Files
msd-core/docs/explanation/security-model.md
Alex V. a63684c222 enhance(#1577): WebFetch/WebSearch injection isolation + opt-in blocking (#1585)
* fix(#1577): isolate WebFetch/WebSearch ingress + opt-in injection blocking

Split A of #1573 (security-critical). Scans WebFetch/WebSearch output (the
largest untrusted channel) in gsd-read-injection-scanner; shared
untrusted-input-boundary reference @-included by the 8 ingest agents
(randomized per-wrap delimiters, in-prompt self-scan guard, task-anchoring);
opt-in security.injection_blocking (default advisory — non-breaking).

arXiv: 2506.05739 (PPA), 2507.15219 (PromptArmor), 2504.20472 (Referencing), 2503.00061 (defense-in-depth).

* fix(#1577): address review — honest blocking docs, config key, ADR, property test, revert localized

- A1: rewrote the opt-in-blocking doc + Security changeset honestly — the PostToolUse hook is a
  circuit-breaker (halts the agent's next step), NOT a redactor; it does not scrub content already
  in the transcript. The prompt-level data/instruction boundary is the primary control.
- A2: registered security.injection_blocking in the config schema + defaults manifests (default
  false) + an e2e config-roundtrip test; the dotted setter writes the nested shape the hook reads.
- A3: reverted the 4 hand-edited localized security-model.md (canonical EN only, per convention).
- A5: ADR-1577 (untrusted-input boundary + opt-in blocking; redaction-vs-circuit-breaker rationale).
- A6: property test — scanner never crashes / only emits valid JSON on unicode/large/malformed input.
- Also: inventory (untrusted-input-boundary.md) + agent-size baseline (8 ingest agents) +
  drift-guard matcher update (Read -> Read|WebFetch|WebSearch). A7 (content<20 early-exit) left as
  the noted pre-existing follow-up.

* fix(#1577): allowlist untrusted-input-boundary.md in injection-scan CI gate

The new reference quotes injection phrases ('ignore previous instructions',
'you are now…') as examples agents must NOT comply with, tripping the repo's
own prompt-injection-scan.sh diff gate (the standalone 'security' CI job, red
on HEAD). Allowlist it alongside the other security docs (security-model.md,
TEST-EXAMPLES.md) that legitimately demonstrate injection patterns. The JS
scanner test doesn't scan references/, so only the shell gate needed it.

Verified: scan --diff origin/next -> 0 findings; scanner JS test 15/15.

* fix(#1577): cover AC #2's gsd-ui-researcher + gsd-assumptions-analyzer

trek-e Major 1: the @-included set dropped two AC #2 agents. Restore them so
no named web-ingress agent is uncovered, keeping the two justified additions
(gsd-ai-researcher, gsd-domain-researcher). Final set = AC's 8 + 2 = 10.
 - gsd-ui-researcher carries the full WebSearch/WebFetch + MCP-fetch toolset.
 - gsd-assumptions-analyzer reads 5-15 codebase source files (external/source-
   document ingress per the boundary), though it has no web tools.
INGEST_AGENTS in the isolation test now asserts all 10; size baselines
regenerated (+60 bytes each, both well under the DEFAULT cap); changeset
reworded 8 -> 10.

Verified: untrusted-input-isolation 14/14; agent-size-budget 39/39.

* docs(#1577): document security.injection_blocking + boundary seam

trek-e Major 2 + Minor:
 - docs/CONFIGURATION.md: add the top-level security.injection_blocking key to
   the Full Schema and a Security Settings subsection, distinguishing it from
   the workflow.security_* namespace; honest circuit-breaker-not-redactor
   framing matching ADR-1577 / security-model.
 - CONTEXT.md: add the 'Untrusted-input boundary' seam glossary entry.

Verified: lint:docs ok; config-field-docs + contributor-standards green.

* test(#1577): make read-injection property test git-text, not binary

trek-e nit (and more): the file embedded a raw U+FFFF AND a raw NUL byte as
degenerate-edge inputs. The NUL is what actually made git classify it binary
(git binary = NUL in first 8K). Replace both with text-safe escapes that keep
the identical runtime values: '\\x00' and String.fromCodePoint(0xFFFF). File
now diffs/blames line-by-line.

Verified: property test 2/2; no NUL/raw-noncharacter bytes remain.

