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HEAD-TO-HEAD COMPARISON
Heeler vs OX Security.
Heeler is an Agentic Development Security platform built for the AI SDLC — one context engine across code, dependencies, runtime, and cloud, modeled around the service — versus an aggregation-first ASPM. Both scan first-party code and dependencies; the split is depth of remediation versus breadth of coverage.
EXECUTIVE SUMMARY
Built for the AI SDLC, one context engine code-to-cloud.
Heeler was built for the AI SDLC, modeled around the service — one context engine that unifies code, dependencies, runtime, and cloud, assembling six dimensions of context from three read-only connections, sensor-less, with deterministic, CI-validated remediation that computes the fix, proves it green in your CI, and opens a merge-ready PR for SCA and SAST. OX Security is an aggregation-first ASPM — native scanners (SAST, SCA, secrets, DAST) plus a third-party connector catalog in one issue model, prioritized with business context and an Agentic Pentester.
Note: OX aggregates wide; Heeler fixes deep — for one console across the widest surface, look at OX; to clear the volume and cost of fixing AI-generated code, that's Heeler.
THE FUNDAMENTAL DIFFERENCE
Heeler fixes deep; OX aggregates wide.
Heeler runs one context engine across code, dependencies, runtime, and cloud — deterministic, CI-validated fixes proven green and runtime-verified closure, modeled around the service. OX aggregates first-party scanning and third-party connectors into one issue model. Both scan first-party code and dependencies and prioritize with context; the split is strategy — depth vs breadth — and what happens after a finding lands.
OX SECURITY
Aggregation-first Active ASPM
Wide coverage, unified into one issue model.
- →Native scanners (SAST, SCA, secrets/PII, IaC, container, DAST) plus a large third-party connector catalog — the AppSec one-stop-shop
- →Prioritizes with Application Business Priority, cloud-asset reachability, an AI Severity Simulator, and an Agentic Pentester
- →VibeSec guides AI coding agents (prompt analysis → pre-generation guidance) and inventories the MCP/model/SaaS stack, with runtime tool-blocking
- →Remediation = AI-generated fix suggestions (Early Access): a SAST subset, four languages, delivered as PR suggestion comments; no dependency-upgrade solver, no CI-validation loop
HEELER
Context-engine native, service-modeled
Six dimensions of context, one model, a validated fix at the end.
- →One context engine assembles six dimensions — code, cloud, business, ownership, threat, agent — from three read-only connections, sensor-less
- →Prioritizes by function + runtime reachability, internet exposure, business tier, and exploit maturity — recomputed continuously
- →Embeds in coding agents via MCP + skills, and vets the skill/instruction files agents load for malicious content, scoring each
- →Remediation = a deterministic, computed fix, built and tested in your CI, repaired until green, opened as a merge-ready PR — SCA and SAST
VERDICT FRAMEWORK
Side-by-side, with a verdict per row.
Five states. Heeler-leaning where Heeler advances; explicit when OX leads; honest about parity.
●
Heeler advantage
Heeler delivers a capability OX 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.
◑
OX edge
Both deliver the capability. OX's implementation leads on a verifiable dimension.
○
OX advantage
Explicit signal that OX Security leads on this row.
Scorecard — 24 capabilities, scoped to code security
| Section | ● Heeler advantage | ◐ Heeler edge | ✓ Parity | ◑ OX edge | ○ OX advantage |
|---|---|---|---|---|---|
| Prevent | 2 | 2 | 2 | 0 | 0 |
| Fix | 4 | 1 | 1 | 0 | 0 |
| Operate | 2 | 5 | 4 | 1 | 0 |
| Total | 8 | 8 | 7 | 1 | 0 |
| Capability | Heeler | OX Security | Verdict |
|---|---|---|---|
| Prevent · stop risk before and as it enters | |||
| Security at AI code generation | 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 — one central policy across Claude Code, Cursor, Copilot, Windsurf, Codex, any MCP client. | VibeSec analyzes the developer's prompt, predicts likely risks, and sends pre-generation security guidance to the coding agent (Agent Guidelines by language and vulnerability type). Runs in the background, before code is generated — a comparable prevent-at-generation approach. | ✓ Parity |
| Agent security & governance | Skill catalog inventories every skill/instruction file in use (skills.md, CLAUDE.md, AGENTS.md, .cursorrules, mcp.json) and vets each for malicious content — prompt injection, exfiltration, destructive commands, permission abuse — with a 0–100 safety score mapped to MITRE ATLAS + OWASP LLM Top 10, plus MCP inventory. | VibeSec's Agent AI BOM inventories the MCP servers, external SaaS, and AI models agents use, with usage and owners, and can block specific MCP tools at runtime. Covers usage governance and enforcement; it inventories and blocks the stack rather than statically vetting the instruction-file content for embedded attacks. | ◐ Heeler edge |
| PR guardrails & policy enforcement | Block / Warn / Observe with plain-English rule authoring; scoped 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. | A configurable policy catalog (code security, secrets/PII, malicious deps, license, SBOM, IaC, container, CI/CD & Git posture, artifact integrity) with per-severity enforcement, CI/CD gating, and SLA policies. Policy is per-scope configuration rather than plain-English, and there's no in-PR one-click validated remediation. | ◐ Heeler edge |
