It tests your app. It proves the bugs. It ships the fix.
Sintropyc opens your web or desktop app in a real sandbox, uses it like an attacker, proves each vulnerability with recorded evidence, rewrites the root cause and verifies the patch held.
Small teams are now the main target.
Attackers moved down-market. The tooling that used to hit enterprises now hits everyone — automatically, at scale, with AI.
SMBs are attacked 3–4× more often than large corporations. You're the primary target now — not collateral damage.
AI cyberattacks on small business grew 340% in 2025. Generative-AI phishing gets opened 54–78% of the time — against just 12% for the traditional kind.
Most breaches aren't sophisticated exploits — they're cloud misconfigurations (open AWS S3 buckets) and over-broad access.
Where it tests you like an attacker.
Sintropyc opens both of your surfaces in one sandbox and proves what's exploitable before they do — web and desktop, in the same run.
One sandbox. Every surface. Real results.
A single run checks your web and desktop app in the same session and hands you findings you can act on today.
Issues surface as the agent works. Each one is linked to the exact line, with a fix already applied and verified — so security ships with your code instead of arriving as a report the week after.
What it actually proves — not just flags.
Every finding ships with a live recording of the exploit. Not a CVSS score. A proof.
Payloads injected and JavaScript execution confirmed in the real browser session.
Proven liveRaw string builds proved against a live database response, not inferred.
Proven liveShell commands run in the sandbox and output captured as evidence.
Proven liveServer-side requests tracked source-to-destination in a live session.
Proven liveFound API keys validated against the live provider — a confirmed exposure.
Live validatedSAST, DAST, SCA, dependency audit and surface recon — same sandbox run.
Same sandboxProof, not noise — and you keep it.
Each run executes in an isolated container on your own machine and is destroyed after. Your code is never stored or used to train any model.
Every finding comes with a live exploit recording and a ready, verified fix — so you ship the patch, not a backlog ticket.
Localhost and private targets run automatically; public targets only after you confirm ownership. Scope is a hard gate, never a model decision.
Proved → fixed → proved again.
The agent demonstrates the issue on the running app and captures the evidence in a live session.
A real change to the root cause — parameterised, scoped, reviewable — applied in the editor.
The same payload is replayed. It no longer fires — before/after, confirmed and recorded.
The questions that come up first.
What are the system requirements for the sandboxes?
Each run executes inside an isolated Docker / Podman container on your own machine, with a bubblewrap fallback. The footprint scales with your app. Every sandbox is timeout-bound, resource-limited and destroyed after the run.
Can I run it in a fully isolated / air-gapped environment?
Detection and scanning run locally — sintro -m audit ./repo --no-live works offline. Live secret validation and the agent's reasoning currently need network access, so a fully air-gapped mode is on the roadmap.
Which models do you use, and how are prompts kept private?
The agent reasons with a mix of Gemini 2.5, DeepSeek and Claude Sonnet, chosen per task. Calls run under enterprise agreements that forbid training on your data — your code is only ever a transient prompt, never stored.
How is test scope controlled?
Scope is a deterministic gate, never a model decision. Localhost, loopback and private-LAN targets are allowed automatically. Public targets only run after you confirm ownership. Anything ambiguous stops and asks.
AI cybersecurity that proves the exploit — then ships the fix.
Most AI security tools stop at a list of maybe-vulnerabilities. Sintropyc is an AI cybersecurity agent that goes further: it runs your web or desktop app in an isolated sandbox, performs automated penetration testing the way a real attacker would, and proves every finding with a recorded live exploit — not a CVSS guess.
It covers the flaws that actually breach small teams: XSS, SQL injection, command injection, SSRF, path traversal and leaked live API keys. Each confirmed issue ships with a root-cause fix Sintropyc writes, then re-verifies by replaying the exploit — dynamic application security testing (DAST) with proof, plus a silent layer of SAST, SCA and dependency auditing in the same run.
A security scanner built for AI-generated code
If your team ships AI-generated code from Cursor, Lovable or Claude Code, new endpoints and secrets land every day. Sintropyc is the vulnerability scanner for AI-generated apps that reviews each change like an attacker before it reaches production — locally, on your own machine, with your source code never stored or used to train a model. Read how AI security testing works →