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HEAD-TO-HEAD COMPARISON
Heeler vs Wiz Code.
Agentic Development Security vs a CNAPP that extended left into code. One models the service and fixes the code; the other reasons from the cloud in. Here's where each leads, where they're equivalent, and how to pick for the AI SDLC.
EXECUTIVE SUMMARY
Two strong platforms, two centers of gravity.
Wiz Code extends the Wiz Security Graph from the cloud into the repo — SCA, IaC, secrets, malware, CI/CD posture, and a native SAST engine. Its strength is code-to-cloud context: code findings prioritized by cloud exposure and attack path. Within the cloud-risk boundary, Wiz is excellent.
Heeler was built for the AI SDLC, modeled around the service — SAST, SCA, secrets, agent-skill security, guardrails, and runtime-aware risk on one context engine. Its strength is deterministic, CI-validated remediation: it computes the fix, proves it green in your CI, and opens a merge-ready PR for both SCA and SAST.
The short version: Wiz reasons from the cloud down to the code; Heeler models the service, goes deep in the code, and closes the loop with a validated fix. Cloud posture and attack paths? Wiz is hard to beat. The volume of AI-generated code and the cost of remediating it? That's the problem Heeler is built for.
THE FUNDAMENTAL DIFFERENCE
One reasons from the cloud in. The other models the service, and fixes the code.
Both platforms detect vulnerabilities and both correlate code to cloud. The split shows up in where each one's center of gravity sits — and what happens after a finding lands.
WIZ CODE
CNAPP-native, cloud-out
Cloud-first context, extended into the repository.
- →Built on the Wiz Security Graph; correlates code findings to cloud attack paths, identity exposure, and runtime reachability via the Wiz sensor
- →Scanner breadth: SCA/SBOM, IaC (1,000–1,400+ rules), secrets (SLM + validation + full git history), DSPM-in-code, malware, CI/CD posture, native + ingested SAST
- →Remediation = Green Agent produces an investigation, plan, and exact code fix, then hands execution to an external coding agent (Claude Code, Cursor) to write it and open a PR for review
- →Deepest where risk is a cloud toxic-combination; code-fix authoring and validation are delegated to the coding agent, scoped to supported findings
HEELER
Context-engine native, service-modeled, AI-SDLC-built
Modeled around the service — the running application as the atomic unit, then deeper into the code.
- →Models the software, not the cloud infrastructure — multi-SCM, multi-cloud, sensor-less, code fingerprinted to the exact running commit
- →Heeler's own SAST engine — cross-function, cross-file source-to-sink taint over a graph dataflow model; build-emulation SCA across 14 ecosystems; CI/CD modeled as a peer ecosystem at depth-10
- →Remediation = Heeler computes the fix (deterministic, strategy-matched), builds and tests it in your CI, repairs until green, and opens a merge-ready PR — SCA and SAST
- →Treats the coding agent as first-class: injects context at generation, and vets the skills and instruction files the agent loads as a supply chain
VERDICT FRAMEWORK
Side-by-side, with a verdict per row.
Four states. Heeler-leaning where Heeler advances; explicit where Wiz leads; honest about parity.
●
Heeler advantage
Heeler delivers a capability Wiz Code does not, or in a fundamentally different 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.
○
Wiz advantage
Explicit signal that Wiz Code leads on this row.
