Customers routinely find and fix exploitable vulnerabilities missed by scanner-first workflows within 24 hours.
Hacktron vs Snyk
Hacktron, the AI-native alternative to Snyk
Snyk started as a deterministic SAST scanner, and bolted on AI to improve rules. Hacktron is AI-native from the start, and catches exploitable PR vulnerabilities and automates deeper code-level validation where other tools leave gaps.
Most Hacktron customers find and fix real vulnerabilities missed by scanner-first workflows within 24 hours of onboarding.
How Hacktron compares to Snyk
Hacktron is built for the moment Snyk-style scanning becomes too noisy or too broad: the pull request where a vulnerable change can still be fixed cheaply.
Top-ranked CTF competitors, DEF CON-published researchers, and leading bug bounty hunters turn new attack patterns into real improvements.
The same methodology has found zero-day vulnerabilities in Next.js, Grafana, OpenAM, GitHub, GitLab, and BeyondTrust.
| Pricing | Hacktron Pro — Unlimited Developers $40/developer/mo | Snyk Team — Up to 10 Developers From $25/developer/mo | Snyk Enterprise Contact sales |
|---|---|---|---|
| Included usage | 50 PRs per developer and unlimited scans per PR, unlimited repos | 1,000 code tests | Custom |
| Overage / add-ons | $1 per additional PR after included usage | Stops working, upgrade required | Custom |
| Pentest | Credit-based — from $2,000 for most applications | No first-party pentest product | No first-party pentest product |
Where Hacktron is deliberately sharper than Snyk
Accuracy and Depth
Hacktron
Reduces false positive noise while surfacing vulnerabilities that other scanners miss, excelling in both precision and recall.
Snyk
Teams get inundated with false positives, making security review a tedious chore rather than a valuable signal.
Repository context
Hacktron
Indexes repositories and call graphs so review can reason about auth, trust boundaries, data flow, and product-specific rules.
Snyk
Uses rule-based code analysis and SAST workflows, leading to false positives and syntactic findings that miss crucial context.
Finding lifecycle
Hacktron
Findings can be addressed from GitHub, Slack, Linear, and Jira, with auto-resolution when the patch lands.
Snyk
Can comment on pull requests and gate merges, but AppSec teams manually address findings outside the PR conversation.
Gets sharper with every review
Hacktron
Learns from triage comments and project rules, so the signal gets more tuned to your attack surface over time.
Snyk
Relies on teams tuning policies, writing custom rules, and manually filtering and prioritizing findings.
Meets your development velocity
Hacktron's reviews are fast yet thorough, only surfacing high-signal issues so that security does not slow down development.
Exploitability focus
Hacktron prioritizes whether a changed path can be exploited in your application, not only whether it matches a weakness category.
Whitebox depth
Hacktron can perform deeper white-box pentests on a full project when a point-in-time pull request scan is not enough.
See the difference between scanner results and PR security review
| Area | Hacktron | Snyk |
|---|---|---|
| Analysis model | AI-native security reviewerHacktron reads a pull request with codebase context, call graphs, and project rules, then decides whether the changed path is actually exploitable. | Developer security scannerSnyk Code is a SAST product inside a wider platform, using semantic analysis to produce issues that teams review and prioritize. |
| Signal quality | Exploitability before categoryHacktron prioritizes real attack paths and includes enough context for engineers to reproduce, understand, and fix the issue. | Scan result before proofSnyk PR checks identify newly introduced issues, but teams still decide which scan findings are reachable, exploitable, or worth blocking. |
| Team learning | Adapts to your appHacktron learns from triage comments, trusted paths, ignored conventions, and .hacktron/rules.md so signal follows your application threat model. | Policy and issue tuningSnyk gives teams policy, severity, and issue-management controls across the platform, which is useful but broader than PR-specific learning. |
| Remediation | Reviewer-style fix contextHacktron explains the vulnerable path in the PR, gives a fix prompt, and closes fixed findings automatically after the remediation commit. | Issue and fix guidanceSnyk can provide fix guidance and pull request checks, but the finding often still needs translation into the exact product behavior changed by the PR. |
| False positives | Built to reduce noiseHacktron is designed to reduce noisy review comments by checking exploitability before interrupting the pull request. | Backlog pressureLarge scanner programs can create issue queues that become less useful when developers learn which alerts usually do not affect their code path. |
Put exploitability-first review on the next pull request.
Hacktron reviews changes like a security engineer: inline, contextual, and focused on vulnerabilities that can actually ship.
Frequently asked questions
What is Hacktron Review?
Hacktron Review is an AI security reviewer for pull requests. It reads code changes with repository context, reasons about exploitability, and gives engineers actionable findings directly inside GitHub.
How is Hacktron different from Snyk?
Snyk is broad platform coverage across code, dependencies, containers, IaC, cloud, and secrets. Hacktron is focused on the PR review moment: did this change introduce a real vulnerability, and how should the engineer fix it?
Should Hacktron replace Snyk?
Not necessarily. Many teams keep Snyk for scanner coverage and add Hacktron where they need higher-signal reasoning on risky pull requests, especially auth, access control, business logic, injection, and prompt injection changes.
How does Hacktron improve over time?
Hacktron learns from triage comments, project rules, trusted paths, and repeated review cycles. The more your team reviews and responds, the more tuned the signal becomes to your application and attack surface.
Where do findings appear?
Findings appear as inline pull request comments on the vulnerable lines, with proof context and fix prompts. When a follow-up commit fixes the issue, Hacktron can auto-resolve the finding.
What kinds of issues does it catch?
Hacktron is built for exploitable code-level issues like auth and access control flaws, business logic bugs, injection, SSRF, prompt injection, secrets exposure, supply-chain risk, and IaC exposures.
How fast can a team start?
Install the GitHub App, choose the repositories Hacktron should review, and put it on the next pull request. Teams often find and fix real vulnerabilities within 24 hours of onboarding.
Does Hacktron also do pentesting?
Yes. Hacktron can escalate from continuous PR review into deeper code-aware whitebox assessment, with validated findings and report-ready output for higher-risk applications and compliance needs.