.svg)
HEAD-TO-HEAD COMPARISON
Heeler vs Cycode.
Heeler is an end-to-end Agentic Development Security platform — one context engine across code, dependencies, runtime, and cloud that prioritizes by real exposure and delivers deterministic, CI-validated remediation proven green across the application. Cycode is scoped to CI/CD and SCM supply-chain posture.
EXECUTIVE SUMMARY
Built for the AI SDLC, across the application.
Heeler runs the whole loop — Prevent, Fix, Operate — on one context engine that unifies code, dependencies, runtime, and cloud, with its own detection, runtime-aware prioritization, and fixes it builds and repairs in your CI until green across SAST, SCA, secrets, supply chain, and agent files. Cycode is scoped to CI/CD pipeline and SCM supply-chain posture with third-party ASPM aggregation; its production runtime context is correlated and ingested, native only at build time.
THE FUNDAMENTAL DIFFERENCE
Heeler runs one context engine across code, dependencies, runtime, and cloud.
Heeler owns the full loop on that engine — its own detection, deterministic CI-validated remediation proven green, sensor-less production-runtime observation, and runtime-verified closure. Cycode overlaps on native code detection, gen-time MCP guardrails, exploitability-aware prioritization, and agentic workflows, but its production runtime is correlated and ingested (native only at build time) and its fixes are generated, human-reviewed PRs. The divergence: how a fix is proven (a real build + CI repair vs a generated, human-reviewed PR), whether production runtime is observed or correlated and ingested, whether the application's endpoint attack surface is discovered from source, and whether closure is verified in production.
CYCODE
Complete ASPM + agentic development security
Native scanners, supply-chain depth, agentic autonomy.
- →Native scanners (AI-SAST with a deterministic core + agentic reasoning, SCA, secrets, IaC, container) + a Context/Risk Intelligence Graph for exploitability-aware prioritization
- →Signature CI/CD pipeline and SCM security: least-privilege + insider-threat anomaly detection, and Cimon — an eBPF build-runner hardening agent with SLSA provenance and a runtime-observed build SBOM; plus source-code-leak detection
- →MCP-based AI-guardrails (intercept prompts/file-reads/MCP-tool-calls), Maestro agentic workflows that generate fix PRs, and ConnectorX aggregation across 100+ third-party tools
- →Production runtime/cloud context is correlated/ingested (no native prod runtime agent; native eBPF is build-time only); fixes are generated PRs gated by review, not built and CI-repaired to green; no source-based endpoint discovery
HEELER
Modeled around the running service
Prevent, Fix, and Operate on one runtime-aware model.
- →One context engine across six dimensions (code, cloud/runtime, business, ownership, threat, agent), sensor-less and read-only — runtime exposure is a native input
- →Its own detection — SAST, build-graph SCA (14 ecosystems, GitHub Actions first-class), validated secrets, agent-file governance — plus an MCP server, Agent Skills, and a CLI
- →Prioritizes by runtime reachability and internet exposure; remediation is built in a sandbox and repaired in your CI until green, committed into the PR
- →Guardrails gate new risk at the PR; workflows operate to a runtime-verified close with per-finding SLOs
VERDICT FRAMEWORK
Side-by-side, with a verdict per row.
Five states. Heeler-leaning where Heeler advances; explicit when Cycode leads; honest about parity.
●
Heeler advantage
Heeler delivers a capability Cycode doesn't, or in a way that changes outcomes.
◐
Heeler edge
Both deliver the capability. Heeler's implementation is materially better on a verifiable dimension.
✓
Parity
Both products deliver the capability comparably.
◑
Cycode edge
Both deliver the capability. Cycode's implementation leads on a verifiable dimension.
○
Cycode advantage
Explicit signal that Cycode leads on this row.