Scorecard — 31 capabilities, scoped to code security
| Section | ● Heeler advantage | ◐ Heeler edge | ✓ Parity | ○ Wiz advantage |
|---|---|---|---|---|
| Context engine | 1 | 3 | 1 | 0 |
| Prevent | 1 | 4 | 0 | 0 |
| Fix | 3 | 2 | 0 | 0 |
| Operate | 4 | 2 | 3 | 0 |
| CI/CD supply chain | 1 | 2 | 0 | 1 |
| Operational fit | 0 | 1 | 2 | 0 |
| Total | 10 | 14 | 6 | 1 |
| Capability | Heeler | Wiz Code | Verdict |
|---|---|---|---|
| Context engine · the foundation | |||
| Code & dependency context | Cross-function, cross-file, source-to-sink taint from Heeler's own SAST engine — taint + graph dataflow, stable dedup fingerprints, false-positive reclassification, deterministic before/after fix emission. Build-emulation dependency resolution (lockfile optional) across 14 ecosystems; full tree — direct, transitive, first-party, bundled. CI/CD modeled as a peer ecosystem at depth-10. | SCA/SBOM with reachability prioritization via the runtime sensor; native SAST (rule-based + agentic AI reasoning) for 6 languages plus third-party ingestion (Checkmarx, Semgrep, Snyk Code). Cross-function taint depth is achieved via AI reasoning rather than a documented deterministic taint graph. | ◐ Heeler edge |
| Business context | Service tier (Tier 1–4) captures data sensitivity, regulatory scope, and customer-trust impact; set at the application level and cascaded to every service; shared repos inherit the highest tier. Production identification is automated — no manual labeling. | Security Graph ingests business context via resource tags, Projects, Service Catalog mappings, and CMDB data; used by Workflows to route and prioritize. Effective, but tag/CMDB-driven rather than an automated tier-cascade model. | ◐ Heeler edge |
| Ownership context | Automated ownership (Tech Lead, Security Lead, Assignee) cascading application → repo → service → individual dependency; team import/sync from Port, GitHub Teams, GitLab groups; contributor de-dup across identities; highest-contributor fallback. | Security Graph surfaces VCS org/team structures, role bindings, and code-to-cloud ownership; Workflows use it to identify owners and route Issues. Strong at the org/repo level; less granular than a per-dependency RACI cascade. | ◐ Heeler edge |
| Threat context | GHSA (alias-aware GHSA↔CVE), OSV, NVD/CVE (CVSS v3+v4); CISA-KEV + VulnCheck-KEV; EPSS score+percentile; CVSS v4 ExploitMaturity; OSSF Malicious Packages + Scorecard; known-ransomware-campaign flag; behavioral-SAST backstop. | Security Graph threat intel + Threat Intel Center; runtime-confirmed exposure; EPSS/KEV; and the Red Agent — an AI 'intelligent attacker' that validates exploitability with proof and reasoning. Runtime-validated exploitability is a genuine strength. | ✓ Parity |
| Agent context | Skill catalog inventories every agent skill/instruction file in use (skills.md, CLAUDE.md, AGENTS.md, .cursorrules, mcp.json); per-skill inspection of external binaries, shell commands, embedded secrets, outbound calls; safety score per skill mapped to MITRE ATLAS + OWASP LLM Top 10. A first-class dependency class. | AI-BOM inventories AI frameworks (LangChain), models, and IDE extensions (Gemini Code Assist, Copilot, Cursor) and maps them onto the Security Graph to eliminate Shadow AI. Inventories the tools; does not vet the customer-authored skill/instruction files those agents load. | ● Heeler advantage |
| Prevent · stop risk from entering the codebase | |||
| Security at AI code generation | Heeler MCP server + auto-loaded Agent Skills inject org-specific context (vuln details, safe upgrade paths, package impact, runtime exposure, service policy) into the agent's reasoning at the moment of decision — the same graph a PR guardrail reads. One central policy across Claude Code, Cursor, Copilot, Windsurf, Codex, any MCP client. | Wiz Code plugins fire at git-lifecycle boundaries (file save, pre-commit, pre-push) and scan AI-generated output for hardcoded secrets, IaC misconfigs, vulnerable dependencies, and container malware; warn by default, configurable block. Strong boundary enforcement; context is injected post-generation rather than into the reasoning. | ◐ Heeler edge |
| Local pre-commit / CLI | heelercli runs the same policy as CI and the platform: SCA, SAST, secrets, malicious-package and license checks; secret detection runs offline (source never leaves the machine). Callable by humans and agents (heeler check). | WizCLI scans build artifacts (container images, VM images), IaC, and dependencies in CI/CD and locally; push protection for secrets at the command line; OAuth web auth, no service-account secrets. | ◐ Heeler edge |
