Trace attacker input to the vulnerable operation.
Farion combines reachability with data-flow analysis across functions and files. See how attacker-controlled input moves through your application, which vulnerable operations it can reach, and the evidence behind each exploitability assessment.
Growing application complexity. Less time to understand the risk.
Third-party dependencies, AI-generated code, and complex deployment configurations make it harder to distinguish scanner noise from vulnerabilities that threaten your application. Each finding needs context: does it affect the code you use, and can an attacker exploit it? Meanwhile, attackers can begin targeting newly disclosed vulnerabilities within hours. Manually investigating every finding consumes the time teams need to secure their applications. Automated exploitability analysis helps teams identify exploitable vulnerabilities, respond sooner, and retain the evidence behind their decisions. That evidence also supports vulnerability management and compliance reviews for organizations addressing NIS2, the Cyber Resilience Act, or BSI IT-Grundschutz.
Findings grouped by route
Farion attaches every finding to the HTTP route, RPC endpoint, or message handler it belongs to — you start from an application path, not one endless global list.
SCA, SAST and active verification, correlated
Open a route and every signal is already there — vulnerable dependencies, code findings, and active-verification results, all tied to the same path. Switch between them without losing context.
Evidence-backed exploitability verdict
See the vulnerable source, the data flow that reaches the sink, and Farion's AI verdict with its supporting evidence — the full case for whether a finding is truly exploitable.
A suggested fix as a pull request, ready for review
Analysis becomes remediation: a concrete patch with a reviewable code diff and a prepared pull request.
A03:2021 – SQL injection in user lookup query
The login email is concatenated into a raw SQL WHERE clause and executed without parameterization.
AI Analysis by Farion
True Positive
LoginRequest.email crosses two injected beans and a factory into the WHERE clause JdbcTemplate executes.
How Farion follows data across function and file boundaries.
The language-aware model resolves function calls, object instances, dependency injection, and field-level data flows. It connects input sources to the operations that consume them, providing the analysis foundation behind the finding.
Farion Dataflow Engine
Farion Security Scanner
Farion Security AI
Findings
Farion ThreatIntel Database
Frequently asked questions
Farion first resolves application structure and data flows through static analysis. AI uses that evidence to explain exploitability and propose remediation. The analysis is not an AI guess based only on a code snippet or an advisory.
Yes. SAST analysis follows input into security-sensitive operations in your code. SCA adds how the application calls dependency code, whether vulnerable functions are reachable, and the data paths that lead into them.
Yes. Active Verification uses the static finding and its route, parameter, and data-flow context to direct dynamic tests against an authorized application.
Questions to answer before a technical evaluation
Follow a finding through your own code.
Walk through the route, data flow, and exploitability assessment with our technical team.