Found by API scanner · Confirmed by expert tester
Reproduce
GET /api/v2/invoices/48213 HTTP/1.1
Host: api.example.com
Authorization: Bearer <token for user_b>

HTTP/1.1 200 OK
{ "invoice_id": 48213, "owner": "user_a", "total": "…" }
Fix

Check ownership on every object lookup. Derive the owner from the authenticated session, never from the request path or body.

SOC loop

Detection D-0311 drafted for cross-tenant invoice reads Daily regression · next run 02:00

Create Jira issueRequest retestTester note: also reproducible on /receipts/{id}
Illustrative finding · sample data
Agentic SOC

The SOC, run by agents. Your logs never leave your cloud.

Each of these used to be its own vendor, its own console and its own invoice, plus the analysts to run them. Here they're phases of one agent loop, reading from the same asset graph and the same findings stream.

Experts on demand

Incident response. Humans when an incident needs them.

Investigation and containment by our responders, actionable intel and recommendations fast, and audited evidence packs for regulated businesses. Customer or not.

Integrations

Fits the way you already ship.

Findings go where your team works. Scans start from your pipeline. Cloud accounts connect through a read-only role, the same one the SOC agents read through. Remediation by the Act agent uses a separate role you opt into.

Ticketing
JiraLinear
Code and CI/CD
GitHubGitLabAzure DevOpsJenkins
Alerts
SlackMicrosoft TeamsPagerDuty
Cloud
AWSMicrosoft AzureGoogle Cloud
Build your own
REST API + webhooks
Reports map toSOC 2 · ISO 27001 · PCI DSS · HIPAA · OWASP Top 10 · OWASP API Security Top 10 · OWASP Top 10 for LLM Applications
FAQ

Questions we hear first.

How do continuous pen testing and the SOC connect?
They are two sides of one loop. Pen testing proves what's exploitable: the Attack agent re-tests every confirmed path daily and tests new surface as it appears, scanners cover every deploy, and expert testers go deep when it matters. Every confirmed finding lands in one stream that Analyse links to live telemetry, Act can remediate, and Adapt turns into a detection for that exact path. Each side also runs on its own.
How is PTaaS different from a traditional pentest?
A traditional pentest ends in a PDF weeks after testing finishes. Here you scope and launch engagements in the platform, see each finding as soon as a tester logs it, message testers directly, and request retests without opening a new statement of work.
Should we choose black-box, grey-box or white-box testing?
It depends on what you want to learn. Black box shows what an outside attacker can reach. Grey box gives testers user-level access and architecture notes, so they spend less time on recon and go deeper. White box adds source code and configuration for the most thorough coverage. Many teams run grey box by default and white box for critical systems.
Do you test the AI model, or the application around it?
Both. Model-level testing targets how the model behaves under attack: jailbreaks, prompt injection, data leakage and unsafe output. Harness-level testing targets what you have built around it: system prompts, retrieval pipelines, tools and agent permissions, which is where application-specific risk lives.
Will scanning affect production?
Scans are rate-limited and can be pointed at staging, restricted to safe checks, or scheduled outside business hours. Expert testing follows rules of engagement agreed with you before any testing starts, and the Attack agent is read-only in production by default.
How do retests work?
When a fix ships, request a retest from the finding. The scanner or the original tester validates the fix, and the status updates everywhere the finding appears, including your reports. After that, daily regression re-checks the path and reopens the finding if it regresses.
Can we buy a pentest without the rest of the platform?
Yes. Each product runs on its own, and every engagement is one scope, one price, agreed up front, with two retests included. Most teams start with whatever their next audit or launch needs.

Know what's exploitable before someone else does.

Get a walkthrough scoped to your web apps, APIs, cloud accounts and AI features, and a testing plan you can take to your next audit.

Book a demo→Scope a pentest