Scorecard — 25 capabilities, scoped to code security
| Section | ● Heeler advantage | ◐ Heeler edge | ✓ Parity | ◑ Cycode edge | ○ Cycode advantage |
|---|---|---|---|---|---|
| Prevent | – | 1 | 2 | 1 | – |
| Fix | 2 | 2 | – | – | – |
| Operate | 3 | 3 | 7 | 3 | 1 |
| Total | 5 | 6 | 9 | 4 | 1 |
| Capability | Heeler | Cycode | Verdict |
|---|---|---|---|
| Prevent · stop risk before and as it enters | |||
| Security at AI code generation | Heeler's MCP server hands the coding agent its runtime-aware context as it writes — 30+ read-only tools exposing live SAST, SCA, and secrets findings, endpoint exposure, runtime and deployment risk, guardrail status, and SLO pressure, plus named secure-development prompts — and can trigger Heeler's validated remediation with the right scope. Drop-in Agent Skills and the CLI cover the same surface locally, for Claude Code, Cursor, Codex, and VS Code. | Cycode's AI Guardrails treat the IDE/CLI as a security boundary via AI hooks and a Cycode MCP server — intercepting outbound prompts, file reads, and MCP tool calls to block secret/PII egress and policy violations, and enriching the coding agent with security context and skills before it acts. A comparable gen-time control layer; both companies build for the agentic-development category. | ✓Parity |
| CLI / local developer scanning | The heelercli runs local scans across the full surface — SAST, SCA, secrets (with live validation), license, and malicious-package checks — with non-zero exit for pre-commit and CI, SARIF output, and policy-as-code; plus IDE reach through the MCP server. | Cycode runs its native scanners locally through a CLI and IDE plugins (VS Code, JetBrains), with pre-commit hooks that block secrets and findings before they're committed, plus inline PR and terminal findings. A comparable local and IDE developer surface. | ✓Parity |
| PR guardrails & policy enforcement | Block / Warn / Observe guardrails post a native status check on GitHub, GitLab, Bitbucket, and Azure DevOps and gate PRs on new dependency vulnerabilities, dependency hygiene, SAST, secrets, and SLO breaches — scoped by runtime context (enforce only on Tier-1, production, or internet-facing services) — with a validated fix committed straight into the PR branch. Block relies on SCM branch protection to enforce. | Cycode gates pull requests with detect / block / monitor policies, PR status checks, and branch protection across GitHub, GitLab, Bitbucket, and Azure DevOps, and can auto-open a fix PR for some finding types. PR gating; enforcement keys on policy and severity rather than a runtime-exposure scope, and it opens a suggested fix PR rather than committing a fix validated by a build into the branch. | ◐Heeler edge |
| IaC pull-request guardrails | Heeler evaluates the Infrastructure-as-Code findings introduced by a pull request instead of failing a change because of pre-existing repository debt. It returns a native source-control check controlled by program policy: Observe records the violations and the decision that would have been made, Warn reports them without preventing merge, and Block fails the check so repository rules can require it. The same policy can move from observation to enforcement without creating separate rules or CI logic. | Cycode can block Infrastructure-as-Code changes using code-to-cloud context in the policy decision. | ◑Cycode edge |
| Fix · resolve findings — code and dependencies | |||
| SAST autofix | Deterministic, strategy-matched transforms (Parameterize / Escape / Allowlist / Path-Normalize) anchored to the exact source-to-sink flow, precomputed per finding on every scan, confidence- and effort-scored, and delivered as PRs validated the same way as dependency fixes (sandbox build + CI repair). Findings needing an architectural change get written guidance instead. | Cycode's Remediation Agent (Maestro) generates context-aware code fixes for SAST findings and can open a pull request autonomously within a workflow, or surface an AI-suggested fix the developer applies in one click. AI-generated and human-reviewed, gated by confidence thresholds, rather than deterministic transforms proven by a build. | ◐Heeler edge |
