Skip to content
Agentmart
Submit a tool

hostile-control-flow-auditor

Trace sensitive operations from every reachable entry through callers, callees, callbacks, middleware, RPC, events, workers, queues, persistence, external…

Skill by dylmarriner

IndexedMIT
Write a review

Chalk Labs

Need help deploying hostile-control-flow-auditor?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/dylmarriner-hostile-control-flow-auditor

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Trace sensitive operations from every reachable entry through callers, callees, callbacks, middleware, RPC, events, workers, queues, persistence, external calls, success, and failure paths.

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/hostile-control-flow-auditor

What's inside

Skill name
hostile-control-flow-auditor
Description
Trace sensitive operations from every reachable entry through callers, callees, callbacks, middleware, RPC, events, workers, queues, persistence, external calls, success, and failure paths.
License
MIT
Instructions
52 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# hostile-control-flow-auditor

## Purpose
Trace sensitive operations from every reachable entry through callers, callees, callbacks, middleware, RPC, events, workers, queues, persistence, external calls, success, and failure paths.

## Threat model
Assume attacker-controlled or externally influenced data can reach every exposed, internal, asynchronous, persisted, operational, and compatibility boundary. Treat cross-tenant and privilege-changing effects as security-sensitive.

## Adversarial mindset
Do not trust names, comments, tests, intended reachability, or prior clean labels. Prefer valid-input abuse, alternate interfaces, replay, second-order effects, races, stale state, and partial failure.

## Inputs consumed
Entry points, routers, handlers, exported functions, callbacks, goroutines, worker loops, SQL writes, network and process sinks.

## Scope
All relevant hand-written code plus security-relevant generated, vendored, schema, migration, deployment, and test boundaries. Read applicable repository instructions and preserve unrelated changes.

## Search strategy
Start with tracked-file inventory and repository references, then use symbol/reference search, route/handler discovery, dangerous-sink search, schema/config inspection, and test mapping. Keep exact paths and line ranges.

## Investigation procedure
Build a call graph; mark trust boundaries and privilege changes; trace success/error/retry/cancel paths; test alternate interfaces and dead branches. Record evidence in audit-results/hostile-control-flow-auditor.md using skills/hostile-repository-auditor/references/artifact-template.md. Inspect callers and callees, success and failure, configuration, persistence, retries, and alternate paths before calling a component clean.

## Questions to ask
Could a callback or worker bypass the guard? Does failure commit? Is the operation reachable through another adapter?

## Cross-component checks
Compare application checks with DB/RLS, adapters, workers, queues, migrations, external responses, caches, and deployment defaults. Follow identity, tenant, state, and attacker data across every boundary.

## Evidence requirements
Cite exact locations, reachable entry point, attacker preconditions, trace, violated invariant, impact, mitigation search, commands/tests, and confidence. Separate confirmed, high-confidence, plausible, hardening, and non-issue.

## False-positive elimination procedure
Attempt to disprove reachability; search for centralized and alternate protections; verify the claimed sink and impact; test a bypass variant; downgrade or close when a real mitigation blocks the path.

## Coverage tracking
List files/components, entry points, callers/callees, workflows, inputs, trust boundaries, invariants, tests, gaps, and exclusions in the artifact. File opening alone is not coverage.

## Escalation conditions
Escalate to the master auditor for suspected Critical/High impact, cross-tenant or privilege escalation, exploitable chains, contradictory controls, or evidence requiring a second specialist.

## Stopping criteria
Stop only after the assigned scope, alternate interfaces, error/retry/concurrency paths, configuration and persistence effects, and tests have been considered, with gaps explicitly recorded.

## Required output artifact
A persistent audit-results/hostile-control-flow-auditor.md artifact containing every field in the shared template, plus findings and commands with results.

## Self-improvement notes
Record any search, heuristic, false-positive lesson, invariant, or cross-component pattern that materially improved detection. Generalize it and propose the owning skill update in audit-results/skill-improvement-log.md.

From dylmarriner/scos-memory, MIT.

More from dylmarriner/scos-memory

Signals

Stars
0
Forks
0
Open issues
0
Last commit (this folder)
Sep 1, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from dylmarriner

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get hostile-control-flow-auditor running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying hostile-control-flow-auditor?

CallGet help
Cite this page

hostile-control-flow-auditor skill. Agent Mart. https://agentmart.dev/skills/dylmarriner-hostile-control-flow-auditor (last updated 2026-10-24)