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Linters don't think
Static analysis catches patterns. It cannot reason about what happens when amount is -9999, or what breaks when two threads collide on the same record.
Syntinel reviews every Pull Request the way an attacker would, then writes a test that exploits each serious finding and runs it in an isolated sandbox — so you see proof, not a guess. Critical issues block the merge.
def process_payment(amount, user_id): # charge the connected account charge = stripe.Charge.create( amount=amount * 100, currency="usd", customer=user_id, ) return charge.idAI-generated code ships fast and introduces subtle bugs the linter was never designed to catch. Human reviewers skim for obvious issues. CI tests only what you remembered to test — not the edge cases an attacker will find first.
Static analysis catches patterns. It cannot reason about what happens when amount is -9999, or what breaks when two threads collide on the same record.
Developers write tests for the code they meant to write. Adversarial edge cases — the ones attackers reach for first — stay uncovered until production finds them.
A failed pipeline 10 minutes after push is a broken flow. Context has switched. The branch is polluted. The cost is measured in reviewer time, not compute.
A developer opens a pull request. Syntinel receives the GitHub webhook and starts reviewing the diff straight away. Every new push to the PR is reviewed again.
An AI model prompted to think like an attacker reviews logic, data flow and security boundaries — injection, broken authorization, path traversal, weak crypto, leaked secrets.
For each high or critical finding, Syntinel writes a test that attacks the code with the finding's proof input and runs it in a locked-down sandbox — no network, read-only filesystem. On our seeded benchmark, 4 of 5 vulnerability classes are confirmed this way on every run, and each test passes once the bug is fixed. Python today.
Findings are posted as a PR comment with severity, proof and a fix. A CRITICAL finding fails the Syntinel check, which blocks the merge when the check is required. The team sees exactly what failed and why.
Every PR reviewed automatically, with a merge-blocking check on critical findings. Opening to waitlist teams first.
Run it before you commit. Scans your whole repository and writes a client-ready report — no waiting on CI.
Illustrative examples of the findings Syntinel reports. Click a tab.
from stripe import Chargefrom .db import conndef process_payment(amount, user_id): # Charge the user's card cents = amount * 100 charge = Charge.create( amount=cents, customer=user_id ) return charge.iddef find_txn(user_id, ref): cur = conn.cursor() # Lookup by reference cur.execute(f"SELECT * FROM txn WHERE ref='{ref}'") return cur.fetchone()import hashlibdef hash_password(pw): return hashlib.md5(pw.encode()).hexdigest()def verify(user, pw): stored = users.get(user) if not stored: return False return hash_password(pw) == stored.passwordfrom flask import Blueprint, requestbp = Blueprint("auth", __name__)@bp.route("/login", methods=["POST"])def login(): body = request.json or {} u = body.get("user") p = body.get("pass") if verify(u, p): return issue_token(u) return {"error": "bad creds"}, 401# TODO: rate limit — no throttle on this routefrom flask import Flask, request, jsonifyapp = Flask(__name__)@app.route("/compute", methods=["POST"])def compute(): body = request.get_json() expr = body.get("expr", "") # Quick-and-dirty calculator endpoint try: result = eval(expr) except Exception as e: return jsonify(error=str(e)), 400 return jsonify(result=result)