| SCA autofix (upgrades) | Deterministic, multi-signal upgrade selection over the resolved graph — Heeler picks the version that clears the most risk with the least disruption (no new known vulnerabilities, proven adoption, cleared minimum-age cooldown), and for transitive vulns finds the smallest bump to the direct ancestor you control (npm, Go, Cargo). Every fix is built in a sandbox and repaired through your CI until green before merge. Auto-fixable across Java, Go, JavaScript, Python, and C#. | Cycode remediates open-source vulnerabilities with one-click PR suggestions (via PR scan, CLI, or IDE) and bulk remediation across many instances. It opens a suggested upgrade PR rather than selecting the version with multi-signal analysis and building and CI-repairing the change to green before merge. | ◐Heeler edge |
| Validated, merge-ready fixes (build + CI repair) | Heeler validates every fix twice: a real build in an isolated sandbox with your project's toolchain before the PR (mvn/Gradle, npm/pnpm/Yarn, pip/uv/Poetry, go build, dotnet), then — once the PR is open — it runs your CI and repairs its own build/test failures with up to five follow-up commits until green, or hands off with an explanation. Draft PR if the sandbox build didn't pass; human review, no auto-merge. | Cycode's agents generate fixes and open pull requests, with the safety gate being human review and confidence thresholds, and its Remediation Agent claims fixes “without breaking functionality.” The docs don't describe building the project in a sandbox and running your CI to repair the fix's own build/test failures until green — validation is human PR review, not a build-and-repair loop. | ●Heeler advantage |
| Policy-managed remediation memories | Heeler stores administrator-approved remediation guidance as memories in program policy and scopes each memory to an organization or repository. On later remediation runs, the Remediation Agent retrieves the applicable memories and applies the repository’s conventions and constraints when generating a fix. The guidance is centrally governed and reusable; it is not a one-off prompt, a triage-suppression rule, or generic model memory. | No documented capability. | ●Heeler advantage |
| Operate · detect, prioritize, and run the program | |||
| SAST detection | Path-aware, interprocedural source-to-sink taint analysis across functions and files — plus structural (Graphscan) and heuristic methods — from Heeler's own engine, with detection rules adapted per codebase, automatic reachability/exposure triage, and step-by-step data-flow proof. | Cycode's native AI-SAST runs a deterministic engine (a low false-positive core), an AI layer that writes repo-specific deterministic rules, and Agentic Code Security that reasons from the code — building a threat model, catching logic, authorization, and cross-file/cross-service flaws, and validating exploitability before surfacing a finding. A comparable, context-aware static engine. | ✓Parity |
| Dependency vulnerability (CVE) detection | Build-graph SCA across 14 ecosystems that resolves the full direct-and-transitive graph itself from your manifests — and from committed lockfiles when present, without requiring one or changing your build — matched with CVSS, EPSS, and known-exploited signals, covering first-party and bundled dependencies too, with GitHub Actions as a first-class ecosystem. | Cycode's native SCA identifies components through deep manifest and binary analysis, resolves direct and transitive dependencies, cross-references CVE databases, flags license risk, and pairs reachability with AI exploitability analysis to focus on what's exploitable in context. Comparable dependency coverage, and it can also ingest third-party SCA findings. | ✓Parity |
| Secrets detection & validation | First-class secrets: full git-history scanning across all branches with commit attribution, active live validation (read-only calls to the issuing provider; an active secret is weighted as maximal impact), offline structural validation, and 700+ rules across 20+ languages; contained and gated at the PR. | Cycode's Secrets Engine natively detects hardcoded and leaked secrets across code, git history, build logs, IaC templates, documentation, and productivity tools (Slack, Confluence, Jira), validates their status, blocks at the PR and pre-commit, and underpins its non-human-identity security. Comparable first-class secrets detection with validation and broad location coverage. | ✓Parity |
| Dependency reachability & noise reduction | Heeler treats a dependency vuln as reachable only when two independent checks agree: runtime reachability (the library is loaded in a running deployment) and static call-graph reachability to the vulnerable functions across six ecosystems (Go, Java, Python, JS/TS, Rust, Ruby). Unreachable findings are auto-mitigated; elsewhere it uses runtime reachability and errs toward reachable. | Cycode pairs static reachability (is the vulnerable function called) with bulk AI exploitability analysis (do the conditions for exploitation actually exist in this app and environment), running exploitability verdicts across many SAST/SCA findings at once to cut the backlog to the exploitable few. A context-reasoned noise-reduction approach. | ✓Parity |
