Recon Skills is a pack of security-testing skills covering reconnaissance, web applications, APIs, authentication, vulnerability validation, cloud infrastructure, and reporting. Security professionals use it for authorized assessments of systems they own or have written permission to test. The catalogue entries are individual skills from the pack.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add uphiago/recon-skills --skill hunt-oauthgit clone --depth 1 https://github.com/uphiago/recon-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/uphiago/recon-skills/hunt-oauth)<a href="https://agentmods.dev/skills/uphiago/recon-skills/hunt-oauth"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-oauth/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/uphiago/recon-skills/hunt-oauth"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-oauth.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Supply Chain · line 215 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Privilege Escalation · line 273 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 292 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Data Exfiltration · line 190 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Excessive Agency · line 289 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.06712 |
| Opus 5 | $0.00014 | $0.03356 |
| Sonnet 5 | $0.00006 | $0.01342 |
| Haiku 4.5 | $0.00003 | $0.00671 |
Grade C, and why
hunt-oauth scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl --max-time 30 --connect-timeout 10 https://target.com/.well-known/openid-configuration | python3 -m json.tool Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl --max-time 30 --connect-timeout 10 -v "https://target.com/oauth/authorize?client_id=APP&redirect_uri=https://target.com/cb&response_type=code&state=FIXED_VALUE" How it starts
The opening of the file, as written. The whole thing — 420 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Crown Jewel Targets
OAuth vulnerabilities are among the highest-value bug classes in web security because they directly enable account takeover, session theft, and authentication bypass — the trifecta that programs pay most for.
Highest-value targets:
- Consumer identity providers (Google, Facebook, PayPal, Apple SSO integrations) — any compromise cascades across all relying parties
- Mobile apps with custom deep link OAuth handlers — Android/iOS intent handling is notoriously loose
- Multi-tenant SaaS platforms (GitLab, Reddit-scale apps) where one OAuth flaw hits millions of accounts
- Gaming/entertainment platforms with federated login (Rockstar, Oculus) — often security-immature teams
- Enterprise SSO connectors — critical infrastructure, high severity payouts
Asset types that pay most:
- OAuth authorization endpoints (
/oauth/authorize,/connect/authorize) - Token exchange endpoints (
/oauth/token) - Mobile deep link handlers (
push_notification_webview, custom scheme URIs) - Social login callback handlers (
/auth/callback,/oauth/callback)
Typical payouts: $500–$20,000+ depending on program; account takeover findings often hit max bounty.
Attack Surface Signals
URL Patterns to Hunt
/oauth/authorize
/oauth/token
/connect/authorize
/auth/callback
/oauth/callback
/login?redirect_uri=
/signin?next=
/auth?return_to=
/oauth/redirect
/push_notification_webview
Response Headers That Signal OAuth
Location: https://accounts.example.com/oauth/...
Set-Cookie: oauth_state=
WWW-Authenticate: Bearer
Content-Type: application/json (with access_token in body)
JavaScript Patterns (grep in JS bundles)
redirect_uri
client_id
response_type=code
response_type=token
state=
nonce=
oauth_token
access_token
push_notification_webview
deeplink
intent://
Tech Stack Signals
- Android apps with
intent-filterinAndroidManifest.xmlhandlinghttp://or custom scheme URIs - Apps using Doorkeeper, OmniAuth, Devise (Ruby), Passport.js (Node), Spring Security OAuth
- Social login buttons (Google, Facebook, Apple) = OAuth surface guaranteed
.well-known/openid-configurationpresent = full OIDC surface available
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 420 lines · 28 tokens per session scan C 3cf5c0ef149c
hunt-oauth is a skill published in the GitHub repository uphiago/recon-skills (1,254 stars, last pushed 10d ago), licensed MIT. It adds 28 tokens to every session and 6,712 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
detecting-suspicious-oauth-application-consent
Detect risky OAuth application consent grants in Azure AD / Microsoft Entra ID using Microsoft Graph API, audit logs, and permission analysis to identify illicit consent grant attacks.
auditing-gcp-iam-permissions
Auditing Google Cloud Platform IAM permissions to identify overly permissive bindings, primitive role usage, service account key proliferation, and cross-project access risks using gcloud CLI, Policy Analyzer, and IAM Recommender.
detecting-compromised-cloud-credentials
Detecting compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Detection.
implementing-aws-config-rules-for-compliance
Implementing AWS Config rules for continuous compliance monitoring of AWS resources, deploying managed and custom rules aligned to CIS and PCI DSS frameworks, configuring automatic remediation with SSM Automation, and aggregating compliance data across accounts.
implementing-cloud-dlp-for-data-protection
Implementing Cloud Data Loss Prevention (DLP) using Amazon Macie, Azure Information Protection, and Google Cloud DLP API to discover, classify, and protect sensitive data across cloud storage, databases, and data pipelines.
implementing-cloud-trail-log-analysis
Implementing AWS CloudTrail log analysis for security monitoring, threat detection, and forensic investigation using Athena, CloudWatch Logs Insights, and SIEM integration to identify unauthorized access, privilege escalation, and suspicious API activity.