Built for AI-era application security. Not adapted to it.
Farion was designed from scratch for a world where vulnerabilities are discovered, weaponized, and exploited by AI. Traditional AppSec architectures were not.
AI changed offensive security. Defensive tooling stayed the same.
Most modern AppSec products still rely on architectures designed long before generative AI existed: a legacy SAST or SCA engine, heuristic prioritization, and an external language model bolted on to summarize the findings. The AI is a post-processing step, not part of the security engine — so it inherits every limitation of the scanner underneath it: shallow data-flow understanding, generic severity metrics, high overhead, inconsistent reasoning, and slow adaptation to new threats.
At a time when exploits can be generated within hours of disclosure, that architecture no longer holds up.
Built for AI-era application security. Not adapted to it.
Native analysis in JavaScript/TypeScript, Python, Go, Rust, C, C++, C#, Java and Kotlin
Compiler-grade analysis per language — SSA-based, context- and field-sensitive.
Our security SLMs, hosted in Germany
Specialized security small language models. Customer code is never used for model training.
Dedicated & on-premises deployment
Run Farion fully isolated behind your own perimeter — built for regulated environments.
Farion Dataflow Engine
Farion Security Scanner
Farion Security AI
Findings
Farion ThreatIntel Database
AI is part of the engine, not a wrapper around it.
Farion was engineered as a distributed, cloud-native platform where every major component was built for AI-assisted security analysis. Each one produces structured facts, so the next stage reasons about exploitability with far more precision than an isolated scanner. General-purpose models are excellent reasoners — but they can't compensate for missing program analysis, so we give them the context program analysis produces.
Native program analysis
Compiler-level understanding per language — native parsers, SSA, control and data flow. Farion reconstructs how data actually moves through an application, so reachability and exploitability rest on traceable program analysis rather than pattern matching.
Threat intelligence
A proprietary vulnerability-intelligence pipeline correlates vendor advisories, research and exploit repositories — not just NVD or OSV. It asks whether a vulnerability can be exploited in your application today, not merely whether the CVE is present.
Exploitability analysis
CVSS and EPSS describe a vulnerability globally, not your codebase. Farion combines data flow, framework behavior, configuration, runtime context and threat intel to decide what is genuinely reachable and exploitable — and so reduces false positives.
SAST-informed active AI verification
Farion uses the routes, sinks, data flows and candidate findings produced by its static analysis engines to generate targeted attack traffic. Active verification tests specific hypotheses instead of running a generic black-box scan. Active verification runs only against target URLs explicitly configured and authorized by the customer.
Enterprise-ready by design.
Farion's distributed microservice architecture supports multiple deployment models without changing the analysis engine — so you can meet regulatory and data-residency requirements without sacrificing detection quality.
Shared SaaS
Hosted in Germany, tenant-isolated.
Dedicated
From 100 contributors on most Kubernetes clusters — in your cloud or your data centre (cloud-native stack).
On-premises and air-gapped
On the Enterprise plan.
See the architecture on your own code.
Native program analysis, proprietary threat intelligence, security language models and SAST-informed active AI verification — one pipeline, running on your codebase.