| Endpoint & API attack-surface discovery | Heeler enumerates every endpoint from source — REST, GraphQL, gRPC, SOAP, and WebSocket, plus the MCP tools/resources/prompts and Spring Boot actuator routes your code exposes — capturing each one's authentication posture and computing internet-accessibility from deployment topology, so your externally reachable, unauthenticated surface is inventoried with no runtime agents or traffic capture. | Not offered. Cycode uses “attack surface” for the AI and supply-chain surface (agents, rule files, pipelines) and treats internet-exposure as a prioritization attribute on a finding, but it doesn't enumerate your application's endpoints and APIs from source with each one's authentication posture and internet-accessibility. | ●Heeler advantage |
| CI/CD pipeline & SCM security | Heeler treats GitHub Actions and reusable workflows as a first-class scanned dependency ecosystem (pin status, provenance, integrity) and gates risk at the PR, but it isn't a pipeline-and-SCM posture product — no least-privilege/access auditing, insider-threat anomaly detection, or build-runner runtime hardening. | Cycode's heritage: SCM and CI/CD posture (least-privilege access auditing, MFA/SSO enforcement, separation of duties, pipeline inventory and misconfiguration), user-behavior anomaly / insider-threat detection, and Cimon — an eBPF build-runner agent that observes process/network/file activity in the build, blocks supply-chain attacks, and produces SLSA provenance and a runtime-observed build SBOM. | ◑Cycode edge |
| Cloud, runtime & business context | Heeler builds its own model of where code runs — containers, VMs, and serverless fingerprinted across AWS, GCP, Azure, Kubernetes, and Vercel, each deployment mapped to the exact running changeset, internet-accessibility auto-detected, service tier (1–4) and prod/non-prod classified, service-to-service and identity edges resolved, and ownership resolved to the owning team, with Tech Lead and Security Lead points of contact — all read-only and sensor-less. This context is what makes exposure, prioritization, and routing real. | Cycode's Context/Risk Intelligence Graph correlates code, pipelines, secrets, and cloud resources and maps code to its exposure in production — but the production runtime and cloud signals are correlated and ingested (cloud is a connector category), not observed by Cycode. Its only native runtime telemetry is Cimon on the CI/CD build runner; there is no native production runtime or cloud agent, so the deeper deployment model is inferred rather than observed. | ◐Heeler edge |
| Risk-based prioritization | Heeler Risk (Urgent / Plan / Defer) ranks SAST and SCA findings by real exposure. For SCA, a vuln must clear a gate: reachable (runtime-loaded, plus a call-graph path where supported) AND internet-exposed (an active deployment on internet-reachable compute) AND not mitigated — fail any and it Defers, however high the CVSS. For SAST, exposure is path-driven from an internet-facing entry point, behind auth, touching sensitive data. Both are weighted by service tier and threat (KEV/EPSS; CWE class), with a per-finding SLO, re-scored continuously. | Cycode's graph prioritizes with exploitability (an AI Exploitability Agent), static reachability, internet exposure, business criticality, data sensitivity, and ownership/blast-radius — claiming to surface the critical few and cut developer noise. A comparably sophisticated, context-rich prioritization engine (though EPSS and CISA-KEV aren't named among its signals). | ✓Parity |
| Multi-tool / third-party ASPM aggregation | Heeler is its own detection-and-fix engine. It brings native SAST, SCA, secrets, and agent-file analysis and exports findings (SARIF, API), but unifying, normalizing, and deduplicating the output of many other vendors' scanners is not its focus. | Alongside its native detection, Cycode's ConnectorX ingests findings from 100+ third-party tools (SAST/SCA/DAST/cloud/infrastructure scanners, SCMs, CI/CD, ticketing), normalizing, deduplicating, correlating, and re-scoring them in one graph — an ASPM aggregation layer over the tools you already run. | ○Cycode advantage |