| Software supply-chain prevention (deps) | Layered guardrails: malicious/compromised (block on sight), typosquat detection, minimum package-age cooldown (blocks freshly published malware before advisories), unpinned-dependency and unpinned-Action detection, dependency-hygiene scoring — each enforceable at the PR; continuous re-evaluation when a clean dependency is later flagged. | Malicious-Dependency policy flags known/suspected malware and recommends removal (typosquatting, protestware, credential theft, RCE, postinstall abuse, chain hijacks), with license and SBOM policies. Currently Early Access. Detection-and-recommend focused; minimum-age cooldown and unpinned-dependency guardrails are not documented. | ● Heeler advantage |
| 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. | OX applies code-to-cloud policy and pull-request enforcement to newly introduced risks, including Infrastructure-as-Code findings. | ✓Parity |
| Agent-file PR enforcement | 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. | No documented capability. | ●Heeler advantage |
| Fix · resolve findings — code and dependencies | |||
| Deterministic upgrade selection | Heeler (not the model) computes the fix: dependency graph + changelog intelligence + breaking-change detection + reachability of called 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. | No dependency-upgrade solver is documented. OX prioritizes and recommends, and its AI Remediation is scoped to first-party code (SAST) — not SCA dependency-version selection. | ● Heeler advantage |
| End-to-end SCA autofix (CI repair loop) | The agent branches, applies the upgrade, makes required first-party code changes, and validates through CI iteratively — compilation for compiled languages, sandbox execution for interpreted — looping until lint/unit/integration tests pass, or abstaining to a human. Produces a merge-ready PR with impact, diff, and proof it builds. | Not offered. OX AI Remediation covers Code Security (SAST) issues only; there is no dependency-upgrade remediation and no Heeler-style CI validate-and-repair loop. | ● Heeler advantage |
| SAST autofix (validated code fixes) | GA. From the taint path to a merged PR: a deterministic, strategy-matched transform (parameterize / escape / allow-list / normalize) chosen from the flaw class and anchored to the exact source-to-sink flow; 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. | AI Remediation (Early Access): an LLM generates a fix suggestion for a subset of SAST issues — JavaScript/Java/Python/C#, severity Medium+ — delivered as PR suggestion comments, IDE fixes, or in-UI. Code is sent to a hosted model; validate the generated advice with your security team. AI-generated and unvalidated rather than deterministic and CI-proven. | ● 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; a confidence score on every candidate transform; Remediation Workbench shows environment-wide distribution. | An 'AI Codefix Available' filter flags issues that have an AI suggestion. A binary availability signal rather than a fix-effort grade and auto-fixable classification. | ◐ Heeler edge |
| Inline PR fix suggestions | For guardrail violations, Heeler posts the fix as a native PR-review suggestion block — click-to-commit, on the exact offending lines — with a commit-and-push fallback; complements the validated merge-ready PRs. | AI Remediation posts suggestions as PR/MR comments with Commit Suggestion and Add to Batch. Comparable click-to-commit delivery — the difference is what's behind it (AI-generated suggestion vs Heeler's deterministic transform). | ✓ Parity |
| 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 | |||
| Unified context graph | One graph unifying six dimensions — code, cloud/runtime, business, ownership, threat, and agent — sensor-less, with everything downstream (prioritization, SLOs, workflows) reading from it. Cloud/runtime and endpoint discovery are broken out in the rows below. | Native SAST (static analysis + pattern detection), SCA, secrets/PII, IaC, and SBOM, plus ingestion of third-party scanners into one unified issue model — a broad, aggregation-first base that correlates code and business context. The aggregation breadth is an OX-specific capability. | ◐ Heeler edge |
| Cloud & runtime context | Fingerprints running services to the exact commit, detects internet-facing exposure, and maps deployments and service-to-service connections across AWS, GCP, Azure, Kubernetes, and Vercel — sensor-less. | Correlates cloud and posture context as part of its aggregation-first ASPM model, but has no application-runtime layer of its own — no fingerprinting of running services to commit, internet-facing exposure detection, or deployment and service-to-service topology. | ◐ Heeler edge |
| Endpoint & API discovery | Enumerates application API endpoints and schemas from source, and models per-endpoint authentication — method, protocol, provider, protected-or-not, auth chain, and token issuer. | No application API endpoint or schema inventory, and no per-endpoint authentication model — endpoints, auth chains, and token issuers sit outside OX's issue-aggregation model. | ● Heeler advantage |
| Secrets detection | Full git-history scanning with per-finding commit attribution; live/active validation via per-provider API parsers, plus scheduled re-validation of rotated creds; rule- and entropy-based; offline in the CLI. | Scans code, git history, containers, runtime, and CI/CD logs; Secret Validation checks whether detected secrets are active; custom detection and exclusion patterns. Broad coverage with validation — at parity for code secrets. | ✓ Parity |
