173 Undocumented Security Findings in TerraGoat: What Standard IaC Scanners Miss (and Why Post-Quantum Matters)

TerraGoat is the canonical vulnerable Terraform repository maintained by Bridgecrew (now Prisma Cloud). It has over 5,000 GitHub stars and is used by security teams worldwide as the benchmark for validating IaC scanners. The premise is straightforward: run your tool against TerraGoat, check how many of the known vulnerabilities it catches.

The problem is that the "known vulnerabilities" reference list is incomplete by design — or by oversight. This research quantifies that gap for the first time.

Methodology

Three tools were run against TerraGoat in isolation, with no tuning or custom rules:

1. 
   Checkov — the official Bridgecrew scanner, the tool TerraGoat was originally built to test


2. 
   Trivy (Aqua Security) — the industry-standard open source vulnerability scanner with IaC support


3. 
   pq-audit — an open source post-quantum cryptography audit framework built to detect cryptographic exposure that standard scanners do not model

Each tool produced its raw JSON output. Results were deduplicated per finding identifier and cross-referenced against Bridgecrew's official TerraGoat documentation to determine which findings had been acknowledged by the maintainers and which had not.

Raw data, gap matrix, and per-tool JSON outputs are available in the research repository.

Findings: The Numbers

Checkov produced 56 findings. Every single one maps to documented behavior in Bridgecrew's official documentation. Checkov does exactly what it says.

Trivy produced 125 findings against the same codebase. AVD-AWS-* and aws-* identifiers covering real misconfigurations across S3, IAM, EC2, RDS, and networking resources — critical and high severity. None of these 125 findings appear in Bridgecrew's TerraGoat documentation.

Total undocumented findings: 173 out of 243. That is 70% of the actual security surface.

The implication is direct: if your team selected Checkov as your primary IaC scanner because it is the "official" tool for TerraGoat and Terraform — you are currently seeing 23% of your exposure. Not because Checkov is broken, but because the documentation does not tell you what it does not cover.

The PQC Layer: What No Standard Scanner Checks

After the Checkov/Trivy comparison, a second analysis was run using pq-audit, focusing exclusively on cryptographic posture.

pq-audit found 2 findings that neither Trivy nor Checkov detected at all:

• 
  BROKEN_NOW: cryptographic algorithms in active use that are already considered broken under current NIST guidance (not future-state — present-state broken)


• 
  SNDL_VULNERABLE: configurations that make data susceptible to "harvest now, decrypt later" attacks — a documented nation-state tactic where encrypted data is archived today for decryption once quantum computing reaches sufficient scale


• 
  PQC readiness gaps: absence of migration paths to NIST FIPS 203 (ML-KEM), FIPS 204 (ML-DSA), or FIPS 205 (SLH-DSA) in encryption configuration defined in IaC

Standard IaC scanners model misconfigurations against known CVEs and policy rules. They do not model cryptographic lifetime or quantum-era threat exposure. For most teams in 2026, that gap is invisible.

A note on methodology: the initial pq-audit run against TerraGoat returned 1,122 findings — nearly all false positives triggered by package-lock.json entries (GAP-001, now fixed in v2). After filtering, 2 real findings remained. This is documented intentionally: a tool that surfaces 1,122 noise results on a clean lab is not useful in CI. The fix — scoping the scan to exclude dependency lock files — reduced the signal-to-noise ratio from unusable to precise. The 2 findings that survived are real.

pq-audit is open source: https://github.com/mk-scorpiosec/pq-audit

Why This Research Exists

IaC security tooling is fragmented and documentation is inconsistent. Teams make scanner selection decisions based on vendor marketing, integration convenience, or name recognition — without a clear picture of coverage.

This research is not an argument that Checkov is bad or that Trivy is better. Both tools serve their stated purpose. The argument is that comparing tools requires complete data, and that data has not existed publicly until now.

The gap matrix published here can be used to:

• Benchmark scanner coverage before adoption


• Justify multi-tool strategies to security leadership


• Identify categories of exposure that require manual review regardless of tooling

Conclusions

1. No single IaC scanner covers the full finding surface of even a well-known, intentionally vulnerable repository.


2. Documentation gaps are not the same as tool gaps — Trivy finds real issues that simply never got documented upstream.


3. Post-quantum cryptography exposure in IaC is invisible to current-generation scanners. This is not a theoretical future problem: SNDL attacks against long-lived data are active today.


4. Multi-tool strategies are not optional for teams with serious security requirements.

Full research, raw data, and methodology: https://github.com/mk-scorpiosec/research/tree/main/terragoat-2026-04

Found these issues in your own infrastructure?

MK ScorpioSec offers post-analysis services based on real findings:

• 
  Remediation playbooks tailored to your specific misconfigurations


• 
  YARA rules for detection of active exploitation patterns


• 
  Identity hardening (Okta, AWS IAM, GCP IAM, Azure AD)


• 
  Implementation engagement + retest validation to confirm fixes hold

→ mkscorpiosec.com · [email protected]

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