| Agent skills & MCP at generation | MCP tools (get_vulnerabilities_for_project, get_sast_results_for_file, guardrail_list, service_risk_brief) plus a library of security-authored skills (dependency upgrades, secret handling, malicious-package detection, remediation) reasoning against the live context engine, with org-specific overrides. | Wiz MCP server (GA) exposes the Security Graph and pre-built AI Skills (triage, remediation, investigation, compliance) to external agents; remediation skills run in Claude Code/Cursor. Comparable MCP surface; Heeler's skills are broader at the prevention/generation moment. | ◐ Heeler edge |
| PR guardrails | Block / Warn / Observe with plain-English rule authoring; scoping by global, repo, service runtime context, and branch; diff-only on net-new violations (no penalty for inherited debt); multi-SCM native checks; in-PR Fix Now triggers a validated remediation PR. | Configurable guardrails alert or block by severity at IDE, PR, or CI/CD; graduated gates (block critical, allow lower with recorded exception); findings posted as PR review comments with remediation links. Policy is per-scope configuration rather than plain-English authoring; Fix Now-style in-PR validated remediation is not claimed. | ◐ Heeler edge |
| Software supply-chain prevention (deps) | Layered: malicious/compromised (OSSF feed, block on sight), typosquat detection, minimum package age cooldown (blocks zero-days before they hit advisory feeds), unpinned-dependency and unpinned-Action detection, OSSF Scorecard hygiene — each enforceable as a guardrail; continuous re-evaluation fires workflows when a clean dep is later flagged. | Malware scanning (hash + pattern) extended to repositories; secrets and IaC scanning; Dependency-review-style gating on advisories. Malware detection is strong; the dependency-supply-chain guardrail set (min-age cooldown, typosquat, unpinned) is not documented. | ● Heeler advantage |
| Fix · solutions, not tickets | |||
| Deterministic upgrade selection | Heeler (not the agent) computes the fix: dependency graph + changelog intelligence + breaking-change detection + reachability of called library methods pick the lowest version that clears the CVEs and adds none. For transitive vulns, the smallest first-party ancestor bump that resolves the whole closure. Reproducible — same input, same fix. | Green Agent suggests remediation using LLM reasoning layered on prescribed methodologies; adaptive rather than a deterministic graph+changelog upgrade solver. Version selection is AI-suggested, not computed to a provably-minimal upgrade. | ● Heeler advantage |
| End-to-end SCA autofix (CI repair loop) | The agent creates a branch, applies the upgrade, makes required code changes, and validates through CI iteratively — compilation testing for compiled languages (Java, Go, C#), sandbox execution for interpreted (Python, JS) — looping up to ~5× until lint/unit/integration tests pass, or abstaining to a human. Produces a merge-ready PR with impact, diff, and proof it builds. | Green Agent builds a plan and exact code fix, then creates a PR or sends the issue to an external coding agent (e.g. Claude) that writes the fix; the PR runs the repo's existing CI. Wiz does not claim a Wiz-owned loop that analyzes CI failures, corrects the code, and re-pushes until green. | ● Heeler advantage |
| SAST autofix (validated code fixes) | GA. From the taint path to a merged PR: deterministic, strategy-matched transform (parameterize / escape / allow-list / normalize) anchored to the exact source-to-sink flow — the engine emits the before/after transform; built and tested in your CI, repaired until green or handed to a human; confidence-scored, only high-confidence auto-opens a PR; human review, no auto-merge. | Wiz SAST remediation agents 'generate pull requests for supported findings in seconds'; in-PR #wiz remediate conversational fixes; AI-generated, validated by the AI attacker rather than a deterministic transform + CI-proven re-scan. Scoped to supported findings. | ● Heeler advantage |
| Fixability scoring | Every SCA remediation graded Easy / Medium / Hard up front via breaking-change analysis; Auto-Fixable label for end-to-end agent execution; confidence score on every candidate transform; Remediation Workbench shows environment-wide distribution. | Green Agent attaches a confidence score and suggested severity adjustment to each verdict. Confidence exists; a fix-effort grade and auto-fixable classification driving a remediation workbench are not documented. | ◐ Heeler edge |
| Inline PR fix suggestions | For guardrail violations, Heeler posts the fix as a native GitHub PR-review suggestion block — click-to-commit, on the exact offending lines, multi-line hunks included — so a developer accepts it inline without leaving the review; falls back to commit-and-push when a hunk can't be expressed as a suggestion. Complements the validated merge-ready PRs. | Findings post as PR review comments with remediation links, and SAST remediation agents generate PRs for supported findings; native click-to-commit suggestion blocks on the offending lines are not documented. | ◐ Heeler edge |
| Operate · continuous evaluation and automated response | |||
