Security Advisor (/mantis-advise)

System Goal

Proactive Secure Development Advisor. Functions as a security guardrail and advisory assistant for developers and coding agents. Queries Mantis threat models, historical vulnerability lineages, verified remediation patterns, triaged false positives, and learned trajectory invariants to ensure that new code and refactors are implemented securely from the start.

Command Definition

Command:
```
/mantis-advise
```
Description: Queries security knowledge for a given target file or module, evaluates proposed changes against known threat boundaries, and provides verified secure implementation guidance.

Execution Command:

bash

python3 reference/scripts/advise.py --file <target_file> [--db knowledge.db]

Arguments (optional):
- ```
--file
```
  /
```
-f
```
  (or
```
--target
```
  /
```
-t
```
  ): Target source file or component path (e.g.
```
src/auth.py
```
  or
```
api/app.py
```
  ). Defaults to repo-wide scope if omitted.
- ```
--db
```
  /
```
-d
```
  : Path to Mantis SQLite database (default: auto-discovers
```
knowledge.db
```
  or
```
workspace/knowledge.db
```
  ).
- ```
--lineage
```
  /
```
-l
```
  : Query lifecycle and recurrence for a specific lineage UUID.
- ```
--signature
```
  /
```
-s
```
  : Query lifecycle for a specific content signature hash.
- ```
--json
```
  : Emit structured JSON output instead of formatted markdown.

How to Fetch Guidance

All Mantis knowledge (threat models, historical findings, verified patches, triaged false positives, and learned invariants) lives in the SQLite database (

knowledge.db

). Do not look for flat files on disk (like

learnings.jsonl

workspace/findings/*.json

). Use one of the two execution doors below:

Mechanism 1: CLI Execution (Recommended for Coding Agents)

Coding agents with standard bash access should run

reference/scripts/advise.py

Query Security Guidance for Target File:
bash
```
python3 reference/scripts/advise.py --file src/auth.py
```
Prints: Actionable security advisory markdown with active threat model, historical vulnerabilities, verified patch diffs, triaged false positives, and invariants.

Query Specific Bug Lineage & Recurrence:

bash

python3 reference/scripts/advise.py --lineage c3a5e982-1234-5678-9abc-def012345678

Machine-Readable JSON:

bash

python3 reference/scripts/advise.py --file src/auth.py --json

Mechanism 2: Python Tool Invocation (Inside Pipeline / Harness)

When running inside an agent harness or Python environment:

python

from core.database import query_security_guidance

guidance = query_security_guidance(db_path="knowledge.db", filepath="src/auth.py")
print(guidance["guidance_summary"])

Or via tool helper:

python

get_security_guidance(filepath="src/auth.py")

Input/Output Contract

Reads:
- ```
knowledge.db
```
  (
```
findings
```
  ,
```
campaign_artifacts
```
  ,
```
learnings
```
  , and
```
risk_scores
```
  tables).
- Target source code files (under repository root).
Writes:
- Structured Security Advisory & Guardrail recommendations formatted for the active developer or coding agent.

Core Advisory Protocols

Protocol 1: Pre-Implementation Security Context Check

Before authoring code or refactoring an existing module:

Run the Advisor: Execute

python3 reference/scripts/advise.py --file <target_file>

Review Advisory Context:
- Trust Boundaries: Identify who interacts with this module (untrusted public internet, authenticated users, internal microservices).
- Historical Pitfalls: Review all vulnerabilities previously confirmed or reproduced on this file. Pay specific attention to recurring
```
lineage_id
```
  chains.
- Verified Safe Idioms: Review verified patch diffs from prior passes marked
```
VERIFIED_SECURE
```
  .
- Triaged False Positives: Review patterns previously classified as false positives to understand intentional design choices and avoid breaking legitimate functionality.

Protocol 2: Trust Boundary Verification

When introducing new endpoints, parameters, data parsing, or subprocess execution:

Input Normalization & Validation:
- Never trust input from external boundaries without canonicalization and strict schema enforcement.
- For file paths: resolve against jail boundaries using strict
```
os.path.abspath
```
  or
```
Path.resolve()
```
  checks (
```
startswith(jail_dir)
```
  ).
- For OS command execution: strictly use
```
shlex.quote
```
  or array-based
```
subprocess.run(["cmd", arg])
```
  without
```
shell=True
```
  .
Defense-in-Depth:
- Ensure server-side validation even if client-side validation is present.
- Ensure zero-privilege assumptions (e.g. no unnecessary IAM permissions, bounded execution timeouts).

Protocol 3: Lineage & Recurrence Defense

When fixing a reported vulnerability or refactoring a vulnerable component, check the bug's
```
lineage_id
```
via
```
python3 reference/scripts/advise.py --file <target_file>
```
.
Ensure the new implementation completely closes all attack vectors demonstrated in prior re-attack verification test suites.

Output Format

The Advisor outputs clean, actionable recommendations:

markdown

# Security Advisory: <target_file>

### 1. Threat Model & Trust Boundaries
- **Entry Points**: <untrusted network / RPC / CLI>
- **Sensitive Assets**: <credentials, filesystem, tenant data>

### 2. Known Pitfalls & Historical Lineages
- **[CWE-XX] <Title>** (Lineage: `<uuid>`): <How it occurred and how it was resolved>
- **Verified Safe Pattern**:
  ```python
  # Safe implementation idiom

3. False Positive Context (Intentional Behavior)

<Pattern>: <Why this pattern is considered safe in this specific architecture>

4. Implementation Checklist

Validated against path traversal / injection / deserialization.
Adheres to verified patch patterns.
Respects trust boundary isolation.

undefined

mantis-advise

NPX Install

Tags

SKILL.md Content

Security Advisor (/mantis-advise)

System Goal

Command Definition

How to Fetch Guidance

Mechanism 1: CLI Execution (Recommended for Coding Agents)

Mechanism 2: Python Tool Invocation (Inside Pipeline / Harness)

Input/Output Contract

Core Advisory Protocols

Protocol 1: Pre-Implementation Security Context Check

Protocol 2: Trust Boundary Verification

Protocol 3: Lineage & Recurrence Defense

Output Format

3. False Positive Context (Intentional Behavior)

4. Implementation Checklist