# AI AppSec (npm · ai-appsec)

Evidence-backed AppSec for AI applications and agents. Powered by HAIEC.

- Trust score: 94/100 (high trust)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-20

## Components

- npm · `ai-appsec`: 94/100 (this document), [markdown](https://verifymcp.io/servers/subodhkc-ai-appsec/ai-appsec.md), [page](https://verifymcp.io/servers/subodhkc-ai-appsec/ai-appsec)

## Channel facts

- Registry: `npm`
- Package: `ai-appsec`
- Version: `0.1.0`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-20.

- **Supply Chain Security**: 100/100
  - No malware found by supply-chain analysis.
  - No known CVEs affecting this package version or its production dependencies.
  - No install/post-install scripts declared.
  - 0 of 5 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 100/100
  - Source repository is publicly reachable at the declared URL.
  - Cryptographically verified build provenance (signed, bound to subodhkc/ai-appsec).
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 30 days ago).
  - Publishes a security disclosure policy (SECURITY.md).
- **Schema Quality & AI Usability**: 69/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 384 tokens (~384/item across 1 items; 1 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 100/100
  - No destabilizing schema changes in the last 30 days.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 1 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 1 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the AI AppSec MCP server?

AI AppSec runs locally as an npm package, launched with npx -y ai-appsec. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add subodhkc-ai-appsec -- npx -y ai-appsec
```

### Cursor

```json
{
  "mcpServers": {
    "subodhkc-ai-appsec": {
      "command": "npx",
      "args": [
        "-y",
        "ai-appsec"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "subodhkc-ai-appsec": {
      "command": "npx",
      "args": [
        "-y",
        "ai-appsec"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add subodhkc-ai-appsec -- npx -y ai-appsec
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "subodhkc-ai-appsec": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "ai-appsec"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add subodhkc-ai-appsec --command npx --arg -y --arg ai-appsec
```

### Hermes

```yaml
mcp_servers:
  subodhkc-ai-appsec:
    command: "npx"
    args: ["-y", "ai-appsec"]
```

### Netclaw

```json
{
  "McpServers": {
    "subodhkc-ai-appsec": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "ai-appsec"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add subodhkc-ai-appsec -t stdio -c npx -a -y ai-appsec
```

### Other

```json
{
  "mcpServers": {
    "subodhkc-ai-appsec": {
      "command": "npx",
      "args": [
        "-y",
        "ai-appsec"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-20 (score 94, 0)

- [security] Stability: 0.97 → pass

### 2026-09-19 (score 94, +1)

No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-16 (score 93, +1)

No change was recorded against any check on this day. Stability & Change Management went from 83 to 87. That category is still filling its 30-day observation window: 25 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-14 (score 92, +1)

No change was recorded against any check on this day. Stability & Change Management went from 77 to 80. That category is still filling its 30-day observation window: 23 days of observed history at the previous scan, 24 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-12 (score 91, +1)

No change was recorded against any check on this day. Stability & Change Management went from 70 to 73. That category is still filling its 30-day observation window: 21 days of observed history at the previous scan, 22 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-10 (score 90, +1)

No change was recorded against any check on this day. Stability & Change Management went from 63 to 67. That category is still filling its 30-day observation window: 19 days of observed history at the previous scan, 20 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-08 (score 89, +1)

No change was recorded against any check on this day. Stability & Change Management went from 57 to 60. That category is still filling its 30-day observation window: 17 days of observed history at the previous scan, 18 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-06 (score 88, +1)

No change was recorded against any check on this day. Stability & Change Management went from 50 to 53. That category is still filling its 30-day observation window: 15 days of observed history at the previous scan, 16 at this one. The score rises as the window fills, whether or not the server changes.

## MCP tools (1)

### `scan_ai_security` (~384 tokens)

Scan AI/LLM Source Code Security

Audit AI applications and agents for security risks before commit, PR,
merge, or deployment. Produces deterministic findings with explicit
coverage, Security Concern Families, Scan Receipts, and Evidence Envelopes.