| Continuous risk / prioritization | Heeler Risk (Urgent / Plan / Defer) recomputed continuously from reachability (function + runtime), internet exposure, downstream service criticality, business tier, exploit maturity, and framework-mitigation checks that suppress CVEs that can't fire in your configuration. | Prioritizes 'toxic combinations affecting business-critical resources first': correlates static findings with runtime exposure, excessive permissions, reachable sensitive data, and network attack paths, validated by the Red Agent. Both are genuinely runtime-aware; different centers of gravity (code vs cloud attack path). | ✓ Parity |
| Secrets detection | Full git-history scanning with per-finding commit attribution; strong live/active validation — per-provider API parsers (AWS, GitHub, GCP, OpenAI, Anthropic, Slack, Datadog, Azure Storage) confirm whether a credential is usable, plus scheduled re-validation so rotated creds are re-checked. Detection is rule- and entropy-based; offline in the CLI. | Also full git-history scanning with live-secret validation; a fine-tuned Small Language Model improves recall on non-obvious secrets in comments, logs, and strings that regex misses — a fair code-security edge. Its extra reach into IaC templates and container images sits outside a code-focused comparison. | ✓ Parity |
| Lifecycle finding states | Active (in code) → Fixed (remediated, not yet deployed) → Deployed (gone from every active deployment); Resolved-Issue view retains MTTR and resolution reason; distinguishes introduced (new dep brought it in) from surfaced (existing code, new advisory). | Cloud Issues and code findings carry status, but a code-finding lifecycle that distinguishes fixed-in-code from gone-from-runtime, and introduced-vs-surfaced, is not documented for Wiz Code. | ● Heeler advantage |
| SLO management | SLO clock starts at first detection (static or runtime) and closes only when Heeler verifies resolution at runtime — not at PR merge; risk-based or CVSS-based strategies; SLO Override when no fix exists; SLO Guardrails block PRs against repos with overdue findings; compliance reporting reflects actual exposure, not ticket state. | Not documented as a native Wiz Code capability; SLA/SLO tracking would come from an integrated ticketing system, not from runtime-verified closure. | ● Heeler advantage |
| Refactor-resilient issue persistence | Cross-scan issue matching survives code movement, file renames, and refactors — the same vulnerability tracked as one issue as code evolves, with commit-level attribution, via stable dedup fingerprints. Avoids the fixed-and-new double-counting legacy scanners produce. | Wiz correlates findings across scans, but a documented refactor-resilient fingerprinting model for code findings is not claimed. | ◐ Heeler edge |
| Automated team & ownership routing | Teams configured once (repos, members, ticketing provider, templates); one workflow fires for all teams and routes each correctly; new repos picked up automatically; missing-team fallback per workflow. Providers: Jira, Linear, Shortcut; messaging: Slack, Teams, Google Chat, Email. | Workflows use Security-Graph ownership (tags, code-to-cloud, Projects, Service Catalog, CMDB) to identify owners and route Issues/Threats; 200+ integrations. Broad routing; ownership is graph/CMDB-derived rather than a per-team config that cascades to dependencies. | ◐ Heeler edge |
| Automated SLO lifecycle | SLO clock starts at first detection, closes when resolution is verified at runtime; SLO Override extends deadlines when no fix exists; SLO Expiring escalation; SLO Guardrails block PRs against overdue repos; severity-based overdue thresholds. | Not documented as a native Wiz Code capability. | ● Heeler advantage |
| Template-driven ticket content | Per-team Jira/Linear/Shortcut templates with Jinja2 variables (finding ID, severity, repo, service, dep graph, reachability, remediation, link back to Heeler); per-team overrides per trigger+action; schema-checked field defaults; dedup so no second ticket for the same entity. | Workflows create Jira tickets and Slack messages from templates in the catalog; deterministic multi-step chains. Rich orchestration; per-team Jinja2 ticket templating with schema-checked dedup is not documented. | ● Heeler advantage |
| Workflow orchestration & response | Event-driven workflows (New Finding, New CVE, Compromised Dependency, SLO Expiring) fire the moment they trigger — unified triage → routing → remediation → runtime SLO closure, deeply integrated with the code context model. | Drag-and-drop Workflows with a template catalog and three execution modes (deterministic, human-in-the-loop with agent verdicts, agent-led hygiene). Wiz's 200+ integration count spans cloud + SOC; for code-finding automation the two are comparable. | ✓ Parity |
| CI/CD supply chain | |||
