Heeler vs Wiz Code

Heeler is one context engine — code, dependencies, runtime, and cloud reasoned as one seamless model — that maps the attack paths between them and ships a fix validated in your CI. That's Agentic Development Security for the AI SDLC. Wiz Code extends a CNAPP left into the repository, reasoning from the cloud in. Here's where each leads, where they're equivalent, and how to pick for the AI SDLC.

EXECUTIVE SUMMARY

Built for the AI SDLC — one context engine, code to cloud.

Heeler reasons across code, dependencies, runtime, and cloud as one seamless model — the running service, its exposure, and the attack paths that run from the code through to the cloud — then computes the fix, proves it green in your CI, and opens a merge-ready PR for both SCA and SAST. Wiz Code extends the Wiz Security Graph from cloud infrastructure into the repository and, on a code finding, hands the fix to an external coding agent to write.

THE FUNDAMENTAL DIFFERENCE

Heeler is one context engine — code to cloud, seamless — and it ships the fix. Wiz extends a CNAPP into the repo and delegates the fix out.

Heeler reasons across code, dependencies, runtime, and cloud as one model and maps the attack paths between them, then computes and CI-validates the fix itself. Wiz correlates code to cloud from its Security Graph, then hands fix authoring to an external coding agent. 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, secrets (SLM + validation + full git history), 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
→Focused on cloud toxic-combination risk; code-fix authoring and validation are delegated to the coding agent, scoped to supported findings

HEELER

Context-engine native, service-modeled, AI-SDLC-built

One seamless model across code, dependencies, runtime, and cloud — the running application as the atomic unit.

→Reasons across the running service, its cloud/runtime context, and the code-to-cloud attack paths between them as one model — multi-SCM, multi-cloud, sensor-less, 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.

Five states. Heeler-leaning where Heeler advances; explicit when 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 edge

Both deliver the capability. Wiz's implementation leads on a verifiable dimension.

○ 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 edge
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	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. Operates at the org/repo level; less granular than a per-dependency owner cascade (Tech Lead / Security Lead).	◐ 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.	✓ 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

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.

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 a plan and hands execution to an external coding agent. Throughput scales with code-generation velocity, not reviewer capacity.

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.

Six-dimension context, one seamless model

The running application is the atomic unit, reasoned across code, dependencies, runtime, and cloud as one model — cross-function, cross-file graph-based taint, build-emulation SCA across 14 ecosystems, and CI/CD as a peer ecosystem at depth-10 — plus business, ownership, and threat, all assembled from three read-only connections, sensor-less.

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.

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.

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.