AI AppSec
NPM · AI-APPSEC
Evidence-backed AppSec for AI applications and agents. Powered by HAIEC.
Available components
Last scanned (4 hours ago)
Scores higher than 93% of npm servers
Category Security
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. How we score → Why this is hard to score →
Supply Chain Security83
- No malware found by supply-chain analysis.Pass
- CVE check failed: a known high-severity CVE affects @modelcontextprotocol/server 2.0.0, a direct dependency. A fixed version is available. View diagnostics → Fail
- No install/post-install scripts declared.Pass
- 0 of 5 dependencies flagged as unhealthy. View diagnostics → Pass
Provenance & Transparency100
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to subodhkc/ai-appsec). View diagnostics → Pass
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 76 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability69
- AI-judged instruction clarity (excellent).Pass
- 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. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
- No destabilizing schema changes in the last 30 days.Pass
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 1 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 1 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 1 Nov 26 0
- Stability: 0.97 → pass security
- 31 Oct 26 0
- Stability: pass → 0.97 functional
- 28 Oct 26 0
- GHSA-f897-62hf-6gxq affects this package: high ▼ security
- 25 Oct 26 0
- Stability: 0.97 → pass security
- 24 Oct 26 0
- CVE-2023-54404 affects this package: high ▼ security
- Stability: pass → 0.97 functional
- 21 Oct 26 −5
- CVE-2026-111771 affects this package: high ▼ security
- CVE-2026-111770 affects this package: high ▼ security
- CVE-2026-111768 affects this package: high ▼ security
- Known CVEs: pass → fail ▼ security
- 18 Oct 26 0
- Stability: 0.97 → pass security
- 17 Oct 26 +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.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 5 Nov 2026 · Analysed npm/ai-appsec@0.1.0
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | npm |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | subodhkc/ai-appsec |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/subodhkc/ai-appsec/.github/workflows/publish.yml@refs/heads/release/ai-appsec-v0.1.0 |
| Rekor log index | 2543651510 |
| Predicate type | SLSA build provenance https://slsa.dev/provenance/v1 |
| Subject digest | sha512:062e713ee0f64919438d119112a0c1023ae11a2851c7cb789886fc34e52bf1e9202b743b92c83d15b9c5a0385a0130490fc7c7ec87ff6d0d3bab03e34 |
Background: How many MCP packages publish verified provenance →
Vulnerabilities 5 findings
| ID | CVE | Severity | Vector | Fix available |
|---|---|---|---|---|
| GHSA-46jr-4wx8-v453 | CVE-2026-111768 | high | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H | yes |
| GHSA-f897-62hf-6gxq | high | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H | yes | |
| GHSA-jm63-cq47-j5jp | CVE-2026-111770 | high | CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:L/A:H | yes |
| GHSA-rvq5-wwqv-78pq | CVE-2026-111771 | medium | CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:N | yes |
| GHSA-mrhx-c7xc-m3w5 | CVE-2023-54404 | high | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H | yes |
Background: What a vulnerability scan can and cannot prove →
Dependencies 5 packages
| Packages resolved | 5 |
|---|---|
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
scan_ai_security Scan AI/LLM Source Code Security ~384
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).
| Name | Type | Req | Description |
|---|---|---|---|
| extendedScope | boolean | – | Include tests/docs/examples in the scan. Default: false (production scope only). |
| targetPath | string | yes | Absolute or relative path to the AI application source code to scan. |
| timeout | number | – | Scan timeout in seconds. Default: 300. |
| Name | Type | Req | Description |
|---|---|---|---|
| actionableFindings | array | yes | – |
| completeness | string | yes | – |
| completenessReasons | array | yes | – |
| errors | array | yes | – |
| evaluatedDetectorIds | array | yes | – |
| evaluatedSecurityCheckIds | array | yes | – |
| evidenceEnvelope | object | – | – |
| limitations | array | yes | – |
| observations | array | yes | – |
| receipt | object | – | – |
| scanId | string | yes | – |
| schemaVersion | string | yes | – |
| securityConcernFamilies | array | yes | – |
| summary | object | yes | – |
| truncation | object | yes | – |
| verdict | string | yes | – |
| versions | object | yes | – |
No examples provided.
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.
npm · ai-appsec
claude mcp add subodhkc-ai-appsec -- npx -y ai-appsec
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 89 out of 100 on VerifyMCP. We recorded 5 known advisories against it as of 5 November 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 5 November 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.