| Workflow & action inventory | Parses every workflow YAML; depth-10 transitive walk across composite + reusable workflows; JS-action npm dependencies spliced into the repo's npm graph; CycloneDX SBOM with pkg:github-action purls; SHA-exact matching; each Action resolved to a pinned commit SHA with its own transitive deps scanned. | Recognizes the github-actions ecosystem in the dependency graph; VCS/CI-CD posture rules; SBOM export. Reusable-workflow depth and Action-npm transitive splicing are not documented at Heeler's depth. | ● Heeler advantage |
| Action risk scoring | Pin status (only a 40-char SHA counts), publisher trust + account age, SLSA attestation on the resolved SHA, and bundled-npm CVEs inherited via the SCA path. | CI/CD security posture checks and VCS configuration rules flag unpinned/over-permissive patterns; strong posture coverage, but a per-Action composite trust score is not documented. | ◐ Heeler edge |
| VCS / CI-CD posture & compliance frameworks | Enforces CI/CD hygiene via guardrails (unpinned actions, excessive token permissions, dangerous triggers) but does not center on compliance-framework mapping. | 40+ Cloud Configuration Rules mapped to OpenSSF SCM Best Practices, OWASP Top 10 CI/CD Risks, CIS for GitHub, and CIS for GitLab — a documented, framework-aligned VCS/CI-CD posture program. | ○ Wiz advantage |
| Unified CI/CD risk management | One data model, one risk score, one guardrail set across repo code and CI/CD; Action findings route through the same CODEOWNERS-based ownership and automated-workflow infrastructure as dependency findings. | CI/CD posture and Action advisories feed the Security Graph and unified policy engine; strong single-platform view, though code and Actions findings surface across the broader Wiz Issue model rather than one code-finding risk score. | ◐ Heeler edge |
| Operational fit | |||
| SCM coverage | GitHub, GitLab, Bitbucket, Azure DevOps — one platform across all. | GitHub, GitLab, Bitbucket (Cloud + Data Center), Azure DevOps for source scanning; PR scanning across GitHub, GitLab, Bitbucket, Azure DevOps. | ✓ Parity |
| Agentless onboarding | Three read-only connections (SCM, artifact registry, cloud) and the six-dimension graph assembles in under 15 minutes; no pipeline integration, no build changes, no tagging, no sensors. GitHub App two-click install; SSO/SCIM. | Agentless connectors for cloud + VCS; a runtime sensor is used for reachability and in-memory confirmation. JIT provisioning via SSO; OAuth for IDE/CLI. Fast, but reachability leans on the sensor. | ◐ Heeler edge |
| Enterprise scale & identity | SSO/SAML + SCIM; API-first; multi-SCM/multi-cloud org rollout. | Trusted by >50% of the Fortune 100; mature enterprise identity, RBAC, and org-scale rollout. | ✓ Parity |
WHERE HEELER ADVANCES
Six places the AI SDLC needs more than a cloud graph.
Every one of these maps back to the context engine — not features bolted onto a scanner.
01
Deterministic, CI-validated remediation — SCA and SAST
Heeler computes the fix, builds and tests it in your CI, repairs until green, and opens a merge-ready PR. Wiz's Green Agent produces an excellent plan and hands execution to an external coding agent. Throughput scales with code-generation velocity, not reviewer capacity.
02
Agent skills security
Heeler inventories and scores the skill and instruction files your agents load (CLAUDE.md, AGENTS.md, skills.md, .cursorrules, mcp.json) for prompt injection, exfiltration, destructive commands, and permission abuse — mapped to MITRE ATLAS + OWASP LLM Top 10. Wiz's AI-BOM inventories frameworks, models, and IDE extensions, but doesn't vet the artifacts themselves.
03
Six-dimension context, modeled around the service
The running application is the atomic unit, then Heeler goes deeper into the code — cross-function, cross-file graph-based taint, build-emulation SCA across 14 ecosystems, and CI/CD as a peer ecosystem at depth-10 — plus cloud, business, ownership, and threat, all assembled from three read-only connections, sensor-less.
04
Runtime-verified SLO closure
The SLO clock closes only when Heeler confirms the fix is gone from every running deployment — not at PR merge. Compliance reflects real exposure, not ticket state.
05
Deterministic dependency solving
Heeler decides the upgrade — dependency graph + changelog intelligence + breaking-change detection + method reachability — to the provably-minimal safe version; the agent only executes. Wiz's selection is AI-suggested and adaptive.
06
Plain-English PR guardrails with in-PR Fix Now
Block / Warn / Observe authored in plain English, scoped by runtime context and branch, diff-only on net-new — with a Fix Now button that triggers a validated remediation PR without leaving the review.
See Heeler across your AI SDLC.
Heeler secures the whole AI SDLC — not just code. A demo runs it against your real repos, dependencies, and cloud, then walks through how prioritization, remediation, and workflows come together. Side-by-side with Wiz Code, if useful.
