Agents, not pipelines
The model plans the engagement, picks the tool, writes the payload, and rewrites the plan from what it just learned. There is no fixed scan template to outgrow.
AI-native application & infrastructure security
Security agents that find, prove and explain vulnerabilities
ScanSuite runs AI agents across your source code, web applications and infrastructure. Each one plans its own work, verifies every finding against the real system, and proves it with an exploit that actually runs — on-premise or in your private cloud.
- AI Native SAST
- AI Pentest
- AI DAST
- Dependency Reachability
AI-Verified Findings
Not another scanner. An agent platform.
Classic scanners produce lists that someone still has to triage. ScanSuite's agents produce conclusions — with the reasoning, the call path and the working proof attached.
44
Tools the pentest agent can call
34
Web attack technique modules
20+
Languages analysed by the code agent
Evidence, not guesses
Every finding is re-checked before it is reported: source-to-sink tracing for code, baseline-versus-payload comparison for web, and for infrastructure a proof of concept that has to run.
Your scanners become tools
Nessus, OpenVAS, Acunetix, ZAP, Nuclei, Trivy and 30+ more stay in the platform — and are handed to the agent as callable tools it can reach for on its own.
Part One
AI Static Analysis
Point it at a repository. The agent reads the code the way a reviewer would — then proves the path from untrusted input to dangerous sink before anything reaches your backlog.
Selected stage
Repository intake
Upload an archive or point ScanSuite at a repository. Scanning modes cover a single run, a daily, weekly or monthly schedule, a monitored branch that scans on change, an incremental scan of only what moved, or a custom path scope — so a re-scan costs what the change costs, not what the codebase costs.
Dependency reachability: from the CVE list to the ones that matter
A dependency scan reports every advisory that touches your lock files. Four gates, cheapest first, decide which of them is worth a person's afternoon.
The rest of the AI static pass
Enabled per scan, on the same run, against the same checkout.
AI-verified secrets
Detected keys and tokens are re-checked by the model, so example credentials and long-rotated test keys stop paging the team at 2am.
AI code documentation
Generates a security-oriented tutorial of the codebase — abstractions, how they relate, chapter by chapter — readable directly in the web interface.
Incremental & monitored
Monitor Changes and Incremental Scan re-analyse only what moved since the last run, which is what makes per-commit AI analysis affordable.
Deduplicated by identity
Findings are keyed on vulnerability class, file and parameter — deduplicated within the scan and against history, so the same issue never lands twice.
Part Two
AI Pentest & AI DAST
Give the agent a scope and one sentence of instruction. It plans the engagement, runs the tools, improvises when the plan stalls, and comes back with a proof of concept that ran.
The whole configuration is a sentence
No scan profile to tune, no attack tree to pre-build. Scope, credentials if you have them, and what you care about.
“Enumerate services, prioritize SMB and web, and verify exploitable findings with a PoC.”
Operator instructions field — everything else is the agent's decision
Selected phase
Plan
The agent returns a strict engagement plan: ordered steps, the rationale for each, the tools it needs, the targets it touches, the outcome it expects, and what depends on what.
What the agent can reach for
Forty-four tools, from a full OSINT bundle down to a single crafted HTTP request.
Recon bundles
Subdomain and OSINT enumeration, host discovery, technology fingerprinting, certificate-transparency origin discovery, DNS recon, Shodan lookups, and endpoint and secret extraction from JavaScript.
Enterprise scanners by API
Nessus, OpenVAS and Acunetix are driven as tools — submitted, polled and parsed — with their findings returned into the agent's context rather than a separate report nobody opens.
Web scan bundles
Quick, balanced, API and deep web scans, each threaded with the engagement's authentication so post-login surface is actually tested, not just the marketing pages.
Improvisation
An allow-listed command runner — nmap with NSE, httpx, gobuster, naabu, nuclei and more — with arguments the model chooses, plus Nuclei templates written on the fly for a target-specific check.
Interactive HTTP
Session-persistent login, parameter fuzzing with response diffing, request comparison for access-control and IDOR gaps, and credential-reuse pivoting across discovered services.
Exploit research to PoC
Look a product and version up in the exploitable-CVE database, fetch the referenced exploit, generate a Python proof of concept, run it in a sandbox — and record the finding only if it worked.
Safety rails
Boundaries enforced in code, not asked for in a prompt: scope-locked targets, no shell and allow-listed binaries only, exploit pages fetched solely from database-returned URLs, sandboxed PoC execution, and budgets on every engagement.
AI DAST — the web scanner that decides its own payloads
A black-box engine you can run on its own or hand to the pentest agent. The model picks the attack point, the technique and the concrete payload; the technique module shapes the request flow and scores the signal.
Selected stage
Discover
An internal crawler plus imported crawl records build the attack surface — visited URLs, forms, parameters — and deduplicate it into distinct attack points, so the same parameter is not tested eleven times under eleven URLs.
34 technique modules
- SQL injection
- SSRF
- SSTI
- XSS, reflected and stored
- XXE
- Command injection
- Open redirect
- Path traversal
- Weak credentials
- Access control
- Client-side
- Server-side
Advantages
- Payloads chosen per endpoint, not replayed from a catalog
- Finds flaws that no rule or template covers
- WAF-aware payload shaping
- A confirmation pass discards what it cannot reproduce
- Every finding carries its HTTP exchange as evidence
- Authenticated, session-aware testing
Close the loop
Vulnerability Management
Everything the engines produce lands in one place — already deduplicated, already validated, already carrying the evidence a developer needs to fix it and the proof a sceptic needs to believe it.
Selected stage
Ingest
Findings from AI Native SAST, dependency reachability, secrets, AI DAST, AI Pentest and every classic scanner are normalized into one vulnerability record, with the product, target, scanner and scan run attached.
The evidence behind every verdict
Code-flow diagram, rationale, confidence, exploit references
Open a finding and the reasoning is there to be checked: the rendered code-flow diagram with its step explanation, the reachability rationale, the confidence statement, the risk score and the reported-exploitation references. An AI verdict you cannot audit is just a different kind of false positive.
A proof of concept you can execute
Generate, edit, run, refactor — in the interface
The PoC is Python you can read, change and save. Run it against the target from the finding view and read the exit code and output, or ask the model to refactor it against the success condition. A finding that ships with an exploit that runs does not get argued about in triage.
Platform & Coverage
Everything the agents are built on
Exploitable Vulnerabilities Database
Over 130,000 CVEs with real exploit evidence, queried locally
Every entry carries evidence rather than a severity label: CISA or VulnCheck KEV listing, a published exploit, PoC code, or an EPSS score in the top decile. It gates dependency findings, backs the pentest agent's exploit research, and is checked automatically during infrastructure scans — no external lookup, no data leaving the deployment.
CI/CD and existing workflows
Pipelines, DefectDojo, Jira
Run scans inside your pipelines and keep the results where your teams already work. Findings export to DefectDojo per scanner, and upload to Jira for remediation tracking, benchmarks and SLA reporting.
EASM & OSINT
Subdomains, hosts, websites, emails and leaked credentials — map the external attack surface before somebody else does.
Custom rules everywhere
Team-specific rules for static, web and infrastructure scanning — including Nuclei templates generated from your own findings.
On-premise or air-gapped
Run the whole platform inside your perimeter, in a private cloud, or fully offline. Your code and findings stay where you put them.
Your model, your choice
Bring your own LLM provider or run models locally. Token usage is recorded per scan so the cost of an engagement is never a surprise.
Application Security Orchestration & Correlation
Selected phase
Development / IDE
IDE plugins, data classification, and engineering checklists catch risks before code leaves the developer workflow.