* docs(#1577): align untrusted boundary docs

Name all 10 ingress agents in INVENTORY/security-model and allowlist the intentional read-injection property corpus for the prompt-injection scanner.

* docs(#1577): align ADR ingest agent count

Update ADR-1577 from 8 to 10 ingest agents so it matches the actual boundary include set and the rest of the docs.

---------

Co-authored-by: Tom Boucher <trekkie@nomorestars.com>
2026-06-24 17:07:23 -04:00

285 lines
14 KiB
Markdown

# GSD Core security model
> **Explanation** — This document describes *why* GSD Core has the security
> posture it does and *how the layers fit together*. It is not a reference for
> every hook parameter. For the `/gsd-secure-phase` command and its options,
> see [Commands](../COMMANDS.md). For the implementation-level hook
> architecture, see [Architecture § Hook System](../ARCHITECTURE.md#hook-system).
> For the org-wide security baseline (scanner controls, incident checklists,
> ownership model), see [SECURITY.md](../../SECURITY.md).
---
## Why AI-driven development needs a dedicated security posture
A conventional code editor does not execute arbitrary packages on your behalf.
GSD Core does. The research → plan → execute pipeline automates the full path
from "name a package" to "run `npm install <package>`", from "write a
planning artifact" to "use that artifact as an LLM system prompt". Each
automation step removes a human from the loop — and each removal is a
potential attack surface.
GSD Core's security model is built around one organising principle:
**defence in depth**. No single control is assumed to be perfect. Several
overlapping layers each reduce a distinct class of risk, and together they
make the attack surface substantially harder to exploit without eliminating
it entirely. The honest summary at the end of this document explains what the
system cannot protect against.
---
## Layer 1 — Supply-chain protection: the Package Legitimacy Gate
### The threat
AI models hallucinate package names. This is not a fringe failure mode: 2025
research documents roughly 20 % of AI-generated package references as
hallucinated names that do not correspond to legitimate packages. A subset of
those hallucinated names — approximately 43 % in the same research — recur
consistently across prompts, meaning an attacker can observe which names AI
tools commonly produce and pre-register those names on npm, PyPI, or
crates.io with malicious post-install scripts. The technique is called
*slopsquatting*.
The insidious quality of slopsquatting is that a hallucinated name that passes
`npm view` *looks legitimate*. The registry entry proves only that someone
registered the name — not that the package does what the AI said it does, not
that it has any legitimate users, and not that its install scripts are safe.
Without a gate, a hallucinated name would flow undetected through GSD's
researcher → planner → executor pipeline and eventually run as
`npm install <attacker-package>` on your machine.
### How the gate works
The gate operates across three pipeline stages:
**Research stage.** When `gsd-phase-researcher` recommends external packages,
it runs `slopcheck install <pkgs> --json` against each one. The results are
written to a `## Package Legitimacy Audit` table in `RESEARCH.md`. Packages
tagged `[SLOP]` (high-confidence hallucination or attacker-registered) are
**stripped from `RESEARCH.md` entirely** before the file is saved. They never
reach the planner.
**Planning stage.** `gsd-planner` reads the Audit table. For any package
tagged `[SUS]` (suspicious: newly registered, low download count, no source
repository, or naming pattern close to a popular package) or `[ASSUMED]`
(sourced from WebSearch rather than direct registry verification), the planner
**inserts a `checkpoint:human-verify` task** before the install step. The
checkpoint includes a direct link to the registry page and specific things to
look for: maintainer history, issue-tracker activity, absence of suspicious
install scripts.
**Execution stage.** If an install fails, `gsd-executor` **surfaces a
checkpoint and stops**. It does not silently try an alternative package name —
which could itself be malicious. This is an explicit rule in the executor's
behaviour (RULE 3 in the executor agent definition).
### Why WebSearch packages are always `[ASSUMED]`
Package names discovered through WebSearch are tagged `[ASSUMED]` regardless
of whether `npm view` succeeds. A package that exists on the registry is not
the same as a package that is safe to install. `npm view` proves registration,
not legitimacy. The `[ASSUMED]` tag triggers the same human-verify checkpoint
as `[SUS]`, ensuring that any unverified web-discovered recommendation always
gets a human review before installation.
### Ecosystem coverage
The researcher uses registry-specific verification commands rather than a
single generic check:
- Node.js: `npm view`
- Python: `pip index versions`
- Rust: `cargo search`
