ADA
Securing your future
Security for the era of vibe coding.
ADA scans your code and detects real issues like SQL injection, command injection, and leaked API keys.
Paste code and click Scan to see results here.
ADA is an accuracy-first, AI-native vulnerability platform for the vibe-coding era. Developer-first. Trust-obsessed.
People don't trust scanners. Too many false alarms, or worse, a real bug that slipped past. So we obsess over one thing: accuracy. Not finding counts. Not flashy dashboards. Just what's real.
AI writes code that runs. That is what it was trained to do, and it does it well. What
it was never trained to do is ask what happens when the input is hostile. The result is
a working feature with an unparameterized query inside it, where nothing looks wrong
until something goes wrong. Research puts the rate at
40% to 60% of unguided AI-generated code containing security
flaws, and they are usually the ordinary ones: string-built SQL, a missing
authorization check, pickle.loads() on something a user sent.
The tools that exist for this were built for security engineers, who can read forty warnings and identify the two that matter. That is a professional skill, and most people shipping with Cursor or Lovable do not have it. Given output they cannot evaluate, they stop reading it. That is the problem we set out to solve.
The market moved before the tooling did. Cursor, Lovable, Bolt and Replit turned building software into a conversation, and the number of people shipping production code without a security background went up by an order of magnitude. Every scanner on the market still assumes the same operator it assumed in 2015: a professional, inside a CI pipeline, with time to triage. The fastest-growing group of software authors has nothing built for them, and the tools they do reach for are accurate enough to be dangerous and noisy enough to be ignored.
| Accuracy on 62 real applications | Findings that are real |
|---|---|
| ADA | 96% |
| Claude Code, told to do a security review | 62% |
| SonarQube | 15% |
| Semgrep | 13% |
24 false alarms across 62 applications. The AI agent produced 799. For a security team that is weeks of work spent dismissing things that were never real. For one person shipping a product it is the reason the report gets closed and never opened again. We would rather surface three issues and have all three be worth your time.
Both numbers are real and they measure different things. Test corpora isolate one vulnerability per file. Real applications bury three bad lines in two thousand. Semgrep scores roughly 90% on the first and 7% on the second. Most vendors publish the first only. We publish both, and the harness that produced them ships in our repo.
We find about 30% of the vulnerabilities in a working application. An AI agent finds roughly 68% and is wrong four times out of ten doing it. Semgrep finds 7%. Published research puts a single tool somewhere between 11% and 27%, so nobody is close to solving this, and anyone claiming otherwise is quoting a test corpus.
A third of what gets missed is not bad code at all. It is missing code. A login route with no rate limiting. A record lookup that never checks whether this user owns that record. Nothing on the screen is wrong, so there is no pattern to match, and no rule engine finds them. Not ours, not anyone's. That is the part we are building next.
Something dangerous is written down.
os.system(f"ping {user_input}")
Something necessary was never written.
@app.route("/login") # no rate limit anywhere
Software used to be written by people trained to distrust their own inputs. That stopped being true about two years ago, and almost nothing in security has caught up.
A model is rewarded for producing something that works. Nothing rewards it for asking what happens when the input is hostile. The flaws are the ordinary ones: a query built by string concatenation, an endpoint with no authorisation check, a password stored in plain text.
Cursor, Lovable, Bolt and Replit turned building software into a conversation. Every scanner on the market still assumes the operator it assumed in 2015: a professional, inside a pipeline, with time to triage forty warnings.
Hand someone output they cannot evaluate and they stop reading it. So we optimised for the opposite of volume. Three findings that all matter beat eighty that might.
Pattern matching finds code that is dangerous. It cannot find code that is missing: the login route with no rate limiting, the record lookup that never checks ownership. Roughly a third of real vulnerabilities are absences like these, and no rule engine reaches them.
Closing that gap is what the Ada Reasoning Engine below is for, and it is the work we are doing now. A detection layer that reads code for intent rather than shape, wrapped in the same triage discipline that produced the number above. Around it sits the rest of the platform: remediation, editor integration, and threat modelling that traces a finding to the exploit path an attacker would actually take.
Signal over volume. A finding that isn't real isn't a feature, it's noise.
Every finding traces to an auditable rule. AI can question one, never invent or hide one.
No security background needed. Built for builders shipping fast with Lovable, Bolt, and Cursor.
The moat isn't detection. It's understanding.
Semgrep, Snyk, and CodeQL already detect well. AdaRE reads each finding in context, separates real threats from noise, and hands you a fix you can trust.
Scan as you code, right in your editor, so issues never reach a commit.
The safer fix, ready to apply. Remediation, not just detection.
Threat modelling on top of findings. The actual exploit path, not just the flagged line.
Detection comes from graduate cybersecurity work at Georgia Tech and hands-on offensive security.
AI triage comes from Stanford CS and production engineering on an AI-powered security platform.
