Continuous Security & Vulnerability Fuzzing in DevOps Pipelines

A FinTech company building microservices for high-concurrency payment gateways and mobile wallet transactions.

reduction in false-positive security scanner noise: 98%reduction in false-positive security scanner noise

How the work runs

The pressure that made this worth automating, the steps the system runs, and what came out the other side.

Pressure & Trigger Points

Traditional security pentests were conducted once a quarter by external vendors, catching security flaws long after code was shipped.
Standard DAST scanners produced excessive false-positive security alerts that overwhelmed developers.
Logic vulnerabilities (e.g., privilege escalation through altered API step sequences) went undetected by static code scanners.

The run · 5 operational steps

Click any step to inspect telemetry signals, model reasoning, and governance gates.

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Pariksha injects intelligent security payloads (SQLi, XSS, CSRF, auth bypass) directly into active pipeline test flows.

Input Signal:

Real-time operational telemetry & queue

Reasoning Pattern:

MCP grounded vector inference

Governance Gate:

Policy constrained with audit write-back

Verified Business Outcomes

Security vulnerability detection shifted left from quarterly pentests to every CI/CD pull request.
98% reduction in false-positive security scanner noise.
Caught critical business logic vulnerability in payment API prior to production deployment, saving millions in potential loss.

Capabilities this relies on