This covers cross-ecosystem hallucination, which occurs at roughly 9 %
according to 2025 USENIX research — cases where an AI recommends a package
that exists in one ecosystem but not the one actually in use.
### Graceful degradation
If `slopcheck` is unavailable (not installed, or the pip install fails at
research time), GSD applies the strictest possible fallback: **every
recommended package is tagged `[ASSUMED]`**, and the planner gates every
install with a `checkpoint:human-verify` task. Research and planning proceed
normally — the system never hard-fails on a missing tool dependency. This
is intentionally stricter than the normal flow: slopcheck unavailability means
every package install gets a human checkpoint.
The `slopcheck` tool is MIT-licensed and pip-installable. If it is ever
abandoned, the `[ASSUMED]`-gate fallback ensures human-checkpoint coverage is
maintained regardless.
---
## Layer 2 — Prompt injection defences
### The threat
GSD Core generates Markdown files that become LLM system prompts. The
research pipeline reads external web content; the planning pipeline
incorporates user-supplied text (`--text-file`, `--prd`); the execution
pipeline writes planning artifacts that are later re-read as agent context.
Any user-controlled text flowing into these artifacts is a potential
**indirect prompt injection** vector — an attacker-controlled string that,
once inside a system prompt, attempts to override the agent's instructions or
exfiltrate information.
### How the defences work
GSD Core addresses prompt injection at three levels.
**Input validation (`security.cjs`).** The `gsd-core/bin/lib/security.cjs`
module is the central security utility. It provides:
- Path traversal prevention: user-supplied file paths (`--text-file`, `--prd`)
are validated to resolve within the project directory, with macOS
`/var` → `/private/var` symlink resolution handled explicitly
- Prompt injection detection: known injection patterns (role overrides,
instruction bypasses, system tag injections) are scanned in user-supplied
text before it enters any planning artifact
- Safe JSON parsing: a wrapper that prevents prototype-pollution attacks via
crafted JSON payloads
- Shell argument validation: arguments passed to subshell commands are
validated before use
**Runtime hook: `gsd-prompt-guard.js`.** This hook fires on every Write or
Edit call that targets `.planning/` files. It scans the content being written
for the same injection patterns as `security.cjs` (a subset inlined directly
into the hook for independence — the hook does not `require()` the module, so
it runs even if the module path changes). Detection is **advisory-only**: the
hook logs the finding but does not block the write. The rationale is that a
false-positive block on a legitimate planning write would be more disruptive
than a missed injection in a secondary scan layer.
**Runtime hook: `gsd-read-injection-scanner.js`.** This hook fires on the
output of every Read, WebFetch, and WebSearch tool call. It scans the *content
that was just read or fetched* for injected instructions in untrusted content —
catching cases where an attacker has embedded instructions in a file or remote
resource that GSD is about to incorporate into an agent's context. The 10
research and doc-ingest agents additionally carry a shared `<security_context>`
data/instruction boundary (defined in
`gsd-core/references/untrusted-input-boundary.md`): `gsd-project-researcher`,
`gsd-phase-researcher`, `gsd-ui-researcher`, `gsd-assumptions-analyzer`,
`gsd-advisor-researcher`, `gsd-doc-classifier`, `gsd-doc-synthesizer`,
`gsd-research-synthesizer`, `gsd-ai-researcher`, and `gsd-domain-researcher`.
Any content fetched or read by those agents is treated as data, never as
instructions, regardless of what the content claims to be.
**Opt-in blocking (`security.injection_blocking`).** By default all injection
detections are advisory-only (logged, not blocked). Setting
`security.injection_blocking = true` in `.planning/config.json` (a registered
config key — `gsd config-set security.injection_blocking true`) upgrades
HIGH-confidence detections to **blocking**. Be precise about what this does: the
scanner is a **PostToolUse** hook, so it runs *after* the Read/WebFetch/WebSearch
has already executed and the fetched content is already in the model's transcript.
Blocking does **not** retroactively redact that content — it emits
`decision: "block"`, which halts the agent's next step and feeds the detection back
as the reason, so the agent is stopped from acting further on the flagged result
instead of silently continuing. LOW detections remain advisory under this setting.
This flag is opt-in; the default (advisory-only) is preserved to avoid breaking
existing workflows. The prompt-level boundary above (treat fetched text as data,
never instructions) is the layer that keeps an injection from being *followed* even
while it sits in context; the hook is a coarse pattern pre-filter and circuit-breaker,
not a redactor.
