Synechron RAPID: Remediation at Machine Speed with a Human at the Gate

Aaron Momin

Chief Information Security Officer,Synechron

Eklove Mohan

Senior Director,North America, Synechron

Cybersecurity

A multi-agent AI system that validates, fixes and verifies the vulnerabilities signature-based tools were never built to catch, inside the CI/CD pipeline you already run.

By Aaron Momin, Chief Information Security Officer and Eklove Mohan, Sr. Director.

Summary:

  • Synechron RAPID is a multi-agent AI accelerator that finds, confirms and fixes application vulnerabilities by reasoning about what the code is meant to do, who is allowed to do it and where the data goes. It runs inside a bank's existing CI/CD pipeline, alongside its SAST, DAST and SCA scanners.
  • Most institutions already hold more scanner findings than they can close, and AI coding assistants are adding to the pile. In 2025, 61% of breaches exploited a flaw that already had a patch available.
  • RAPID targets the flaws pattern-matching scanners overlook, including broken access control, insecure direct object references and privilege escalation, and it confirms each one can be reached and exploited before a developer sees it.
  • Every fix is measured against a baseline captured before any code changes, coordinated across files into one reviewable patch and retested afterward. A human approves each merge, and each change carries reasoning an auditor can follow.
  • Because the baseline and retest bound regression risk, RAPID makes it practical to remediate legacy and core banking code that teams have left untouched for years.

Most financial institutions do not have a vulnerability discovery problem. They have a backlog inventory. Existing scanners have already cataloged thousands of findings, and AI coding models are now adding to that list faster than any team can work through it. The question security leaders are asking has changed from "what are we exposed to" to "how fast can we close it." At Synechron, we built RAPID to answer that second question.

What RAPID Is

Synechron RAPID Agentic Accelerator is a multi-agent AI system that discovers, validates and remediates application vulnerabilities by reasoning about how your code works: its business logic, its data flow and its authorization model. It runs inside the CI/CD pipeline you already operate and sits alongside your existing SAST, DAST and SCA tooling. RAPID augments those scanners rather than replacing them.

A signature-based scanner matches known-bad patterns. A DAST tool fires requests at endpoints. RAPID's agents model intent, which is how they surface the classes of flaws those tools were never designed to detect: broken access control, insecure direct object references, privilege escalation and business-logic vulnerabilities, alongside the OWASP Top 10 and framework-specific exposures. Every finding is mapped to severity and category, so your team sees risk at a glance.

What Delayed Remediation Is Costing You

  • In 2025, 61% of breaches exploited a vulnerability for which a patch already existed.
  • Attackers weaponize a disclosed vulnerability within 48 hours. The industry average fix cycle for critical application vulnerabilities is roughly 54 days.
  • Of all known vulnerabilities, 45% are never remediated.
  • Modern SAST tools produce false-positive rates as high as 91%, burying real logic flaws under noise that teams must triage by hand before any fix can start.
  • The average financial services breach now costs $5.56 million.

Three Remediation Capabilities Your Scanners Don't Have

1. Only Confirmed, Exploitable Findings Reach Your Developers

Before any fix is proposed, RAPID validates that a finding is reachable and exploitable in your code, then ranks it by business risk. The false-positive noise that stalls triage never lands in an engineer's queue. RAPID also validates before it generates: it does not spin up test cases or proof-of-concept exploits the moment a candidate vulnerability is identified. Your developers spend their time on issues that matter, not on clearing scanner alerts.

2. Fixes Are Tested Before and After, Coordinated Across Files and Gated by a Human

Before touching code, RAPID guides a deterministic baseline test run to capture current behavior, so every fix is measured against a known state. Specialized agents then coordinate the change across multiple files into a single reviewed patch, creating new files where needed, backed by adversarial review and severity-scaled self-correction. If any part of a fix cannot be fully applied, RAPID says so; it never claims a fix it did not complete. After patching, it prompts a retest to confirm the vulnerability is closed and existing functionality is intact. Nothing merges without human sign-off.

3. Every Fix Arrives with the Evidence Auditors Ask For

Each finding and fix carries a full reasoning trace: what was found, why it is exploitable, how it was fixed and how it was verified. Release is governed, with rollback if anything drifts. Auditors are asking harder questions: 65% of organizations lack confidence their vulnerability program would pass a regulatory audit. RAPID produces the trail that closes that gap as a by-product of doing the work.

The result is a smaller backlog, reduced manual triage effort and a faster path from discovery to remediation.

Built for the Code Nobody Wants to Touch

Legacy core banking technology costs the industry $50 billion a year in maintenance, lost revenue and penalties, and much of that code stays vulnerable because regression risk has historically blocked change. RAPID's pre-validated baseline and post-validation retest make it materially safer to remediate in legacy and core systems. This allows security and engineering teams to address risk in legacy systems that have traditionally remained untouched because the cost of getting a fix wrong was too high.

How It Runs

RAPID's Continuous Code Investigation Pipeline has five stages and runs continuously against your backlog:

1. Identify. Reasoning-based triage that separates real threats from scanner noise.
2. Pre-Validate. A deterministic baseline test that captures current behavior before code is touched.
3. Remediate. AI code-level patching across files, delivered as a single reviewed patch.
4. Post-Validate. A retest that confirms the fix holds and functionality is intact.
5. Release. Governed rollout, rollback if anything drifts and an audit-ready reasoning trace.

Because it works down existing backlogs autonomously and continuously, with a human approving every merge, RAPID is built for exactly the year-old backlog most teams have stopped looking at.

Who Should Be Looking at This

If your team is delaying or unclear on code fixes, sitting on a growing backlog or has ever said "we'll patch it next sprint," RAPID was built for you.

Contact your Synechron account representative to schedule a walkthrough of your codebase.

The Author

Aaron Momin
Aaron Momin

Chief Information Security Officer

Aaron is Synechron’s Chief Information Security Officer. He oversees the execution of Synechron's worldwide information security strategy and information security program. Aaron possesses nearly three decades of extensive experience in cyber risk, IT risk, information security, and business continuity planning. He most recently served as the Chief Information Security Officer at Certinia. Over the years, Aaron has also held significant positions at prestigious global consulting firms. He was a Managing Director at PwC and held managerial roles in security at both Ernst & Young and Accenture.

Eklove Mohan
Eklove Mohan

Senior Director

Eklove Mohan is a Senior Director in the North America CTO office at Synechron. His work focuses on application security, agentic AI systems, cloud computing, and enterprise architecture. His recent work includes designing AI-integrated technical architectures for financial services spanning claims, fraud, and underwriting, combining real-time and batch processing with generative AI and agentic workflows. Eklove writes on emerging topics at the intersection of agentic AI, LLM security, and enterprise-grade AI adoption. He is based in Virginia, USA.