Want the full team's LinkedIn profiles? Send us a message →
Send us a message and we'll get back to you, or email us directly at contactus@adasecure.net.
Last updated: 31 July 2026
ADA is a security scanner. You paste code into it, so we think you deserve an unusually specific answer about where that code goes. This page is that answer, no vague "we may share data with partners."
If you scan without an account: the code you paste is processed to run the scan, and a record of that scan, the code, the findings, and the write-up, is kept so we can measure usage and improve the scanner. That record isn't linked to you: no account, no IP address, no session identifier. See "We keep a record of every scan" below. Your IP is used in memory to enforce rate limits and isn't stored with the scan.
If you sign in with Google: we receive and store your email address, name, profile picture URL, and Google account ID. We also save your scan history, the code you scanned, the findings, and the AI write-up, so you can revisit past scans.
If you use the contact form: we store the name, email address, and message you submit, plus your IP address.
Running a scan sends data to these third parties. This is the section most privacy policies leave vague, so here it is in full:
requirements.txt or package.json, the package names and version
numbers are sent to look up known vulnerabilities. Your code is not sent.The scanners themselves (semgrep and trufflehog3) run locally on our server. We have explicitly disabled semgrep's usage telemetry, so no scan data is reported to them.
This applies whether or not you have an account. When you run a scan, we store the code you submitted, the findings, the risk verdict, and the AI write-up. We use these records to measure how ADA is used, to see which detection rules fire on real code and which produce false positives, and to improve the scanner.
These records are not linked to you. We store a flag for whether the scan came from a signed-in account, but not which account, and no IP address or session identifier. Credentials are masked first, exactly as described below.
If you're signed in, your scan history is stored separately and is linked to your account, that's what makes the history dropdown and report export work.
The practical version: don't paste code you wouldn't be comfortable having stored on our servers. If your employer restricts sending source code to third-party services that retain it, that restriction applies here.
If a scan detects a credential (an API key, token, or password) in your code, we mask it
before saving anything to our database. The masked form keeps just enough to identify which
credential it was, for example AKIA…[redacted]. Live secrets are not stored in
plaintext.
That said: if you paste a real, active credential, you should treat it as exposed and rotate it. It passed through our server and Anthropic's API in order to be scanned.
Two cookies, both first-party. No advertising cookies, and no third-party analytics, we don't load Google Analytics or anything like it.
ada_vid), a random ID we generate, used to
count visitors and to see whether people come back. It's an analytics cookie, so we'll call
it what it is: it does track your return visits. It contains a random string and nothing
else, no name, no email, no IP, and no link to your account if you have one. Clearing your
cookies resets it and we lose the connection entirely.We record page loads: the page, the time, the visitor cookie above, and the domain
of the site that linked you here (for example reddit.com), never the full
referring URL, which can contain search terms. We use this to know how many people visit, how
many go on to run a scan, and where they came from.
Requests from bots and crawlers are excluded, and we don't store IP addresses against page views.
Account details and scan history are kept until you ask us to delete them. Contact messages are kept so we can reply and follow up. Scan records (see below) are kept indefinitely at present; if we adopt a fixed retention period we'll say so here.
Email contactus@adasecure.net and we'll delete your account and its scan history. We're a small team, expect a human reply, not an automated portal.
If this policy changes materially, we'll update the date at the top. Continuing to use ADA after a change means the updated policy applies.
Questions about any of this: contactus@adasecure.net.
Last updated: 28 July 2026
The rules for using ADA. The most important part is the section on what ADA does not guarantee, please actually read that one.
ADA scans code you provide for common security problems: hardcoded secrets, risky code patterns, and known-vulnerable dependencies. It then uses AI to explain the findings, judge which are likely false positives, and suggest fixes.
This is the part that matters most. A clean scan does not mean your code is safe. ADA finds specific classes of known problems, it does not find every vulnerability, and no scanner does. Do not treat ADA as a substitute for a security review, a penetration test, or your own judgment.
ADA is provided "as is", without warranty of any kind. We are not liable for any damages, breach, or loss arising from your use of it, including vulnerabilities ADA failed to detect, or findings it reported that turned out to be wrong.
The summaries, the "likely real / likely false positive" triage, and the suggested fixes are generated by an AI model. They can be mistaken. Suggested fixes are suggestions, review and test them before putting them anywhere near production. ADA never applies a fix to your code automatically, by design.
Don't submit code you don't own or otherwise have the right to share, and don't submit code you're contractually barred from sending to a third-party AI service. Scanning sends your code to Anthropic, see the Privacy Policy.
Rate limits apply. Don't try to bypass them, don't use ADA to attack it or anything else, and don't resell access. We can suspend accounts that abuse the service.
You're responsible for what happens under your account. Accounts are created via Google sign-in; keep that account secure.
These terms may change. Material changes get a new date at the top, and continuing to use ADA means you accept them.