| Agent-file & AI-supply-chain governance | Heeler inspects pull-request changes to agent instructions, skill files, hooks, subagents, and MCP configuration, including CLAUDE.md, AGENTS.md, and SKILL.md. It combines deterministic checks, LLM-based intent analysis, and analysis of external references to identify prompt injection, tool poisoning, unsafe command execution, secret access or exfiltration, permission bypass, and related agent-control risks. The evidence and verdict are returned through Observe, Warn, or Block before the changed artifact is trusted by coding agents. | Cycode discovers AI rule files, skill files, and MCP configurations and surfaces risk and provenance context. Its documented capability centers on inventory and governance rather than an explicit pull-request verdict for malicious or unsafe changes to those files. | ◐Heeler edge |
| SBOM & dependency inventory | A live dependency inventory (with OpenSSF hygiene scoring) and CycloneDX SBOMs at five scopes — including runtime SBOMs per running service and per deployment, built from real runtime context — alongside global, application, and repository scopes. | Cycode natively generates (and ingests) SPDX and CycloneDX SBOMs kept current with code changes, and — via Cimon on the build runner — a runtime-observed build SBOM that captures what actually executed during the build (dynamically fetched deps, vendored and statically-linked code). Comparable inventory breadth, with a build-time runtime SBOM. | ✓Parity |
| Automated response workflows & routing | A standing when-this-then-that engine across the whole estate: one trigger (new finding, fix available, compromised dependency, new secret, at-risk agent file, SLO expiring, PR merged with unresolved guardrail violations) → AND-combined conditions → up to three chained actions that share context. Actions span messaging (Slack/Teams/Google Chat/email), ticketing (Jira/Linear/GitHub/Shortcut, de-duplicated), and domain actions (Fix with Heeler Agent, Update SLO Override, Generate SBOM, Webhook), routed to the owning team, with a plain-English builder. | Cycode's Maestro orchestrates agentic workflows (trigger → filters → ordered agent flow → human controls) that triage, validate exploitability, generate fix PRs, and rebuild containers, plus Remediation Campaigns for scoped, owner-assigned, due-dated remediation with burn-down tracking and ticketing. Comparable workflow automation and routing. | ✓Parity |
| SLOs & runtime-verified closure | Every tracked finding under an SLO policy carries a per-band (Urgent / Plan / Defer) SLO clock; SLO-expiring events trigger workflows, and an Update SLO Override action can extend a due date automatically. Findings run Active → Fixed → Deployed, and closure is runtime-verified — a fix reaches Deployed only once every running deployment confirms the vulnerability is actually gone, not merely merged. | Cycode tracks SLAs (workflows trigger on missed SLA; escalation templates) and runs Remediation Campaigns with due dates and burn-down, and auto-resolves findings a subsequent scan no longer detects. SLA and campaign tracking; closure is a resolved violation state / re-scan, not gated on every running deployment confirming the vulnerability is actually gone. | ◐Heeler edge |
| Sensitive-data inventory | Heeler analyzes application source to identify the sensitive data types handled by the code and records them in the application catalog. Each data type is connected to the repositories, services, APIs, and owning teams that process it, together with business criticality and available deployment or exposure context. A reviewer can move from a data type to the applications and interfaces that handle it and evaluate that data-handling risk with the same ownership and runtime context used for other application-security findings. | No documented capability. | ●Heeler advantage |
| Infrastructure-as-Code findings | Heeler evaluates Infrastructure-as-Code against policy and creates a persistent finding for each violation. The finding retains the affected file or infrastructure resource and links it to the repository, application, owning team, business criticality, and any connected cloud or runtime object. The same finding is used for prioritization, lifecycle tracking, workflow routing, pull-request guardrails, and remediation instead of remaining a one-time CI scanner result. | Cycode scans Infrastructure-as-Code across development and code-to-cloud workflows and provides contextual findings and automated remediation. | ◑Cycode edge |
