AEGIS  ·  AI-assisted AppSec

The staff-level security engineer for AI-built regulated SaaS.

Aegis isn't another scanner. It runs deterministic analyzers first, treats those findings as ground truth, and layers evidence-backed reasoning on top to build the exploit chains an attacker would actually use — then hands you mergeable fixes and immutable evidence.

Deterministic-first Evidence-backed Mergeable remediations Immutable evidence
Aegis — Breach Path 1 CRITICAL PATH
Exploit chain · evidence-backed
Public API endpoint exposed /upload · no auth Unvalidated file parser RCE-class finding · deterministic Over-broad IAM role s3:* on tenant bucket Tenant PHI store cross-tenant read · impact
Patch file-parser RCE parsers/upload.ts FIX READY
Scope IAM policy to tenant iam/tenant-role.tf IN REVIEW
The problem

Flat findings are not a security program.

Regulated teams don't drown because they have too few tools. They drown because every tool produces another undifferentiated list — and someone still has to figure out which five issues, in combination, actually get an attacker to the data.

Typical scanner

A backlog you can't triage

  • Thousands of findings ranked by generic severity
  • No view of how issues combine into a real attack
  • False positives that erode engineering trust
  • "Recommendations" with no mergeable fix
  • Reports built for a PDF, not for a pull request
Aegis

Decisions, with evidence attached

  • Deterministic findings as verifiable ground truth
  • Findings correlated into reachable breach paths
  • Reasoning that never invents unsubstantiated issues
  • Code-level, mergeable remediations
  • Immutable evidence for every decision and fix
How it works

Deterministic analysis first. Evidence-backed reasoning second.

Four stages, in order. Reasoning is always accountable to the stage beneath it.

01

Deterministic analyzers

Aegis runs deterministic analyzers across your code, infrastructure, and configuration. The findings they produce are evidence-backed and reproducible — this is ground truth, and everything downstream is anchored to it.

Output: verifiable findings + evidence
02

Evidence-backed exploit-chain reasoning

LLM reasoning operates strictly on top of deterministic findings. It correlates them into the breach paths an attacker would actually take — entry point to impact — without inventing anything the evidence doesn't support.

Output: prioritized breach paths
03

Mergeable remediation

For each link in the chain, Aegis produces code-level fixes — deterministic fixers and generated changes — packaged for human review and merge. Not advice: diffs.

Output: reviewable pull-request-ready fixes
04

Retest & immutable evidence

After a fix lands, Aegis retests the path to confirm it's closed and preserves the full trail — finding, reasoning, fix, and verification — as tamper-evident evidence for audit.

Output: confirmed closure + audit record
Trust architecture

Engineered to be trusted inside regulated systems.

Aegis is built for environments where the security tool itself has to meet the bar.

Deterministic ground truth

The model never originates findings. Everything it reasons about is anchored to deterministic, evidence-backed analysis.

Tenant isolation

Multi-tenant boundaries are enforced throughout, so one customer's code and evidence never bleed into another's.

Immutable evidence

Findings, decisions, and fixes are preserved as a tamper-evident record purpose-built for audit and compliance.

Hostile-code sandboxing

Analyzers are designed to handle untrusted, potentially malicious code safely — containment is a first-class concern.

AWS-first posture

Built for AWS-first SaaS, with the deployment and least-privilege patterns regulated cloud teams already expect.

Accountable reasoning

Every conclusion traces back to its evidence, so security and audit teams can verify — not just trust — the output.

Worked example

Five findings. One breach path.

Individually, each of these might sit in a backlog for months. Chained, they're a cross-tenant PHI exposure. Aegis surfaces the chain — and the fix that breaks it earliest.

Public /upload exposed · no auth File parser RCE-class Worker IAM role s3:* granted Tenant bucket PHI objects Cross-tenant read impact

Aegis recommends patching the file-parser RCE first — it's the earliest link that, once closed, breaks the entire chain — and ships the fix as a reviewable diff.

Who it's for

What each team gets from Aegis.

Security & AppSec leads
  • Breach paths ranked by real, reachable impact
  • Far less noise — evidence-backed findings only
  • A defensible answer to "what do we fix first?"
Platform & engineering leads
  • Mergeable fixes that fit the existing review flow
  • No triage tax on every scanner false positive
  • Retest confirms the path is actually closed
Compliance & audit
  • Immutable evidence for every finding and fix
  • A complete, verifiable decision trail
  • Posture built for healthcare, finance, and gov

Know what gets you breached before someone else does.

Book an Aegis assessment and see your real breach paths — with mergeable fixes attached.