**CI scanner.** `prompt-injection-scan.security.test.cjs` scans all agent, workflow,
and command files for embedded injection vectors as part of the test suite.
This catches injection attempts in the GSD source itself — for example, a
supply-chain attack that modified a workflow file to add a role-override
instruction.
### Read Injection Scanner vs Prompt Guard
The two hooks cover complementary surfaces. `gsd-prompt-guard.js` watches
*writes to planning artifacts* — it catches injection being planted.
`gsd-read-injection-scanner.js` watches *reads and remote fetches* — it catches
injection being ingested from external content (a dependency's README, a
third-party config file, a user-provided document, or any URL fetched via
WebFetch or WebSearch). The in-prompt `<security_context>` boundary in research
agents provides an additional containment layer: even if an injected string
reaches an agent, it is structurally separated from the instruction region.
Together these controls bracket the ingest → store → re-read lifecycle.
---
## Layer 3 — Repository and dependency integrity
Upstream of GSD's runtime behaviour, the `open-gsd` organisation enforces
controls at the repository and package level. These are documented in full in
[`docs/security/baseline.md`](../security/baseline.md) and are summarised
here for completeness.
**Dependency integrity.** All third-party dependencies are pinned via
`package-lock.json` and verified against published checksums before install.
A `scripts/check-npm-integrity.cjs` gate detects invalid versions, missing
packages, and extraneous packages at CI time. This mitigates dependency
confusion and typosquatting attacks against GSD's own dependencies.
**Secret scanning.** Every commit and PR is scanned for hardcoded secrets.
Intentional test fixtures must be annotated with the project-standard
exclusion grammar (see `SECURITY.md` for the annotation format). Un-annotated
suppressions fail CI.
**Locale-safe text scanning.** Output and user-facing strings are scanned for
Unicode homoglyphs, bidirectional override characters, and invisible Unicode —
the class of attacks documented in CVE-2021-42574 ("Trojan Source") that can
hide malicious content in diffs.
---
## Trade-offs and limits
The security model described here meaningfully reduces the attack surface for
AI-driven development. It does not eliminate supply-chain risk.
**What the Package Legitimacy Gate reduces:** The probability that a
hallucinated or attacker-registered package reaches `npm install` without
a human checkpoint. The `[SLOP]` gate removes high-confidence bad packages
entirely; the `[SUS]` / `[ASSUMED]` gates require human review before
execution. This substantially raises the cost of a successful slopsquatting
attack.
**What the Package Legitimacy Gate does not eliminate:** A legitimate package
that is later compromised (account takeover, dependency confusion in its own
tree) is not caught by slopcheck, which checks registration signals at
research time. Lock files and `npm audit` at the dependency-integrity layer
are the controls for that class of attack.
**What the prompt injection defences reduce:** The probability that
user-controlled text in planning artifacts successfully overrides agent
instructions. Pattern-matching on known injection forms catches the
common cases; novel jailbreaks or low-signal injections may pass undetected.
The advisory-only posture means detection is logged but not blocked — a
deliberate choice that preserves workflow continuity at the cost of
not hard-stopping on a detection.
**What the prompt injection defences do not eliminate:** A sufficiently
creative injection that does not match known patterns, or an injection that
arrives through a channel the hooks do not cover. The previously uncovered
channel of content injected into a dependency's published README and read by a
subagent browsing documentation is now scanned at ingress by
`gsd-read-injection-scanner.js` (which covers WebFetch and WebSearch output)
and structurally isolated in-prompt by the `<security_context>` boundary in
research agents — but novel jailbreaks and low-signal injections may still pass
undetected. Defence in depth means each layer makes the attack harder, not that
any single layer makes it impossible.
**Reporting vulnerabilities.** Report via private GitHub security advisory at
`https://github.com/open-gsd/gsd-core/security/advisories/new`. Do not open
public issues. See [SECURITY.md](../../SECURITY.md) for the response timeline
and disclosure policy.
---
## Related
- [Commands](../COMMANDS.md) — includes `/gsd-secure-phase` and
`/gsd-code-review` with security-relevant flags
- [Architecture § Hook System](../ARCHITECTURE.md#hook-system) —
implementation detail on every hook, its event trigger, and safety properties
- [SECURITY.md](../../SECURITY.md) — vulnerability reporting, org-wide
security baseline, secret-scan exclusion governance, and dependency
integrity verification
- [Docs index](../README.md)