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 hardcoded-credential-huntgit 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/hardcoded-credential-hunt)<a href="https://agentmods.dev/skills/uphiago/recon-skills/hardcoded-credential-hunt"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hardcoded-credential-hunt.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 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 42 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 Supply Chain · line 64 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 Supply Chain · line 111 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.
- medium Data Exfiltration · line 135 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.
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 | $0.00022 | $0.01917 |
| Opus 5 | $0.00011 | $0.00958 |
| Sonnet 5 | $0.00004 | $0.00383 |
| Haiku 4.5 | $0.00002 | $0.00192 |
Grade C, and why
hardcoded-credential-hunt 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 -sk "https://target.com/api/config" | python3 -c " Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
compatibility: Requires curl, python3 How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hardcoded Credential Hunt
Detect credentials baked into client-side code or HTML responses. Targets include master passwords in form value attributes, secret keys in inline scripts, API tokens in configuration endpoints, and plaintext credentials leaked through debug error pages. This class of vulnerability bypasses authentication entirely — no brute force required.
When to Use
- An application serves HTML forms with pre-filled or hidden password fields.
- A configuration endpoint (
/api/config,/env,/settings) returns JSON with credential-like strings. - A debug/error page leaks application secrets in JavaScript variables.
- An unauthenticated API endpoint returns data that controls authentication (reset, exit registration, admin actions).
- JavaScript bundles contain string assignments matching password patterns.
Prerequisites
terminalwith curl and python3.- A target serving HTML, JSON, or JavaScript without proper authentication on configuration/settings endpoints.
- Access to at least one public page, form, or API endpoint.
Quick Detection
# Scan HTML for password fields with pre-filled values
curl --max-time 30 --connect-timeout 10 -sk "https://target.com/PATH" | grep -Eoi '(?:password|passwd|senha|pass|pwd|secret)\s*[=:"]\s*"?[^"&\s]{4,30}"?' | head -10
# Scan JSON config endpoints for credential-like keys
curl --max-time 30 --connect-timeout 10 -sk "https://target.com/api/config" | python3 -c "
import sys, json, re
try:
data = json.load(sys.stdin)
for k, v in data.items() if isinstance(data, dict) else []:
if any(x in k.lower() for x in ['pass','secret','key','token','auth']):
print(f'{k}: {v}')
except: pass
"
# Scan inline JavaScript for hardcoded secrets
curl --max-time 30 --connect-timeout 10 -sk "https://target.com/" | grep -Eo '(?:SECRET|PASSWORD|API_KEY|TOKEN)\s*=\s*"[^"]{8,}"' | head -10
Procedure
Phase 1 — HTML Form Inspection
Look for password fields with value attributes or hidden inputs containing credentials:
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 · 166 lines · 22 tokens per session scan C 27d86a741b20
hardcoded-credential-hunt is a skill published in the GitHub repository uphiago/recon-skills (1,245 stars, last pushed 6d ago), licensed MIT. It adds 22 tokens to every session and 1,917 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 2026-08-30.
Other skills, from other repositories
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-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.
securing-api-gateway-with-aws-waf
Securing API Gateway endpoints with AWS WAF by configuring managed rule groups for OWASP Top 10 protection, creating custom rate limiting rules, implementing bot control, setting up IP reputation filtering, and monitoring WAF metrics for security effectiveness.
auditing-aws-s3-bucket-permissions
Systematically audit AWS S3 bucket permissions to identify publicly accessible buckets, overly permissive ACLs, misconfigured bucket policies, and missing encryption settings using AWS CLI, S3audit, and Prowler to enforce least-privilege data access controls.
auditing-azure-active-directory-configuration
Auditing Microsoft Entra ID (Azure Active Directory) configuration to identify risky authentication policies, overly permissive role assignments, stale accounts, conditional access gaps, and guest user risks using AzureAD PowerShell, Microsoft Graph API, and ScoutSuite.
auditing-terraform-infrastructure-for-security
Auditing Terraform infrastructure-as-code for security misconfigurations using Checkov, tfsec, Terrascan, and OPA/Rego policies to detect overly permissive IAM policies, public resource exposure, missing encryption, and insecure defaults before cloud deployment.