Tame wild code.
Automated red-team engineers that live in your GitHub repo. Tell them where to dig in plain English. They hunt for exploits that actually work.
The scan is free. You pay only if we find a working exploit.
From install to fix list in a day.
No pentest kickoff call or scoping spreadsheet. The agents clone your repo, stand it up in an isolated sandbox, and attack the running app, never production.
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Connect GitHub
Install the GitHub app or sign in with GitHub. Read-only access. Starting a scan is free.
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Point them somewhere (optional)
Describe what worries you in plain English. Skip it and the agents follow their own instincts about your codebase.
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Let it run
10 to 20 hours, depending on size. OWASP Juice Shop takes at least 10. You get a progress link when it starts.
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Hand the report to your coding agent
Claude Code, Codex, or Devin can read it and fix what we found. You pay only if it lists a confirmed exploit.
Steer in plain English
Examples of the directions teams give.
Focus on the Stripe webhook. Assume the attacker has a free-tier account.
We just added SSO. Try to get into another tenant's workspace.
Exploited before the patch exists.
Days for attackers to exploit a vulnerability, 2020 to 2026E. Negative means before a patch is public.
Days for organizations to fix one, over the same period.
Source: Juan Pablo Castro, VP at TrendAI, LinkedIn, October 2026.
Offensive security becomes a continuous capability.
Attackers already move at AI speed. Defenders need the same speed and scale, aimed at their own code first.
The codebase doesn't stand still. A team can spend weeks working through pentest findings while developers keep shipping, new services get connected and permissions change. By the time one report is closed, there is a new set of weaknesses to find.
AI widens that gap. Bain estimates it can compress a typical attack sequence from about four weeks to about eighteen hours.1 A yearly pentest can't keep up with that. seku.red runs a red-team engineer against every repo you connect, as often as you ship.
1. Bain & Company estimate, attack sequence duration with AI assistance.
Not another SAST.
Scanners flag code patterns. Our agents attack the running app and keep only what holds up.
Built on your scanners, not a replacement
We read the output of whatever SAST you already run, then try to exploit each lead in a sandbox. False positives are dropped with a reason. Findings with no route in from outside are marked unreachable.
- Semgrep
- CodeQL
- Snyk
- Bandit
- OWASP ZAP
- your SAST
Blackbox pentesting, with no source required
The same agent also attacks like an outsider with no source access, catching forgotten endpoints and default settings. That costs about 400× less than a manual pentest.
The model is fine-tuned on data from experienced bug bounty hunters and penetration testers, including minus-day vulnerabilities, and retrained nightly.
A report your coding agent can act on.
Each finding is either confirmed, a false positive, unreachable, or low signal. Confirmed ones include the full chain, so a coding agent can patch them without asking.
- CWE, file and line for every finding
- Attack paths in order: entry, pivot, impact
- The payload that worked, so the fix can be retested
## Confirmed exploitable (1) ### SQL injection in login → admin takeover CWE-89, routes/login.ts:37 Entry POST /rest/user/login, `email` field Pivot email: ' OR 1=1-- → first row of Users Impact JWT for admin@juice-sh.op Fix Use a parameterized query with `replacements: { email }`. Retest Replay the payload above, expect 401. ## False positive (12) ## Unreachable (7) ## Low signal (31)
Tame wild code.
The scan is free. You pay only if we find a working exploit. Production is never in scope.