Find novel vulnerabilities
with the best of all models
Devin reasons across complex codebases
to find novel vulnerabilities, using the best models
Devin finds the vulnerabilities other tools miss, validates that they are actually exploitable
under your threat model, and writes remediations at scale

Frontier-model scanning, prioritization grounded in your environment, and autonomous remediation
Devin reasons across complex codebases
to find novel vulnerabilities, using the best models
Findings are reproduced in a sandbox for exploitability and rated by what would actually cause damage
In the same platform, Devin writes the fix, tests in its own computer, and opens the PR for review
When SonarQube or Fortify or Veracode flags an issue, Devin automatically analyzes and fixes it, leaving engineers to review the patch. Now, ~70% of vulnerabilities are resolved automatically
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Devin finds novel vulnerabilities including business logic flaws and chained exploits, using the best of all frontier and specialized cyber models
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Devin Review flags security issues with every diff, so vulnerabilities are caught and fixed before they reach production
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Devin stands up your app, safely reproduces each finding, writes the patch, and opens a remediation PR for review
Devin takes in and deduplicates findings, then verifies and prioritizes based on exploitability
Devin Security finds, validates, and fixes security vulnerabilities in your code. Instead of matching your code against a fixed list of patterns, it launches a team of Devin agents that read your code the way a security engineer would - reasoning about how data flows, whether an attacker can actually reach a vulnerable line, and whether several small issues combine into a real exploit.
A scan is an orchestrator agent that launches and coordinates a series of child agents, each doing one part of the security work. There are three core phases and two optional ones:
(1) Threat modeling and matcher creation. The threat model is based on a map of your systems, services, network policies, and data flows. Devin drafts it from your code and infrastructure, and your team corrects what it can't see. It drives better scans, real prioritization, and re-scoring of findings from your other tools.
(2) Investigation. Multiple agents run in parallel, one per batch. Each reads the real source code around its signals and decides which are genuine vulnerabilities. This is where the depth comes from - the signals only point agents at code; the agents are told to look past them and trace issues across files.
(3) Aggregation and triage. One agent combines all findings, removes duplicates, attaches likely owners, composes cross-file attack chains, and assigns each finding a priority.
(4) Runtime validation (optional). If your scan profile enables it, agents stand up your app and safely reproduce top findings to confirm they're actually exploitable.
(5) Report (optional). If your profile enables it, an agent compiles a shareable report of the results. Report templates can be customized.
Running many investigation agents in parallel is what lets a scan apply a security engineer's depth to every part of a codebase without taking weeks.
Fewer false alarms, with proof. Every candidate must pass a strict reachability-and-impact check before it's flagged, and (when enabled) runtime validation reproduces it against a live build. What reaches your team is evidence, not a queue of "maybes" to hand-triage.
Vulnerability classes scanners miss. Because agents reason step by step, they find logic flaws and chained exploits — where several individually low-severity issues combine into one real threat. Pattern-based tools can't reach these.
The fix, not just the ticket. You can hand any finding back to Devin to open a policy-compliant pull request, and the next scan checks whether the fix actually resolved it.
Coverage at scale. The parallel architecture lets a single program scan across a large repository estate, and follow-up scans only look at what changed — so continuous coverage stays affordable.
Devin stands up your app in its own isolated machine and safely reproduces the finding there. Each finding comes back confirmed, false positive, or flagged for human review, with logs and screenshots attached.
Yes. You can give Devin access to your existing scanners and instruct it to run or consume them—today this is done through the profile feature via prompting and an API integration. Devin can then help with validation, deduplication, attack-chain composition, prioritization, and remediation. Scan profiles can be customized with specific orderings and instructions for handling various scanners.
Devin Security is additive—more coverage is always better. It helps you surface and do more than traditional scanners are capable of. Over time it may replace some legacy SAST or DAST workflows once you've proven the value.
Devin Security is model-neutral: it draws on models from every major lab and our own, and routes intelligently to optimize cost-performance. In Deep mode, scans also use frontier cyber models.
You can absolutely use a Devin workflow for narrow security tasks. The difference is architectural: skills are prompts, while Devin Security is an orchestration layer of Devins coordinated through an agentic map-reduce architecture that reasons across an entire codebase - often the only way to know whether something is trustworthy is to consider how it's actually used across the repo. Devin Security gives you dynamic repo slicing, parallel investigation, completion management, cost-aware batching, incremental scans, reducer-based dedupe and prioritization, optional runtime validation per finding, scan profiles, and a finding lifecycle that connects to Devin remediation.