COMPARE & TRUST · AGENTIC DEVELOPMENT SECURITY

What is Agentic Development Security?

AI writes the code and AI attacks it — and traditional AppSec, built for human-paced development, can't keep up. Agentic Development Security (ADS) is the new operating model: prevent, fix, and audit risk across the AI SDLC, automatically and at machine speed. Here's the category Forrester defined — and how Heeler delivers every layer of it.

Detection is commoditized. Context is the differentiator.

In April 2026, Forrester named the shift. As AI agents generate code at machine speed and AI attackers weaponize flaws in minutes, scanning and triage no longer bound risk. ADS platforms don't just find problems — they prevent, prioritize, and fix them autonomously, in context.

Explore the Context Engine →
01

Machine-speed development

AI agents ship code around the clock, faster than any team can review it — more code, less scrutiny, more exploitable paths.

02

Machine-speed attackers

The same AI chains low-severity findings into working exploits in minutes. The backlog you deferred is now a live attack surface.

03

A brand-new attack surface

The agents themselves — their skills, MCP servers, extensions, and pipelines — run with implicit trust. Compromised instructions become compromised software.

CORE ADS CAPABILITIES

Heeler delivers every layer of ADS.

Forrester describes Agentic Development Security not as a tool but as a platform that combines multiple intelligence and control layers. Heeler delivers all of them from one context engine.

Code & dependency analysis, beyond pattern-matching
Heeler runs its own SCA and SAST engines: interprocedural, cross-file taint that proves reachability and logic flaws, plus code-to-cloud context that scores real, in-context exploitability — not CVSS.
Guardrails for AI-assisted coding
Heeler embeds in coding agents (MCP, agent skills) and the CLI, and gates the PR with SCM-native checks — guiding agents to secure outcomes and blocking unsafe instructions before they execute.
Intelligent triage & prioritization
Heeler Risk continuously ranks every finding by runtime exposure, business tier, and active exploitation — Urgent, Plan, or Defer — so effort goes to what's actually exploitable.
Automated remediation for code & dependencies
Deterministic fixes: a graph-safe dependency upgrade or a taint-bound source-code transform, validated in your build and CI and delivered as a merge-ready PR that preserves functionality.
Dynamic testing of live apps & APIs
Heeler maps your exposed API surface and its auth posture from code — endpoint enumeration, auth-path tracing, exposed actuators — and ties it to runtime (internet-facing, deployed), pinpointing exploitable exposure without waiting on live fuzzing.
Policy-driven SDLC quality gates
Policy-as-code enforced autonomously at the pull request through the SCM's own branch protection — block, warn, or observe — not manual review.
Supply chain & toolchain protection
Compromised, typosquatted, and unpinned dependencies; the transitive GitHub Actions graph; and the agent toolchain itself — coding agents, MCP servers, agent skills — inventoried and scored.
Governance, reporting & risk analytics
One graph, continuously re-scored as the world changes — durable posture, SLO tracking, and audit-ready evidence over time, not point-in-time scans.
WHY FIXING IS THE HEART OF ADS

The goal isn't more findings. It's less risk.

A finding isn't security — it's a to-do. Nothing is actually safer until the code changes and ships, and AI now generates vulnerable code faster than any team can remediate by hand. That's why remediation, not detection, is the defining capability of Agentic Development Security: the platform has to close risk automatically, or the backlog just grows. Heeler does — turning findings into validated, merge-ready fixes across your dependencies and your code, so your team ships secure software instead of triaging tickets.

See how Heeler fixes →

See Agentic Development Security in action.

Connect a repo and watch Heeler prevent, prioritize, and fix risk across your AI SDLC — automatically, in your first session.