USE when a developer asks to:
\- "check this for security issues"
\- "audit this task before I push"
\- "review this change for security problems"
\- "scan this AI agent" or "scan this AI app"
\- "check my LLM application"
\- "security review this PR"
\- "is this safe to merge"
\- "check this before deployment"
\- "audit this code for vulnerabilities"
\- "run a security scan"
\- "check for security risks before commit"
\- "review this implementation before pushing"

Also use for:
\- reviewing AI/LLM/agent source code for security
\- validating AI code before merge
\- checking an agent before deployment
\- reviewing RAG or model integration security
\- looking for unsafe AI source-code patterns
\- checking AI-output-to-dangerous-action flows
\- checking AI source-code secrets/security controls

DO NOT use for:
\- actual LLM response/content verification (use verify_llm_content)
\- tenant/RLS/cross-customer isolation (use scan_tenant_isolation)
\- generic compliance questionnaires or compliance certification
\- generic non-AI source scanning where no AI check applies

This tool performs static analysis only. It does NOT execute target code,
make network requests, or emit telemetry. BLOCK findings are advisory —
deployment enforcement is handled by check_deploy_security (not yet implemented).

Input parameters:

- `extendedScope` (boolean): Include tests/docs/examples in the scan. Default: false (production scope only).
- `targetPath` (string, required): Absolute or relative path to the AI application source code to scan.
- `timeout` (number): Scan timeout in seconds. Default: 300.

Output parameters:

- `actionableFindings` (array)
- `completeness` (string)
- `completenessReasons` (array)
- `errors` (array)
- `evaluatedDetectorIds` (array)
- `evaluatedSecurityCheckIds` (array)
- `evidenceEnvelope` (object)
- `limitations` (array)
- `observations` (array)
- `receipt` (object)
- `scanId` (string)
- `schemaVersion` (string)
- `securityConcernFamilies` (array)
- `summary` (object)
- `truncation` (object)
- `verdict` (string)
- `versions` (object)

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/subodhkc-ai-appsec/ai-appsec#diagnostics

## Score history

- 2026-09-20: 94
- 2026-09-19: 94
- 2026-09-18: 93
- 2026-09-17: 93
- 2026-09-16: 93
- 2026-09-15: 92
- 2026-09-14: 92
- 2026-09-13: 91
- 2026-09-12: 91
- 2026-09-11: 90
- 2026-09-10: 90
- 2026-09-09: 89
- 2026-09-08: 89
- 2026-09-07: 88
- 2026-09-06: 88
- 2026-09-05: 87
- 2026-09-04: 87
- 2026-09-03: 86
- 2026-09-02: 86
- 2026-09-01: 86
- 2026-08-31: 85
- 2026-08-30: 85
- 2026-08-29: 84
- 2026-08-28: 84
- 2026-08-27: 80
- 2026-08-26: 80
- 2026-08-25: 79
- 2026-08-24: 79
- 2026-08-23: 79
- 2026-08-22: 79

## Common questions

### What is the AI AppSec MCP server?

AI AppSec is an MCP server listed in the public MCP registry as io.github.subodhkc/ai-appsec. Evidence-backed AppSec for AI applications and agents. Powered by HAIEC. This page covers its npm package (ai-appsec).

### Is the AI AppSec MCP server safe to use?

AI AppSec scores 94 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. It declares no install or post-install scripts. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the AI AppSec MCP server expose?

AI AppSec exposes 1 tool: scan_ai_security. Their descriptions and schemas cost roughly 384 tokens of context every time the server is loaded.

### Is the AI AppSec MCP server still maintained?

AI AppSec is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the AI AppSec MCP server under?

AI AppSec declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

## Links

- npm package: https://www.npmjs.com/package/ai-appsec
- Socket report: https://socket.dev/npm/package/ai-appsec
- Repository: https://github.com/subodhkc/ai-appsec
- Changelog RSS feed: https://verifymcp.io/servers/subodhkc-ai-appsec/ai-appsec.xml
- Changelog JSON feed: https://verifymcp.io/servers/subodhkc-ai-appsec/ai-appsec.json
- HTML version of this page: https://verifymcp.io/servers/subodhkc-ai-appsec/ai-appsec