| GitHub audit-log behavioral checks | Heeler ingests the GitHub organization audit log for each connected organization and evaluates defined patterns across the resulting source-control events. A match creates a native finding that retains the actor, action, affected repository or organization, timestamp, and matching event context. The finding enters Heeler’s ownership, prioritization, investigation, workflow, and lifecycle tracking rather than remaining a searchable or exported log event. | Cycode continuously monitors GitHub audit events and alerts on suspicious activity such as anomalous locations, unusual download or clone behavior, access changes, and security-control modifications. Those events are correlated with source-code and pipeline posture. | ◑Cycode edge |
| OpenSSF Scorecard repository health | Heeler records the repository’s OpenSSF Scorecard result and each check outcome on the repository object in the catalog. The same repository view links the signal to applications, ownership, vulnerabilities, dependency health, provenance, deployment, and exposure context. Teams can inspect which Scorecard checks reduced the result and evaluate repository-maintenance risk in relation to the applications that use the repository instead of treating the score as an external badge. | No documented capability. | ●Heeler advantage |
WHERE HEELER ADVANCES
Where the two platforms diverge.
Parity on the code-security core, with a handful of real divergences.
01
Fixes proven by a real build and CI, not generated and human-gated
Both platforms auto-fix — Cycode's Maestro Remediation Agent generates context-aware fixes and opens pull requests, gated by human review and confidence thresholds. Heeler goes further on proof: it builds every fix in an isolated sandbox with your toolchain, and once the PR is open runs your CI and repairs its own build/test failures with follow-up commits until green — or opens a draft PR with an explanation. A fix asserted “without breaking functionality” is not the same as one demonstrated to build and pass tests.
02
Production runtime observed, not correlated from ingested tools
Cycode talks code-to-cloud and “Prompt to Runtime,” but its production runtime and cloud context is correlated over the graph and ingested from connectors — its only native runtime telemetry is Cimon on the CI/CD build runner, not production. Heeler builds its own deployment model sensor-less: each deployment mapped to the exact running changeset, internet-accessibility, service tier, and ownership — exposure and prioritization run on runtime Heeler observes itself.
03
The endpoint and API attack surface, discovered from source
Cycode uses “attack surface” for the AI and supply-chain surface and treats internet-exposure as a finding attribute, but it doesn't enumerate your application's endpoints and APIs from source. Heeler inventories every route — REST, GraphQL, gRPC, SOAP, WebSocket, plus MCP and actuator interfaces — with each one's authentication posture and internet-accessibility, so your externally reachable, unauthenticated surface is a first-class object, not an attribute.
04
Runtime-verified closure, not SLA tracking and re-scan
Cycode tracks SLAs and campaign burn-down and auto-resolves what a re-scan no longer detects. Heeler moves each finding Active → Fixed → Deployed and closes it only when every running deployment confirms the vulnerability is actually gone — per-finding SLO clocks driving the program to proof-in-production, not a violation marked resolved.
05
One context engine code-to-cloud, not breadth stitched from correlation and ingestion
Cycode's supply-chain coverage spans pipeline security, source-code-leak detection, and third-party ASPM aggregation. But its production runtime is correlated and ingested, and its fixes are generated PRs gated by review. Heeler is a single context engine that unifies code, dependencies, runtime, and cloud — detecting natively, observing production itself, and delivering validated fixes and runtime-verified closure as one seamless model, not a runtime picture stitched from correlation and ingestion.
See Heeler on your codebase.
A demo runs Heeler against your real repos and cloud — native detection across the surface, the runtime map, the prioritization, the validated remediation PRs, and the agent-file catalog. Cycode and Heeler overlap on the code-security core; where it counts, we'll show what fixes proven in CI, natively-observed runtime context, source-based endpoint discovery, and verified-in-production closure add on top.
