Versioned security assessment

Report ID: SA-88A8E9A0

7/23/2026, 11:57:16 PM

risk-control-engineer security assessment v4

Skill Security Certification Report

Audit History
Scanner version 3.0.0 Audit model: codex Latest published report
Skill name
risk-control-engineer
Version
v4
Maintainer
zl2023github
Source
github.com/zl2023github/software-engineer-skills/tree/main/software-engineering/risk-control-engineer
Coverage
1 Files scanned · 455 Lines analyzed
Policy version
skillstore-security-audit-policy-v1

Highest confirmed finding severity

Medium

2 confirmed security findings require attention.

Installation context

Check the current Skill page

This page summarizes report evidence only. The Skill page provides the canonical install advisory.

Open current Skill page

This report does not block or authorize the manifest or ZIP.

The Python rule-engine example performs dynamic evaluation of rule text and is a confirmed code-execution risk. The 21 command alerts, two reconnaissance alerts, and entropy alert are false positives caused by Markdown fences, graph variables, and multilingual text. Two additional control-quality defects could hide rule failures or misstate backtest performance.

Report position

Latest published report

Latest refers to the report sequence, not to artifact currentness.

Audit attestation

Active attestation

A public attestation is available for this exact report.

Human verification

Not verified

No human verification is recorded for this report.

Coverage

1 Files scanned · 455 Lines analyzed

3 items shown for review

Limitations

This report does not claim runtime or sandbox execution and does not prove the absence of side effects.

Evidence chain

Follow the evidence from source binding to the install contract. Available evidence supports verification; it is not a safety guarantee.

  1. Source

    Commit and path bound

  2. Artifact

    Content and tree hashes bound

  3. Audit

    Complete

  4. Install contract

    Open manifest to verify

    Open manifest

Capabilities observed

Observed means this report recorded supporting evidence. Not recorded does not prove that a capability is absent.

Contains scripts

May execute code included with the Skill.

Observed in 1 evidence location

Network access

May connect to external services.

Not recorded by this audit

Filesystem access

May read or write local files.

Not recorded by this audit

Env variables

May read values from the process environment.

Not recorded by this audit

External commands

May invoke commands or programs outside the Skill.

Observed in 21 evidence locations

Capability review items (1)
High
SKILL.md:291
Dynamic code evaluation with eval()
return bool(eval(condition, {\"__builtins__\": {}}, allowed_vars))
The rule engine evaluates condition text through eval with feature values as locals. Removing builtins does not prevent malicious expressions from traversing Python objects, so untrusted rules can execute unintended code.

Risk findings

Confirmed security concerns are separated from items that still need review.

Confirmed security concerns (2)

RISK-001 Medium
SKILL.md:286-293
Rule Evaluation Fails Open
The rule engine catches every evaluation error and returns false. Invalid or malicious conditions can silently bypass controls instead of producing a review or rejection.
The broad exception handler directly converts every rule evaluation failure into a non-match. This behavior is explicit in the example.
RISK-002 Medium
SKILL.md:387-392
Backtest Metrics Misstate Control Performance
The capture rate measures fraud prevalence instead of captured fraud, while the false-positive rate uses all labeled rows as its denominator. Decisions based on these metrics may weaken fraud controls.
The formulas visibly omit rule outcomes from capture rate and do not normalize false positives by legitimate cases. Standard confusion-matrix definitions confirm both errors.

Remediation

Suggested fixes recorded by this audit. Applying them is the maintainer’s responsibility.

  1. FIX-001
    High
    Rule conditions are executed with Python eval.
    Replace eval with a constrained expression parser that validates an explicit operator and identifier allowlist.
  2. FIX-002
    Medium
    Rule evaluation suppresses every exception and treats failures as non-matches.
    Reject invalid rules during validation and fail closed with structured errors, monitoring, and an explicit review decision.
  3. FIX-003
    Medium
    Backtest capture and false-positive metrics use incorrect denominators.
    Compute capture rate as TP divided by TP plus FN, and false-positive rate as FP divided by FP plus TN.

Expert evidence

Immutable subject identity, scanner metadata, dismissed matches, and source-level evidence.

Artifact subject

Marketplace commit
88a8e9a07f4c54ab105c1c41b6267c287146b07b
Content hash
7af6ba91bd7c669afcc36789e4c8d7f580a1d1d2f833c2fd159efeb9edd28281
Tree hash
6fc2076acede0c422de8d8336ac735d190a7ece29e4e2622e1ed836f11295ee4
Skill path
skills/zl2023github/risk-control-engineer
Audit payload hash
9bf1c90e28c0abdbf86f1bcd46d4bd45

Analysis metadata

Audit model: codex

Analysis state: Complete

Scope is limited to the recorded files, lines, methods, and evidence. No runtime or sandbox execution is claimed.

Verify and export

JSON report Signed attestation CITATION.cff SARIF 2.1.0 Signed installation manifest Source

The manifest and lockfile bind install artifacts to cryptographic hashes. This integrity claim is separate from the security assessment.

Audit attestation: active