| Runtime-aware prioritization & reachability | Heeler Risk (Urgent / Plan / Defer) from function + runtime code reachability, internet exposure, downstream service criticality, business tier, exploit maturity, and framework-mitigation checks — recomputed continuously; deployment auto-detected, sensor-less. | Prioritizes with Application Business Priority, an AI Severity Simulator, and Agentic-Pentester validation. Its Reachability validates whether cloud assets are internet-reachable (exposure), not source-to-sink code reachability; runtime context needs the K8s runtime sensor. Both are context-aware — different reachability models. | ✓ Parity |
| Finding lifecycle & refactor-resilience | Lifecycle states Active → Fixed → Deployed (gone from every running deployment, runtime-verified); introduced-vs-surfaced distinction; cross-scan issue matching survives file moves, renames, and refactors via stable dedup fingerprints, with commit-level attribution. | Active / Resolved / Removed states plus a Change Intelligence view (new / changed-severity / resolved / removed, trends, regressions across scans). Trend and diff tracking; a runtime-verified deployed close and refactor-resilient fingerprinting are not documented. | ◐ Heeler edge |
| SLO management & response orchestration | SLOs that close only on a runtime-verified fix — not at PR merge; SLO Override / Expiring / Guardrails; event-driven workflows route findings to the owning team (per-team Jira/Linear/Shortcut templates, Slack/Teams/Chat) and can auto-trigger a validated remediation PR. | Broad ticketing and messaging (Jira, ServiceNow, Linear, Asana, Monday, Azure Boards, GitHub Issues; Slack, Teams) with automation rules and SLA enforcement. Routing and SLA — but SLA closes on issue resolution/scan state, not a runtime-verified fix, and remediation isn't executed in-loop. | ◐ Heeler edge |
| CI/CD & supply-chain posture | Continuous posture management, not just a PR gate: validates that dependency pinning and minimum-release-age controls are configured and enforced across ecosystems (npm, pnpm, Yarn, Bun, uv, pip, Deno) — flagging repos that are missing them — alongside a compromised-dependency catalog with SCA + behavioral-SAST detection. CI/CD is modeled as a peer ecosystem (depth-10 action graph, Actions pinned to SHAs with their npm deps scanned); CycloneDX SBOM. | A dedicated OSC&R (Open Software Supply Chain Attack Reference) framework with coverage reporting, PBOM (pipeline bill of materials), artifact-integrity, and CI/CD- and Git-posture policies. Framework-aligned posture — OSC&R coverage, PBOM, and artifact attestation are OX-specific capabilities. Comparable depth, different shape. | ✓ Parity |
| 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. | OX scans Infrastructure-as-Code and normalizes the findings into its ASPM graph and workflow. | ✓Parity |
| 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. | OX uses source-control audit-log activity in Git Posture policies that evaluate administrative conditions across repositories, including inactive privileged users, bot ownership, and excessive administration. Selected policies cover GitHub, GitLab, Azure DevOps, and Bitbucket. | ◑OX Security 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 |
| 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. | OX provides API-BOM, AI-BOM, PII policies, and inventory across code, build, and cloud assets. Its documented model inventories data-related and application assets but does not present each source-derived data type as an application-catalog object linked to the services and APIs that process it. | ◐Heeler edge |
WHERE HEELER ADVANCES
Where deep beats wide for the AI SDLC.
Every one of these maps back to the context engine — not features bolted onto a scanner.
01
Deterministic, CI-validated remediation
Heeler computes the fix, builds and tests it in your CI, repairs until green, and opens a merge-ready PR across SCA and SAST. OX's AI Remediation is Early Access, SAST-only, AI-suggested and unvalidated. Throughput scales with generation velocity, not reviewer capacity.
02
Deterministic dependency solving
Heeler picks the provably-minimal safe upgrade (graph + changelog + breaking-change + method reachability). OX has no dependency-upgrade solver — its remediation is first-party code only.
03
Preventive supply-chain guardrails
Minimum-age cooldown, unpinned-dependency and unpinned-Action detection, and typosquat blocking stop malware before an advisory exists — beyond OX's Early-Access malicious-dependency detection.
04
Agent-skill content vetting
Heeler vets the instruction and skill files agents load for embedded attacks and scores each 0–100. OX inventories and blocks the MCP/model/SaaS stack, but doesn't vet the artifact content for malicious instructions.
05
Runtime-verified closure + code reachability
SLOs close only when the fix is gone from every running deployment, and prioritization uses function-level source-to-sink reachability — not just cloud-asset exposure.
06
One context engine, code-to-cloud, sensor-less
Code, cloud, business, ownership, threat, and agent context unified in a single engine from three read-only connections — no sensor required for code-to-runtime prioritization, live in minutes.
See Heeler across your AI SDLC.
Heeler secures the whole AI SDLC — not just code. A demo runs it against your real repos: prioritization, the validated remediation PRs, and the agent-skill catalog. Side-by-side with OX, if useful.
