Code security

Review every pull request across the software you ship.

ThreatMind automatically reviews pull requests with SAST, SCA, infrastructure-as-code, secret, CI/CD pipeline, and malware scanning, then uses AI AutoFix to generate reviewable code fixes for supported findings in under 10 minutes.

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Automatic PR review SAST + SCA + secrets IaC + pipelines + malware

ThreatMind workspace

Automatic PR reviewpayments/api · PR #248

Live context

Checks6 / 6

Findings9

Fixes3

Analysis activityRunning SAST, SCA, and secret checksReviewing IaC and pipeline definitionsScanning package changes for malware

High-signal findingAuthorization bypass in project export

SASTSource verifiedFix generated

Automatic security review on every pull request SAST, SCA, IaC, secret, pipeline, and malware signals in one workflow AI AutoFix turns supported findings into reviewable fixes

Six layers of PR security

One pull request. Six layers of review.

ThreatMind reviews first-party code, open-source dependencies, infrastructure definitions, committed secrets, CI/CD pipeline changes, and package integrity together. ThreatMind AI then triages every signal in product context, cutting noise, escalating what is reachable, and running a business-logic review pass no generic scanner can.

Automatic pull-request review

Review each pull request as part of the development workflow across GitHub, GitHub Enterprise, GitLab, Bitbucket Cloud and Data Center, Azure Repos, and AWS CodeCommit. ThreatMind AI triages every signal against product context and flags business-logic risks in the change while it is still easy to understand and fix.

Static application security testing

Use SAST to trace insecure data flows, dangerous APIs, injection risks, authorization weaknesses, secrets, and other vulnerabilities in first-party code.

Software composition analysis

Use SCA to identify vulnerable open-source dependencies and understand which package changes introduce known software supply-chain risk.

Infrastructure-as-code security

Review infrastructure definitions for insecure defaults, exposed services, excessive permissions, missing encryption, and risky cloud configuration before deployment.

Secret scanning

Detect credentials, tokens, and keys committed to the repository. Evidence is redacted, so the finding shows where the secret lives without ever storing or displaying the secret itself.

CI/CD pipeline security

Review GitHub Actions and CircleCI workflow changes for risky triggers, injection paths, excessive permissions, and unpinned dependencies before the pipeline runs them.

Malware and package integrity

Scan new and changed dependencies for malicious packages, suspicious installation behavior, and supply-chain indicators before they enter the build. Coverage extends to AI/ML ecosystems, including Conda, R, and Hugging Face model artifacts.

AI AutoFix

Turn supported high-confidence findings into reviewable code changes, inspect the unified diff, and prepare the pull-request workflow in less than 10 minutes.

How it works

From product context to security action.

A deliberate workflow keeps the scope, evidence, and next step connected.

Connect the repository

Connect the repository and enable automatic security review for new pull requests and branch changes.

Run six review layers

ThreatMind runs SAST, SCA, IaC, secret, pipeline, and malware scanning, then correlates the evidence with the code and product context.

AutoFix inside the PR workflow

Generate a reviewable code fix, update the pull request, create tracked work, or retain the security decision in history.

Evidence to action

A single security decision across code, dependencies, infrastructure, and packages.

ThreatMind keeps every scanner signal attached to the repository, branch, pull request, source location, finding, and remediation workflow.

Automatic pull-request status with review findings
Every scanner signal triaged by ThreatMind AI before it reaches your team
SAST evidence linked to the affected source location
SCA and malware signals attached to dependency changes
Secret findings with redacted evidence and match location
Pipeline findings tied to the workflow definition that introduced them
IaC findings connected to the affected resource definition
AI-generated fixes presented as unified diffs

Built for multi-repository workflows — GitHub Enterprise, Bitbucket Data Center, and AWS CodeCommit are supported too

GitHubGitLabBitbucketAzure ReposAWS CodeCommit

See code security in ThreatMind.

Walk through the workflow with your product, team, and security priorities in mind.

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